WorldWideScience

Sample records for multispectral satellite images

  1. Synchronous atmospheric radiation correction of GF-2 satellite multispectral image

    Science.gov (United States)

    Bian, Fuqiang; Fan, Dongdong; Zhang, Yan; Wang, Dandan

    2018-02-01

    GF-2 remote sensing products have been widely used in many fields for its high-quality information, which provides technical support for the the macroeconomic decisions. Atmospheric correction is the necessary part in the data preprocessing of the quantitative high resolution remote sensing, which can eliminate the signal interference in the radiation path caused by atmospheric scattering and absorption, and reducting apparent reflectance into real reflectance of the surface targets. Aiming at the problem that current research lack of atmospheric date which are synchronization and region matching of the surface observation image, this research utilize the MODIS Level 1B synchronous data to simulate synchronized atmospheric condition, and write programs to implementation process of aerosol retrieval and atmospheric correction, then generate a lookup table of the remote sensing image based on the radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum) to correct the atmospheric effect of multispectral image from GF-2 satellite PMS-1 payload. According to the correction results, this paper analyzes the pixel histogram of the reflectance spectrum of the 4 spectral bands of PMS-1, and evaluates the correction results of different spectral bands. Then conducted a comparison experiment on the same GF-2 image based on the QUAC. According to the different targets respectively statistics the average value of NDVI, implement a comparative study of NDVI from two different results. The degree of influence was discussed by whether to adopt synchronous atmospheric date. The study shows that the result of the synchronous atmospheric parameters have significantly improved the quantitative application of the GF-2 remote sensing data.

  2. Approaching bathymetry estimation from high resolution multispectral satellite images using a neuro-fuzzy technique

    Science.gov (United States)

    Corucci, Linda; Masini, Andrea; Cococcioni, Marco

    2011-01-01

    This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.

  3. Multispectral thermal imaging

    Energy Technology Data Exchange (ETDEWEB)

    Weber, P.G.; Bender, S.C.; Borel, C.C.; Clodius, W.B.; Smith, B.W. [Los Alamos National Lab., NM (United States). Space and Remote Sensing Sciences Group; Garrett, A.; Pendergast, M.M. [Westinghouse Savannah River Corp., Aiken, SC (United States). Savannah River Technology Center; Kay, R.R. [Sandia National Lab., Albuquerque, NM (United States). Monitoring Systems and Technology Center

    1998-12-01

    Many remote sensing applications rely on imaging spectrometry. Here the authors use imaging spectrometry for thermal and multispectral signatures measured from a satellite platform enhanced with a combination of accurate calibrations and on-board data for correcting atmospheric distortions. The approach is supported by physics-based end-to-end modeling and analysis, which permits a cost-effective balance between various hardware and software aspects. The goal is to develop and demonstrate advanced technologies and analysis tools toward meeting the needs of the customer; at the same time, the attributes of this system can address other applications in such areas as environmental change, agriculture, and volcanology.

  4. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  5. Neural network multispectral satellite images classification of volcanic ash plumes in a cloudy scenario

    Directory of Open Access Journals (Sweden)

    Matteo Picchiani

    2015-03-01

    Full Text Available This work shows the potential use of neural networks in the characterization of eruptive events monitored by satellite, through fast and automatic classification of multispectral images. The algorithm has been developed for the MODIS instrument and can easily be extended to other similar sensors. Six classes have been defined paying particular attention to image regions that represent the different surfaces that could possibly be found under volcanic ash clouds. Complex cloudy scenarios composed by images collected during the Icelandic eruptions of the Eyjafjallajökull (2010 and Grimsvötn (2011 volcanoes have been considered as test cases. A sensitivity analysis on the MODIS TIR and VIS channels has been performed to optimize the algorithm. The neural network has been trained with the first image of the dataset, while the remaining data have been considered as independent validation sets. Finally, the neural network classifier’s results have been compared with maps classified with several interactive procedures performed in a consolidated operational framework. This comparison shows that the automatic methodology proposed achieves a very promising performance, showing an overall accuracy greater than 84%, for the Eyjafjalla - jökull event, and equal to 74% for the Grimsvötn event. 

  6. Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.J.

    2000-01-03

    Sandia National Laboratories (SNL), Los Alamos National Laboratory (LANL), and the Savannah River Technology Center (SRTC) have developed a diverse group of algorithms for processing and analyzing the data that will be collected by the Multispectral Thermal Imager (MTI) after launch late in 1999. Each of these algorithms must be verified by comparison to independent surface and atmospheric measurements. SRTC has selected 13 sites in the continental U.S. for ground truth data collections. These sites include a high altitude cold water target (Crater Lake), cooling lakes and towers in the warm, humid southeastern US, Department of Energy (DOE) climate research sites, the NASA Stennis satellite Validation and Verification (V and V) target array, waste sites at the Savannah River Site, mining sites in the Four Corners area and dry lake beds in the southwestern US. SRTC has established mutually beneficial relationships with the organizations that manage these sites to make use of their operating and research data and to install additional instrumentation needed for MTI algorithm V and V.

  7. Band co-registration modeling of LAPAN-A3/IPB multispectral imager based on satellite attitude

    Science.gov (United States)

    Hakim, P. R.; Syafrudin, A. H.; Utama, S.; Jayani, A. P. S.

    2018-05-01

    One of significant geometric distortion on images of LAPAN-A3/IPB multispectral imager is co-registration error between each color channel detector. Band co-registration distortion usually can be corrected by using several approaches, which are manual method, image matching algorithm, or sensor modeling and calibration approach. This paper develops another approach to minimize band co-registration distortion on LAPAN-A3/IPB multispectral image by using supervised modeling of image matching with respect to satellite attitude. Modeling results show that band co-registration error in across-track axis is strongly influenced by yaw angle, while error in along-track axis is fairly influenced by both pitch and roll angle. Accuracy of the models obtained is pretty good, which lies between 1-3 pixels error for each axis of each pair of band co-registration. This mean that the model can be used to correct the distorted images without the need of slower image matching algorithm, nor the laborious effort needed in manual approach and sensor calibration. Since the calculation can be executed in order of seconds, this approach can be used in real time quick-look image processing in ground station or even in satellite on-board image processing.

  8. Multispectral imaging for biometrics

    Science.gov (United States)

    Rowe, Robert K.; Corcoran, Stephen P.; Nixon, Kristin A.; Ostrom, Robert E.

    2005-03-01

    Automated identification systems based on fingerprint images are subject to two significant types of error: an incorrect decision about the identity of a person due to a poor quality fingerprint image and incorrectly accepting a fingerprint image generated from an artificial sample or altered finger. This paper discusses the use of multispectral sensing as a means to collect additional information about a finger that significantly augments the information collected using a conventional fingerprint imager based on total internal reflectance. In the context of this paper, "multispectral sensing" is used broadly to denote a collection of images taken under different polarization conditions and illumination configurations, as well as using multiple wavelengths. Background information is provided on conventional fingerprint imaging. A multispectral imager for fingerprint imaging is then described and a means to combine the two imaging systems into a single unit is discussed. Results from an early-stage prototype of such a system are shown.

  9. Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

    Directory of Open Access Journals (Sweden)

    Meng Lu

    2017-10-01

    Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

  10. Multispectral Image Feature Points

    Directory of Open Access Journals (Sweden)

    Cristhian Aguilera

    2012-09-01

    Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  11. Multispectral analytical image fusion

    International Nuclear Information System (INIS)

    Stubbings, T.C.

    2000-04-01

    With new and advanced analytical imaging methods emerging, the limits of physical analysis capabilities and furthermore of data acquisition quantities are constantly pushed, claiming high demands to the field of scientific data processing and visualisation. Physical analysis methods like Secondary Ion Mass Spectrometry (SIMS) or Auger Electron Spectroscopy (AES) and others are capable of delivering high-resolution multispectral two-dimensional and three-dimensional image data; usually this multispectral data is available in form of n separate image files with each showing one element or other singular aspect of the sample. There is high need for digital image processing methods enabling the analytical scientist, confronted with such amounts of data routinely, to get rapid insight into the composition of the sample examined, to filter the relevant data and to integrate the information of numerous separate multispectral images to get the complete picture. Sophisticated image processing methods like classification and fusion provide possible solution approaches to this challenge. Classification is a treatment by multivariate statistical means in order to extract analytical information. Image fusion on the other hand denotes a process where images obtained from various sensors or at different moments of time are combined together to provide a more complete picture of a scene or object under investigation. Both techniques are important for the task of information extraction and integration and often one technique depends on the other. Therefore overall aim of this thesis is to evaluate the possibilities of both techniques regarding the task of analytical image processing and to find solutions for the integration and condensation of multispectral analytical image data in order to facilitate the interpretation of the enormous amounts of data routinely acquired by modern physical analysis instruments. (author)

  12. PROCEDURES FOR ACCURATE PRODUCTION OF COLOR IMAGES FROM SATELLITE OR AIRCRAFT MULTISPECTRAL DIGITAL DATA.

    Science.gov (United States)

    Duval, Joseph S.

    1985-01-01

    Because the display and interpretation of satellite and aircraft remote-sensing data make extensive use of color film products, accurate reproduction of the color images is important. To achieve accurate color reproduction, the exposure and chemical processing of the film must be monitored and controlled. By using a combination of sensitometry, densitometry, and transfer functions that control film response curves, all of the different steps in the making of film images can be monitored and controlled. Because a sensitometer produces a calibrated exposure, the resulting step wedge can be used to monitor the chemical processing of the film. Step wedges put on film by image recording machines provide a means of monitoring the film exposure and color balance of the machines.

  13. BEE FORAGE MAPPING BASED ON MULTISPECTRAL IMAGES LANDSAT

    Directory of Open Access Journals (Sweden)

    A. Moskalenko

    2016-10-01

    Full Text Available Possibilities of bee forage identification and mapping based on multispectral images have been shown in the research. Spectral brightness of bee forage has been determined with the use of satellite images. The effectiveness of some methods of image classification for mapping of bee forage is shown. Keywords: bee forage, mapping, multispectral images, image classification.

  14. Multi-spectral band selection for satellite-based systems

    International Nuclear Information System (INIS)

    Clodius, W.B.; Weber, P.G.; Borel, C.C.; Smith, B.W.

    1998-01-01

    The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed

  15. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  16. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

    Science.gov (United States)

    Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

    2017-05-01

    WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

  17. Computational multispectral video imaging [Invited].

    Science.gov (United States)

    Wang, Peng; Menon, Rajesh

    2018-01-01

    Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430-718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

  18. Multispectral Landsat images of Antartica

    Energy Technology Data Exchange (ETDEWEB)

    Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.; Eliason, E.M.; Fergurson, H.M.

    1988-01-01

    The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

  19. Multispectral Panoramic Imaging System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — International Electronic Machines Corporation, a leader in the design of precision imaging systems, will develop an innovative multispectral, panoramic imaging...

  20. Multi-spectral imager

    CSIR Research Space (South Africa)

    Stolper, R

    2006-02-01

    Full Text Available channel are boresighted with two beamsplitter windows; and • The IR system is boresighted. APPLICATION High-voltage environment • Detecting loose strands, bolts and nuts; • Detecting Corona discharges on insulator discs; • Detecting... and locating spark gaps; • Detecting and locating RIV sources; • Audit sub-stations and transmission lines for audio noise and Corona activities. RECORDINGS / APPLICATIONS REPORTING TOOL: MultiSOFT • Image handling software for grabbing, processing...

  1. Multispectral imaging of wok fried vegetables

    DEFF Research Database (Denmark)

    Løje, Hanne; Dissing, Bjørn Skovlund; Clemmensen, Line Katrine Harder

    2011-01-01

    This paper shows how multispectral images can be used to assess color change over time in wok fried vegetables. We present results where feature selection was performed with sparse methods from the multispectral images to detect the color changes of wok fried carrots and celeriac stored at +5°C...

  2. Multispectral image enhancement processing for microsat-borne imager

    Science.gov (United States)

    Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin

    2017-10-01

    With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.

  3. Multispectral analysis of multimodal images

    Energy Technology Data Exchange (ETDEWEB)

    Kvinnsland, Yngve; Brekke, Njaal (Dept. of Surgical Sciences, Univ. of Bergen, Bergen (Norway)); Taxt, Torfinn M.; Gruener, Renate (Dept. of Biomedicine, Univ. of Bergen, Bergen (Norway))

    2009-02-15

    An increasing number of multimodal images represent a valuable increase in available image information, but at the same time it complicates the extraction of diagnostic information across the images. Multispectral analysis (MSA) has the potential to simplify this problem substantially as unlimited number of images can be combined, and tissue properties across the images can be extracted automatically. Materials and methods. We have developed a software solution for MSA containing two algorithms for unsupervised classification, an EM-algorithm finding multinormal class descriptions and the k-means clustering algorithm, and two for supervised classification, a Bayesian classifier using multinormal class descriptions and a kNN-algorithm. The software has an efficient user interface for the creation and manipulation of class descriptions, and it has proper tools for displaying the results. Results. The software has been tested on different sets of images. One application is to segment cross-sectional images of brain tissue (T1- and T2-weighted MR images) into its main normal tissues and brain tumors. Another interesting set of images are the perfusion maps and diffusion maps, derived images from raw MR images. The software returns segmentation that seem to be sensible. Discussion. The MSA software appears to be a valuable tool for image analysis with multimodal images at hand. It readily gives a segmentation of image volumes that visually seems to be sensible. However, to really learn how to use MSA, it will be necessary to gain more insight into what tissues the different segments contain, and the upcoming work will therefore be focused on examining the tissues through for example histological sections.

  4. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-06-01

    Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

  5. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multispectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  6. Multispectral Imaging of Wok-Fried Vegetables

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Dissing, Bjørn Skovlund; Hyldig, Grethe

    2012-01-01

    Quality control in the food industry is often performed by measuring various chemical compounds in the food involved. The authors propose an imaging concept for acquiring high-quality multispectral images to evaluate optical reflection changes in carrots and celeriac over a period of 14 days....... For comparison, sensory analysis was performed on the same samples. Prior to multispectral image recording, the vegetables were prefried and frozen at -30 °C for 4 months. During the 14 days of image recording, the vegetables were kept at +5 °C. In this period, surface changes and thereby reflectance properties...

  7. Supervised Classification Performance of Multispectral Images

    OpenAIRE

    Perumal, K.; Bhaskaran, R.

    2010-01-01

    Nowadays government and private agencies use remote sensing imagery for a wide range of applications from military applications to farm development. The images may be a panchromatic, multispectral, hyperspectral or even ultraspectral of terra bytes. Remote sensing image classification is one amongst the most significant application worlds for remote sensing. A few number of image classification algorithms have proved good precision in classifying remote sensing data. But, of late, due to the ...

  8. Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

    Science.gov (United States)

    Kandylakis, Z.; Karantzalos, K.

    2016-06-01

    In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

  9. Multispectral Imaging in Cultural Heritage Conservation

    Science.gov (United States)

    Del Pozo, S.; Rodríguez-Gonzálvez, P.; Sánchez-Aparicio, L. J.; Muñoz-Nieto, A.; Hernández-López, D.; Felipe-García, B.; González-Aguilera, D.

    2017-08-01

    This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum). In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

  10. MULTISPECTRAL IMAGING IN CULTURAL HERITAGE CONSERVATION

    Directory of Open Access Journals (Sweden)

    S. Del Pozo

    2017-08-01

    Full Text Available This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum. In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

  11. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields

    NARCIS (Netherlands)

    Hamzeh, Saied; Naseri, Abd Ali; Alavipanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

    2016-01-01

    This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image

  12. Precise Multi-Spectral Dermatological Imaging

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Carstensen, Jens Michael; Ersbøll, Bjarne Kjær

    2004-01-01

    In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral dermatological images is proposed. The system is made up of an integrating sphere, light emitting diodes and a generic monochromatic camera. The system can collect up to 10 different spectral bands....... These spectral bands vary from ultraviolet to near infrared. The welldefined and diffuse illumination of the optically closed scene aims to avoid shadows and specular reflections. Furthermore, the system has been developed to guarantee the reproducibility of the collected images. This allows for comparative...

  13. Oximetry using multispectral imaging: theory and application

    Science.gov (United States)

    MacKenzie, Lewis E.; Harvey, Andrew R.

    2018-06-01

    Multispectral imaging (MSI) is a technique for measurement of blood oxygen saturation in vivo that can be applied using various imaging modalities to provide new insights into physiology and disease development. This tutorial aims to provide a thorough introduction to the theory and application of MSI oximetry for researchers new to the field, whilst also providing detailed information for more experienced researchers. The optical theory underlying two-wavelength oximetry, three-wavelength oximetry, pulse oximetry, and multispectral oximetry algorithms are described in detail. The varied challenges of applying MSI oximetry to in vivo applications are outlined and discussed, covering: the optical properties of blood and tissue, optical paths in blood vessels, tissue auto-fluorescence, oxygen diffusion, and common oximetry artefacts. Essential image processing techniques for MSI are discussed, in particular, image acquisition, image registration strategies, and blood vessel line profile fitting. Calibration and validation strategies for MSI are discussed, including comparison techniques, physiological interventions, and phantoms. The optical principles and unique imaging capabilities of various cutting-edge MSI oximetry techniques are discussed, including photoacoustic imaging, spectroscopic optical coherence tomography, and snapshot MSI.

  14. Multispectral open-air intraoperative fluorescence imaging.

    Science.gov (United States)

    Behrooz, Ali; Waterman, Peter; Vasquez, Kristine O; Meganck, Jeff; Peterson, Jeffrey D; Faqir, Ilias; Kempner, Joshua

    2017-08-01

    Intraoperative fluorescence imaging informs decisions regarding surgical margins by detecting and localizing signals from fluorescent reporters, labeling targets such as malignant tissues. This guidance reduces the likelihood of undetected malignant tissue remaining after resection, eliminating the need for additional treatment or surgery. The primary challenges in performing open-air intraoperative fluorescence imaging come from the weak intensity of the fluorescence signal in the presence of strong surgical and ambient illumination, and the auto-fluorescence of non-target components, such as tissue, especially in the visible spectral window (400-650 nm). In this work, a multispectral open-air fluorescence imaging system is presented for translational image-guided intraoperative applications, which overcomes these challenges. The system is capable of imaging weak fluorescence signals with nanomolar sensitivity in the presence of surgical illumination. This is done using synchronized fluorescence excitation and image acquisition with real-time background subtraction. Additionally, the system uses a liquid crystal tunable filter for acquisition of multispectral images that are used to spectrally unmix target fluorescence from non-target auto-fluorescence. Results are validated by preclinical studies on murine models and translational canine oncology models.

  15. Reproducible high-resolution multispectral image acquisition in dermatology

    Science.gov (United States)

    Duliu, Alexandru; Gardiazabal, José; Lasser, Tobias; Navab, Nassir

    2015-07-01

    Multispectral image acquisitions are increasingly popular in dermatology, due to their improved spectral resolution which enables better tissue discrimination. Most applications however focus on restricted regions of interest, imaging only small lesions. In this work we present and discuss an imaging framework for high-resolution multispectral imaging on large regions of interest.

  16. Multispectral imaging for medical diagnosis

    Science.gov (United States)

    Anselmo, V. J.

    1977-01-01

    Photography technique determines amount of morbidity present in tissue. Imaging apparatus incorporates numerical filtering. Overall system operates in near-real time. Information gained from this system enables physician to understand extent of injury and leads to accelerated treatment.

  17. Highly Protable Airborne Multispectral Imaging System

    Science.gov (United States)

    Lehnemann, Robert; Mcnamee, Todd

    2001-01-01

    A portable instrumentation system is described that includes and airborne and a ground-based subsytem. It can acquire multispectral image data over swaths of terrain ranging in width from about 1.5 to 1 km. The system was developed especially for use in coastal environments and is well suited for performing remote sensing and general environmental monitoring. It includes a small,munpilotaed, remotely controlled airplance that carries a forward-looking camera for navigation, three downward-looking monochrome video cameras for imaging terrain in three spectral bands, a video transmitter, and a Global Positioning System (GPS) reciever.

  18. Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

    Science.gov (United States)

    Clark, M. L.; Kilham, N. E.

    2015-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

  19. Peach Flower Monitoring Using Aerial Multispectral Imaging

    Directory of Open Access Journals (Sweden)

    Ryan Horton

    2017-01-01

    Full Text Available One of the tools for optimal crop production is regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This paper presents the development of an image processing algorithm to detect peach blossoms on trees. Aerial images of peach (Prunus persica trees were acquired from both experimental and commercial peach orchards in the southwestern part of Idaho using an off-the-shelf unmanned aerial system (UAS, equipped with a multispectral camera (near-infrared, green, blue. The image processing algorithm included contrast stretching of the three bands to enhance the image and thresholding segmentation method to detect the peach blossoms. Initial results showed that the image processing algorithm could detect peach blossoms with an average detection rate of 84.3% and demonstrated good potential as a monitoring tool for orchard management.

  20. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Directory of Open Access Journals (Sweden)

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  1. Utilization of Multispectral Images for Meat Color Measurements

    DEFF Research Database (Denmark)

    Trinderup, Camilla Himmelstrup; Dahl, Anders Lindbjerg; Carstensen, Jens Michael

    2013-01-01

    This short paper describes how the use of multispectral imaging for color measurement can be utilized in an efficient and descriptive way for meat scientists. The basis of the study is meat color measurements performed with a multispectral imaging system as well as with a standard colorimeter...... of color and color variance than what is obtained by the standard colorimeter....

  2. An integrated compact airborne multispectral imaging system using embedded computer

    Science.gov (United States)

    Zhang, Yuedong; Wang, Li; Zhang, Xuguo

    2015-08-01

    An integrated compact airborne multispectral imaging system using embedded computer based control system was developed for small aircraft multispectral imaging application. The multispectral imaging system integrates CMOS camera, filter wheel with eight filters, two-axis stabilized platform, miniature POS (position and orientation system) and embedded computer. The embedded computer has excellent universality and expansibility, and has advantages in volume and weight for airborne platform, so it can meet the requirements of control system of the integrated airborne multispectral imaging system. The embedded computer controls the camera parameters setting, filter wheel and stabilized platform working, image and POS data acquisition, and stores the image and data. The airborne multispectral imaging system can connect peripheral device use the ports of the embedded computer, so the system operation and the stored image data management are easy. This airborne multispectral imaging system has advantages of small volume, multi-function, and good expansibility. The imaging experiment results show that this system has potential for multispectral remote sensing in applications such as resource investigation and environmental monitoring.

  3. Multispectral Imaging for Determination of Astaxanthin Concentration in Salmonids

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Nielsen, Michael Engelbrecht; Ersbøll, Bjarne Kjær

    2011-01-01

    Multispectral imaging has been evaluated for characterization of the concentration of a specific cartenoid pigment; astaxanthin. 59 fillets of rainbow trout, Oncorhynchus mykiss, were filleted and imaged using a rapid multispectral imaging device for quantitative analysis. The multispectral imaging...... device captures reflection properties in 19 distinct wavelength bands, prior to determination of the true concentration of astaxanthin. The samples ranged from 0.20 to 4.34 mu g per g fish. A PLSR model was calibrated to predict astaxanthin concentration from novel images, and showed good results...... concentration in rainbow trout fillets....

  4. Satellite image collection optimization

    Science.gov (United States)

    Martin, William

    2002-09-01

    Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

  5. Novel instrumentation of multispectral imaging technology for detecting tissue abnormity

    Science.gov (United States)

    Yi, Dingrong; Kong, Linghua

    2012-10-01

    Multispectral imaging is becoming a powerful tool in a wide range of biological and clinical studies by adding spectral, spatial and temporal dimensions to visualize tissue abnormity and the underlying biological processes. A conventional spectral imaging system includes two physically separated major components: a band-passing selection device (such as liquid crystal tunable filter and diffraction grating) and a scientific-grade monochromatic camera, and is expensive and bulky. Recently micro-arrayed narrow-band optical mosaic filter was invented and successfully fabricated to reduce the size and cost of multispectral imaging devices in order to meet the clinical requirement for medical diagnostic imaging applications. However the challenging issue of how to integrate and place the micro filter mosaic chip to the targeting focal plane, i.e., the imaging sensor, of an off-shelf CMOS/CCD camera is not reported anywhere. This paper presents the methods and results of integrating such a miniaturized filter with off-shelf CMOS imaging sensors to produce handheld real-time multispectral imaging devices for the application of early stage pressure ulcer (ESPU) detection. Unlike conventional multispectral imaging devices which are bulky and expensive, the resulting handheld real-time multispectral ESPU detector can produce multiple images at different center wavelengths with a single shot, therefore eliminates the image registration procedure required by traditional multispectral imaging technologies.

  6. Vicarious Calibration of Beijing-1 Multispectral Imagers

    Directory of Open Access Journals (Sweden)

    Zhengchao Chen

    2014-02-01

    Full Text Available For on-orbit calibration of the Beijing-1 multispectral imagers (Beijing-1/MS, a field calibration campaign was performed at the Dunhuang calibration site during September and October of 2008. Based on the in situ data and images from Beijing-1 and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS, three vicarious calibration methods (i.e., reflectance-based, irradiance-based, and cross-calibration were used to calculate the top-of-atmosphere (TOA radiance of Beijing-1. An analysis was then performed to determine or identify systematic and accidental errors, and the overall uncertainty was assessed for each individual method. The findings show that the reflectance-based method has an uncertainty of more than 10% if the aerosol optical depth (AOD exceeds 0.2. The cross-calibration method is able to reach an error level within 7% if the images are selected carefully. The final calibration coefficients were derived from the irradiance-based data for 6 September 2008, with an uncertainty estimated to be less than 5%.

  7. Image quality (IQ) guided multispectral image compression

    Science.gov (United States)

    Zheng, Yufeng; Chen, Genshe; Wang, Zhonghai; Blasch, Erik

    2016-05-01

    Image compression is necessary for data transportation, which saves both transferring time and storage space. In this paper, we focus on our discussion on lossy compression. There are many standard image formats and corresponding compression algorithms, for examples, JPEG (DCT -- discrete cosine transform), JPEG 2000 (DWT -- discrete wavelet transform), BPG (better portable graphics) and TIFF (LZW -- Lempel-Ziv-Welch). The image quality (IQ) of decompressed image will be measured by numerical metrics such as root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural Similarity (SSIM) Index. Given an image and a specified IQ, we will investigate how to select a compression method and its parameters to achieve an expected compression. Our scenario consists of 3 steps. The first step is to compress a set of interested images by varying parameters and compute their IQs for each compression method. The second step is to create several regression models per compression method after analyzing the IQ-measurement versus compression-parameter from a number of compressed images. The third step is to compress the given image with the specified IQ using the selected compression method (JPEG, JPEG2000, BPG, or TIFF) according to the regressed models. The IQ may be specified by a compression ratio (e.g., 100), then we will select the compression method of the highest IQ (SSIM, or PSNR). Or the IQ may be specified by a IQ metric (e.g., SSIM = 0.8, or PSNR = 50), then we will select the compression method of the highest compression ratio. Our experiments tested on thermal (long-wave infrared) images (in gray scales) showed very promising results.

  8. Multispectral imaging of acute wound tissue oxygenation

    Directory of Open Access Journals (Sweden)

    Audrey Huong

    2017-05-01

    Full Text Available This paper investigates the appropriate range of values for the transcutaneous blood oxygen saturation (StO2 of granulating tissues and the surrounding tissue that can ensure timely wound recovery. This work has used a multispectral imaging system to collect wound images at wavelengths ranging between 520nm and 600nm with a resolution of 10nm. As part of this research, a pilot study was conducted on three injured individuals with superficial wounds of different wound ages at different skin locations. The StO2 value predicted for the examined wounds using the Extended Modified Lambert–Beer model revealed a mean StO2 of 61±10.3% compared to 41.6±6.2% at the surrounding tissues, and 50.1±1.53% for control sites. These preliminary results contribute to the existing knowledge on the possible range and variation of wound bed StO2 that are to be used as indicators of the functioning of the vasomotion system and wound health. This study has concluded that a high StO2 of approximately 60% and a large fluctuation in this value should precede a good progression in wound healing.

  9. Fusion of multispectral and panchromatic images using multirate filter banks

    Institute of Scientific and Technical Information of China (English)

    Wang Hong; Jing Zhongliang; Li Jianxun

    2005-01-01

    In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.

  10. Color enhancement in multispectral image of human skin

    Science.gov (United States)

    Mitsui, Masanori; Murakami, Yuri; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

    2003-07-01

    Multispectral imaging is receiving attention in medical color imaging, as high-fidelity color information can be acquired by the multispectral image capturing. On the other hand, as color enhancement in medical color image is effective for distinguishing lesion from normal part, we apply a new technique for color enhancement using multispectral image to enhance the features contained in a certain spectral band, without changing the average color distribution of original image. In this method, to keep the average color distribution, KL transform is applied to spectral data, and only high-order KL coefficients are amplified in the enhancement. Multispectral images of human skin of bruised arm are captured by 16-band multispectral camera, and the proposed color enhancement is applied. The resultant images are compared with the color images reproduced assuming CIE D65 illuminant (obtained by natural color reproduction technique). As a result, the proposed technique successfully visualizes unclear bruised lesions, which are almost invisible in natural color images. The proposed technique will provide support tool for the diagnosis in dermatology, visual examination in internal medicine, nursing care for preventing bedsore, and so on.

  11. Multispectral Stokes polarimetry for dermatoscopic imaging

    Science.gov (United States)

    Castillejos, Y.; Martínez-Ponce, Geminiano; Mora-Nuñez, Azael; Castro-Sanchez, R.

    2015-12-01

    Most of skin pathologies, including melanoma and basal/squamous cell carcinoma, are related to alterations in external and internal order. Usually, physicians rely on their empirical expertise to diagnose these ills normally assisted with dermatoscopes. When there exists skin cancer suspicion, a cytology or biopsy is made, but both laboratory tests imply an invasive procedure. In this regard, a number of non-invasive optical techniques have been proposed recently to improve the diagnostic certainty and assist in the early detection of cutaneous cancer. Herein, skin optical properties are derived with a multispectral polarimetric dermatoscope using three different illumination wavelength intervals centered at 470, 530 and 635nm. The optical device consist of two polarizing elements, a quarter-wave plate and a linear polarizer, rotating at a different angular velocity and a CCD array as the photoreceiver. The modulated signal provided by a single pixel in the acquired image sequence is analyzed with the aim of computing the Stokes parameters. Changes in polarization state of selected wavelengths provide information about the presence of skin pigments such as melanin and hemoglobin species as well as collagen structure, among other components. These skin attributes determine the local physiology or pathology. From the results, it is concluded that optical polarimetry will provide additional elements to dermatologists in their diagnostic task.

  12. Pattern Decomposition Method and a New Vegetation Index for Hyper-Multispectral Satellite Data Analysis

    Science.gov (United States)

    Muramatsu, K.; Furumi, S.; Hayashi, A.; Shiono, Y.; Ono, A.; Fujiwara, N.; Daigo, M.; Ochiai, F.

    We have developed the ``pattern decomposition method'' based on linear spectral mixing of ground objects for n-dimensional satellite data. In this method, spectral response patterns for each pixel in an image are decomposed into three components using three standard spectral shape patterns determined from the image data. Applying this method to AMSS (Airborne Multi-Spectral Scanner) data, eighteen-dimensional data are successfully transformed into three-dimensional data. Using the three components, we have developed a new vegetation index in which all the multispectral data are reflected. We consider that the index should be linear to the amount of vegetation and vegetation vigor. To validate the index, its relations to vegetation types, vegetation cover ratio, and chlorophyll contents of a leaf were studied using spectral reflectance data measured in the field with a spectrometer. The index was sensitive to vegetation types and vegetation vigor. This method and index are very useful for assessment of vegetation vigor, classifying land cover types and monitoring vegetation changes

  13. Multi-spectral endogenous fluorescence imaging for bacterial differentiation

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

    2017-07-01

    In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

  14. Multispectral image pansharpening based on the contourlet transform

    Energy Technology Data Exchange (ETDEWEB)

    Amro, Israa; Mateos, Javier, E-mail: iamro@correo.ugr.e, E-mail: jmd@decsai.ugr.e [Departamento de Ciencias de la Computacion e I.A., Universidad de Granada, 18071 Granada (Spain)

    2010-02-01

    Pansharpening is a technique that fuses the information of a low resolution multispectral image (MS) and a high resolution panchromatic image (PAN), usually remote sensing images, to provide a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets based algorithms. Recently, the contourlet transform has been proposed. This transform combines the advantages of the wavelets transform with a more efficient directional information representation. In this paper we propose a new pansharpening method based on contourlets, compare with its wavelet counterpart and assess its performance numerically and visually.

  15. A survey of classical methods and new trends in pansharpening of multispectral images

    Directory of Open Access Journals (Sweden)

    Katsaggelos Aggelos

    2011-01-01

    Full Text Available Abstract There exist a number of satellites on different earth observation platforms, which provide multispectral images together with a panchromatic image, that is, an image containing reflectance data representative of a wide range of bands and wavelengths. Pansharpening is a pixel-level fusion technique used to increase the spatial resolution of the multispectral image while simultaneously preserving its spectral information. In this paper, we provide a review of the pan-sharpening methods proposed in the literature giving a clear classification of them and a description of their main characteristics. Finally, we analyze how the quality of the pansharpened images can be assessed both visually and quantitatively and examine the different quality measures proposed for that purpose.

  16. Lossless compression of multispectral images using spectral information

    Science.gov (United States)

    Ma, Long; Shi, Zelin; Tang, Xusheng

    2009-10-01

    Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

  17. Preliminary analysis of the forest health state based on multispectral images acquired by Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Czapski Paweł

    2015-09-01

    Full Text Available The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat 8 OLI instrument (Operational Land Imager.

  18. Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

    Directory of Open Access Journals (Sweden)

    Jin Li

    2014-01-01

    Full Text Available Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC combined with image data compression (IDC approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE. Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS-based algorithm has better compression performance than the traditional compression approaches.

  19. Multispectral image compression based on DSC combined with CCSDS-IDC.

    Science.gov (United States)

    Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

    2014-01-01

    Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

  20. Acquisition performance of LAPAN-A3/IPB multispectral imager in real-time mode of operation

    Science.gov (United States)

    Hakim, P. R.; Permala, R.; Jayani, A. P. S.

    2018-05-01

    LAPAN-A3/IPB satellite was launched in June 2016 and its multispectral imager has been producing Indonesian coverage images. In order to improve its support for remote sensing application, the imager should produce images with high quality and quantity. To improve the quantity of LAPAN-A3/IPB multispectral image captured, image acquisition could be executed in real-time mode from LAPAN ground station in Bogor when the satellite passes west Indonesia region. This research analyses the performance of LAPAN-A3/IPB multispectral imager acquisition in real-time mode, in terms of image quality and quantity, under assumption of several on-board and ground segment limitations. Results show that with real-time operation mode, LAPAN-A3/IPB multispectral imager could produce twice as much as image coverage compare to recorded mode. However, the images produced in real-time mode will have slightly degraded quality due to image compression process involved. Based on several analyses that have been done in this research, it is recommended to use real-time acquisition mode whenever it possible, unless for some circumstances that strictly not allow any quality degradation of the images produced.

  1. Skin condition measurement by using multispectral imaging system (Conference Presentation)

    Science.gov (United States)

    Jung, Geunho; Kim, Sungchul; Kim, Jae Gwan

    2017-02-01

    There are a number of commercially available low level light therapy (LLLT) devices in a market, and face whitening or wrinkle reduction is one of targets in LLLT. The facial improvement could be known simply by visual observation of face, but it cannot provide either quantitative data or recognize a subtle change. Clinical diagnostic instruments such as mexameter can provide a quantitative data, but it costs too high for home users. Therefore, we designed a low cost multi-spectral imaging device by adding additional LEDs (470nm, 640nm, white LED, 905nm) to a commercial USB microscope which has two LEDs (395nm, 940nm) as light sources. Among various LLLT skin treatments, we focused on getting melanin and wrinkle information. For melanin index measurements, multi-spectral images of nevus were acquired and melanin index values from color image (conventional method) and from multi-spectral images were compared. The results showed that multi-spectral analysis of melanin index can visualize nevus with a different depth and concentration. A cross section of wrinkle on skin resembles a wedge which can be a source of high frequency components when the skin image is Fourier transformed into a spatial frequency domain map. In that case, the entropy value of the spatial frequency map can represent the frequency distribution which is related with the amount and thickness of wrinkle. Entropy values from multi-spectral images can potentially separate the percentage of thin and shallow wrinkle from thick and deep wrinkle. From the results, we found that this low cost multi-spectral imaging system could be beneficial for home users of LLLT by providing the treatment efficacy in a quantitative way.

  2. Multi-spectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2011-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

  3. Viability Prediction of Ricinus cummunis L. Seeds Using Multispectral Imaging

    DEFF Research Database (Denmark)

    Olesen, Merete Halkjær; Nikneshan, Pejman; Shrestha, Santosh

    2015-01-01

    The purpose of this study was to highlight the use of multispectral imaging in seed quality testing of castor seeds. Visually, 120 seeds were divided into three classes: yellow, grey and black seeds. Thereafter, images at 19 different wavelengths ranging from 375–970 nm were captured of all the s...

  4. Semiconductor Laser Multi-Spectral Sensing and Imaging

    Directory of Open Access Journals (Sweden)

    Han Q. Le

    2010-01-01

    Full Text Available Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO. These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

  5. Semiconductor laser multi-spectral sensing and imaging.

    Science.gov (United States)

    Le, Han Q; Wang, Yang

    2010-01-01

    Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

  6. A Novel Perceptual Hash Algorithm for Multispectral Image Authentication

    Directory of Open Access Journals (Sweden)

    Kaimeng Ding

    2018-01-01

    Full Text Available The perceptual hash algorithm is a technique to authenticate the integrity of images. While a few scholars have worked on mono-spectral image perceptual hashing, there is limited research on multispectral image perceptual hashing. In this paper, we propose a perceptual hash algorithm for the content authentication of a multispectral remote sensing image based on the synthetic characteristics of each band: firstly, the multispectral remote sensing image is preprocessed with band clustering and grid partition; secondly, the edge feature of the band subsets is extracted by band fusion-based edge feature extraction; thirdly, the perceptual feature of the same region of the band subsets is compressed and normalized to generate the perceptual hash value. The authentication procedure is achieved via the normalized Hamming distance between the perceptual hash value of the recomputed perceptual hash value and the original hash value. The experiments indicated that our proposed algorithm is robust compared to content-preserved operations and it efficiently authenticates the integrity of multispectral remote sensing images.

  7. Design Considerations, Modeling and Analysis for the Multispectral Thermal Imager

    International Nuclear Information System (INIS)

    Borel, C.C.; Clodius, W.B.; Cooke, B.J.; Smith, B.W.; Weber, P.G.

    1999-01-01

    The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: ''End-to-end modeling and analysis (EEM).'' We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term ''end-to-end modeling and analysis.'' We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable

  8. Multispectral Image Road Extraction Based Upon Automated Map Conflation

    Science.gov (United States)

    Chen, Bin

    Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD

  9. COMPARISON OF RETINAL PATHOLOGY VISUALIZATION IN MULTISPECTRAL SCANNING LASER IMAGING.

    Science.gov (United States)

    Meshi, Amit; Lin, Tiezhu; Dans, Kunny; Chen, Kevin C; Amador, Manuel; Hasenstab, Kyle; Muftuoglu, Ilkay Kilic; Nudleman, Eric; Chao, Daniel; Bartsch, Dirk-Uwe; Freeman, William R

    2018-03-16

    To compare retinal pathology visualization in multispectral scanning laser ophthalmoscope imaging between the Spectralis and Optos devices. This retrospective cross-sectional study included 42 eyes from 30 patients with age-related macular degeneration (19 eyes), diabetic retinopathy (10 eyes), and epiretinal membrane (13 eyes). All patients underwent retinal imaging with a color fundus camera (broad-spectrum white light), the Spectralis HRA-2 system (3-color monochromatic lasers), and the Optos P200 system (2-color monochromatic lasers). The Optos image was cropped to a similar size as the Spectralis image. Seven masked graders marked retinal pathologies in each image within a 5 × 5 grid that included the macula. The average area with detected retinal pathology in all eyes was larger in the Spectralis images compared with Optos images (32.4% larger, P < 0.0001), mainly because of better visualization of epiretinal membrane and retinal hemorrhage. The average detection rate of age-related macular degeneration and diabetic retinopathy pathologies was similar across the three modalities, whereas epiretinal membrane detection rate was significantly higher in the Spectralis images. Spectralis tricolor multispectral scanning laser ophthalmoscope imaging had higher rate of pathology detection primarily because of better epiretinal membrane and retinal hemorrhage visualization compared with Optos bicolor multispectral scanning laser ophthalmoscope imaging.

  10. Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

    Science.gov (United States)

    Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

    1993-01-01

    This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

  11. Quality assessment of butter cookies applying multispectral imaging

    DEFF Research Database (Denmark)

    Stenby Andresen, Mette; Dissing, Bjørn Skovlund; Løje, Hanne

    2013-01-01

    calculated for a statistical prediction model correlating multispectral images with a browning score. The browning score is calculated as a function of oven temperature and baking time. It is presented as a quadratic response surface. The investigated process window was the intervals 4–16 min and 160–200°C...

  12. Multispectral Imaging of Meat Quality - Color and Texture

    DEFF Research Database (Denmark)

    Trinderup, Camilla Himmelstrup

    transformations to the CIELAB color space, the common color space within food science. The results show that meat color assessment with a multispectral imaging is a great alternative to the traditional colorimeter, i.e. the vision system meets some of the limitations that the colorimeter possesses. To mention one...

  13. Multi-spectral lifetime imaging: methods and applications

    NARCIS (Netherlands)

    Fereidouni, F.

    2013-01-01

    The aim of this PhD project is to further develop multispectral life time imaging hardware and analyses methods. The hardware system, Lambda-Tau, generates a considerable amount of data at high speed. To fully exploit the power of this new hardware, fast and reliable data analyses methods are

  14. An Approach for Unsupervised Change Detection in Multitemporal VHR Images Acquired by Different Multispectral Sensors

    Directory of Open Access Journals (Sweden)

    Yady Tatiana Solano-Correa

    2018-03-01

    Full Text Available This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR optical images acquired by different multispectral sensors. The proposed approach, which is inspired by a recent framework developed to support the design of change-detection systems for single-sensor VHR remote sensing images, addresses and integrates in the general approach a strategy to effectively deal with multisensor information, i.e., to perform change detection between VHR images acquired by different multispectral sensors on two dates. This is achieved by the definition of procedures for the homogenization of radiometric, spectral and geometric image properties. These procedures map images into a common feature space where the information acquired by different multispectral sensors becomes comparable across time. Although the approach is general, here we optimize it for the detection of changes in vegetation and urban areas by employing features based on linear transformations (Tasseled Caps and Orthogonal Equations, which are shown to be effective for representing the multisensor information in a homogeneous physical way irrespectively of the considered sensor. Experiments on multitemporal images acquired by different VHR satellite systems (i.e., QuickBird, WorldView-2 and GeoEye-1 confirm the effectiveness of the proposed approach.

  15. Multi-spectral confocal microendoscope for in-vivo imaging

    Science.gov (United States)

    Rouse, Andrew Robert

    The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

  16. Use of multispectral images and chemometrics in tomato seed studies

    DEFF Research Database (Denmark)

    Shrestha, Santosh; Deleuran, Lise Christina; Gislum, René

    During the production of tomato seeds, green tomatoes are normally discarded before seed extraction irrespective of their maturity stage. Studies indicate that seeds from green tomatoes may reach be able to reach full germination capacity. Thus the potential of multispectral imaging for non......-destructive discrimination of seeds based on their germination capacity was investigated. A total of 840 seeds extracted from green and red tomatoes were divided into two sets; a training set and a test set consisting of 648 and 192 seeds respectively. Each set consisted of 96 seeds from green tomatoes. The multispectral...... images of the seeds were captured and normalized canonical discriminant analysis was used to analyse the images. Germination tests were performed and seeds that subsequently germinated were recorded as viable. The viable seeds were classified with 99% and 98% accuracy for the training and test set...

  17. Quality assessment of butter cookies applying multispectral imaging

    Science.gov (United States)

    Andresen, Mette S; Dissing, Bjørn S; Løje, Hanne

    2013-01-01

    A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were calculated for a statistical prediction model correlating multispectral images with a browning score. The browning score is calculated as a function of oven temperature and baking time. It is presented as a quadratic response surface. The investigated process window was the intervals 4–16 min and 160–200°C in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis showed that the most significant wavelengths for browning predictions were in the interval 400–700 nm and the wavelengths significant for water prediction were primarily located in the near-infrared spectrum. The water prediction model was found to correctly estimate the average water content with an absolute error of 0.22%. From the images it was also possible to follow the browning and drying propagation from the cookie edge toward the center. PMID:24804036

  18. Multispectral mid-infrared imaging using frequency upconversion

    DEFF Research Database (Denmark)

    Sanders, Nicolai Højer; Dam, Jeppe Seidelin; Jensen, Ole Bjarlin

    2013-01-01

    It has recently been shown that it is possible to upconvert infrared images to the near infrared region with high quantum efficiency and low noise by three-wave mixing with a laser field [1]. If the mixing laser is single-frequency, the upconverted image is simply a band-pass filtered version...... parameter, allowing for fast tuning and hence potentially fast image acquisition, paving the way for upconversion based real time multispectral imaging. In the present realization the upconversion module consists of an external cavity tapered diode laser in a Littrow configuration with a computer controlled...

  19. Snapshot spectral and polarimetric imaging; target identification with multispectral video

    Science.gov (United States)

    Bartlett, Brent D.; Rodriguez, Mikel D.

    2013-05-01

    As the number of pixels continue to grow in consumer and scientific imaging devices, it has become feasible to collect the incident light field. In this paper, an imaging device developed around light field imaging is used to collect multispectral and polarimetric imagery in a snapshot fashion. The sensor is described and a video data set is shown highlighting the advantage of snapshot spectral imaging. Several novel computer vision approaches are applied to the video cubes to perform scene characterization and target identification. It is shown how the addition of spectral and polarimetric data to the video stream allows for multi-target identification and tracking not possible with traditional RGB video collection.

  20. SPEKTROP DPU: optoelectronic platform for fast multispectral imaging

    Science.gov (United States)

    Graczyk, Rafal; Sitek, Piotr; Stolarski, Marcin

    2010-09-01

    In recent years it easy to spot and increasing need of high-quality Earth imaging in airborne and space applications. This is due fact that government and local authorities urge for up to date topological data for administrative purposes. On the other hand, interest in environmental sciences, push for ecological approach, efficient agriculture and forests management are also heavily supported by Earth images in various resolutions and spectral ranges. "SPEKTROP DPU: Opto-electronic platform for fast multi-spectral imaging" paper describes architectural datails of data processing unit, part of universal and modular platform that provides high quality imaging functionality in aerospace applications.

  1. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  2. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

  3. Automated segmentation of pigmented skin lesions in multispectral imaging

    International Nuclear Information System (INIS)

    Carrara, Mauro; Tomatis, Stefano; Bono, Aldo; Bartoli, Cesare; Moglia, Daniele; Lualdi, Manuela; Colombo, Ambrogio; Santinami, Mario; Marchesini, Renato

    2005-01-01

    The aim of this study was to develop an algorithm for the automatic segmentation of multispectral images of pigmented skin lesions. The study involved 1700 patients with 1856 cutaneous pigmented lesions, which were analysed in vivo by a novel spectrophotometric system, before excision. The system is able to acquire a set of 15 different multispectral images at equally spaced wavelengths between 483 and 951 nm. An original segmentation algorithm was developed and applied to the whole set of lesions and was able to automatically contour them all. The obtained lesion boundaries were shown to two expert clinicians, who, independently, rejected 54 of them. The 97.1% contour accuracy indicates that the developed algorithm could be a helpful and effective instrument for the automatic segmentation of skin pigmented lesions. (note)

  4. Use of Multispectral Imaging in Varietal Identification of Tomato

    DEFF Research Database (Denmark)

    Shrestha, Santosh; Deleuran, Lise Christina; Olesen, Merete Halkjær

    2015-01-01

    Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... obtained provide an opportunity of using multispectral imaging technology as a primary tool in a scientific community for identification/discrimination of plant varieties in regard to genetic purity and plant variety protection/registration.......Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... cultivars to study parents and offspring relationship and varietal identification respectively. Normalized canonical discriminant analysis (nCDA) and principal component analysis (PCA) were used to analyze and compare the results for parents and offspring study. Both the results showed clear discrimination...

  5. Multispectral system for medical fluorescence imaging

    International Nuclear Information System (INIS)

    Andersson, P.S.; Montan, S.; Svanberg, S.

    1987-01-01

    The principles of a powerful multicolor imaging system for tissue fluorescence diagnostics are discussed. Four individually spectrally filtered images are formed on a matrix detector by means of a split-mirror arrangement. The four images are processed in a computer, pixel by pixel, by means of mathematical operations, leading to an optimized contrast image, which enhances a selected feature. The system is being developed primarily for medical fluorescence imaging, but has wide applications in fluorescence, reflectance, and transmission monitoring related to a wide range of industrial and environmental problems. The system operation is described for the case of linear imaging on a diode array detector. Laser-induced fluorescence is used for cancer tumor and arteriosclerotic plaque demarcation using the contrast enhancement capabilities of this imaging system. Further examples of applications include fluorescing minerals and flames

  6. Multispectral image analysis for object recognition and classification

    Science.gov (United States)

    Viau, C. R.; Payeur, P.; Cretu, A.-M.

    2016-05-01

    Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

  7. The development of a specialized processor for a space-based multispectral earth imager

    Science.gov (United States)

    Khedr, Mostafa E.

    2008-10-01

    This work was done in the Department of Computer Engineering, Lvov Polytechnic National University, Lvov, Ukraine, as a thesis entitled "Space Imager Computer System for Raw Video Data Processing" [1]. This work describes the synthesis and practical implementation of a specialized computer system for raw data control and processing onboard a satellite MultiSpectral earth imager. This computer system is intended for satellites with resolution in the range of one meter with 12-bit precession. The design is based mostly on general off-the-shelf components such as (FPGAs) plus custom designed software for interfacing with PC and test equipment. The designed system was successfully manufactured and now fully functioning in orbit.

  8. Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

    Science.gov (United States)

    Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

    2017-12-01

    Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

  9. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2012-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. The pellets were divided into two groups: one with pellets coated using synthetic astaxanthin in fish oil and the other with pellets coated...

  10. Portable multispectral imaging system for oral cancer diagnosis

    Science.gov (United States)

    Hsieh, Yao-Fang; Ou-Yang, Mang; Lee, Cheng-Chung

    2013-09-01

    This study presents the portable multispectral imaging system that can acquire the image of specific spectrum in vivo for oral cancer diagnosis. According to the research literature, the autofluorescence of cells and tissue have been widely applied to diagnose oral cancer. The spectral distribution is difference for lesions of epithelial cells and normal cells after excited fluorescence. We have been developed the hyperspectral and multispectral techniques for oral cancer diagnosis in three generations. This research is the third generation. The excited and emission spectrum for the diagnosis are acquired from the research of first generation. The portable system for detection of oral cancer is modified for existing handheld microscope. The UV LED is used to illuminate the surface of oral cavity and excite the cells to produce fluorescent. The image passes through the central channel and filters out unwanted spectrum by the selection of filter, and focused by the focus lens on the image sensor. Therefore, we can achieve the specific wavelength image via fluorescence reaction. The specificity and sensitivity of the system are 85% and 90%, respectively.

  11. Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

    Science.gov (United States)

    Moody, Daniela Irina

    2018-04-17

    An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

  12. Multispectral UV imaging for determination of the tablet coating thickness

    DEFF Research Database (Denmark)

    Novikova, Anna; Carstensen, Jens Michael; Zeitler, J. Axel

    2017-01-01

    The applicability of off-line multispectral ultraviolet (UV) imaging in combination with multivariate data analysis was investigated to determine the coating thickness and its distribution on the tablet surface during lab scale coating. The UV imaging results were compared with the weight gain...... measured for each individual tablet and the corresponding coating thickness and its distribution measured by terahertz pulsed imaging (TPI). Three different tablet formulations were investigated, two of which contained UV active tablet cores. Three coating formulations were applied: Aquacoat® ECD (a mainly...... translucent coating) and Eudragit® NE (a turbid coating containing solid particles). It was shown that UV imaging is a fast and non-destructive method to predict individual tablet weight gain as well as coating thickness. The coating thickness distribution profiles determined by UV imaging correlated...

  13. Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

    Science.gov (United States)

    Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

    2017-10-15

    Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

  14. Multispectral therapeutic endoscopy imaging and intervention

    Science.gov (United States)

    Bala, John L.; Schwaitzberg, Steven D.

    2007-02-01

    With the debut of antibiotic drug therapy, and as a result of its ease of use and general success in treating infection, drugs have become the treatment of choice for most bacterial infections. However, the advent of multiple, very aggressive drug-resistant bacteria, an increasing population which cannot tolerate drugs, and the high cost of drug therapy suggest that a new modality for treating infections is needed. The complex interplay of clonal spread, persistence, transfer of resistance elements and cell-to-cell interaction all contribute to the difficulty in developing drugs to treat new antibiotic-resistant bacterial strains. A dynamic non-drug system, using extant pulsed ultraviolet lightwave technology to kill infection, is being developed to destroy pathogens. This paper theorizes that the shock effect of pulsed xenon's high energy ultraviolet pulses at wavelengths between 250-270nm separates the bacteria's DNA bands, and, subsequently, destroys them. Preliminary laboratory tests have demonstrated the ability of the technology to destroy Staphylococcus aureus, Pseudomonas aeruginosa Escherichia coli, Helicobacter pylori, Acinetobacter baumannii, Klebsiella punemonia, Bacillus subtillis, and Aspergillus fumigates at penetration depths of greater than 3mm in fluids with 100% effectiveness in less than five seconds of exposure to pulsed xenon lightwaves. Micro Invasive Technology, Inc is developing .pulsed xenon therapeutic catheters and endoscopic instruments for internal antimicrobial eradication and topographical devices for prophylactic wound, burn and surgical entrance/exit site sterilization. Pulsed Xenon light sources have a broad optical spectrum (190-1200nm), and can generate light pulses with sufficient energy for combined imaging and therapeutic intervention by multiplexing a fiber optic pathway into the body. In addition, Pulsed Xenon has proven ability to activate photo reactive dyes; share endoscopic lightguides with lasers while, simultaneously

  15. Multispectral Image Analysis for Robust Prediction of Astaxanthin Coating

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Frosch, Stina; Nielsen, Michael Engelbrecht

    2013-01-01

    The aim of this study was to investigate the possibility of predicting the type and concentration level of astaxanthin coating of aquaculture feed pellets using multispectral image analysis. We used both natural and synthetic astaxanthin, and we used several different concentration levels...... of synthetic astaxanthin in combination with four different recipes of feed pellets. We used a VideometerLab with 20 spectral bands in the range of 385-1050 nm. We used linear discriminant analysis and sparse linear discriminant analysis for classification and variable selection. We used partial least squares...

  16. Dual-emissive quantum dots for multispectral intraoperative fluorescence imaging.

    Science.gov (United States)

    Chin, Patrick T K; Buckle, Tessa; Aguirre de Miguel, Arantxa; Meskers, Stefan C J; Janssen, René A J; van Leeuwen, Fijs W B

    2010-09-01

    Fluorescence molecular imaging is rapidly increasing its popularity in image guided surgery applications. To help develop its full surgical potential it remains a challenge to generate dual-emissive imaging agents that allow for combined visible assessment and sensitive camera based imaging. To this end, we now describe multispectral InP/ZnS quantum dots (QDs) that exhibit a bright visible green/yellow exciton emission combined with a long-lived far red defect emission. The intensity of the latter emission was enhanced by X-ray irradiation and allows for: 1) inverted QD density dependent defect emission intensity, showing improved efficacies at lower QD densities, and 2) detection without direct illumination and interference from autofluorescence. Copyright 2010 Elsevier Ltd. All rights reserved.

  17. Whole-body and multispectral photoacoustic imaging of adult zebrafish

    Science.gov (United States)

    Huang, Na; Xi, Lei

    2016-10-01

    Zebrafish is a top vertebrate model to study developmental biology and genetics, and it is becoming increasingly popular for studying human diseases due to its high genome similarity to that of humans and the optical transparency in embryonic stages. However, it becomes difficult for pure optical imaging techniques to volumetric visualize the internal organs and structures of wild-type zebrafish in juvenile and adult stages with excellent resolution and penetration depth. Even with the establishment of mutant lines which remain transparent over the life cycle, it is still a challenge for pure optical imaging modalities to image the whole body of adult zebrafish with micro-scale resolution. However, the method called photoacoustic imaging that combines all the advantages of the optical imaging and ultrasonic imaging provides a new way to image the whole body of the zebrafish. In this work, we developed a non-invasive photoacoustic imaging system with optimized near-infrared illumination and cylindrical scanning to image the zebrafish. The lateral and axial resolution yield to 80 μm and 600 μm, respectively. Multispectral strategy with wavelengths from 690 nm to 930 nm was employed to image various organs inside the zebrafish. From the reconstructed images, most major organs and structures inside the body can be precisely imaged. Quantitative and statistical analysis of absorption for organs under illumination with different wavelengths were carried out.

  18. Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

    Science.gov (United States)

    Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

    2016-10-01

    The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

  19. Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators.

    Science.gov (United States)

    Restaino, Rocco; Vivone, Gemine; Dalla Mura, Mauro; Chanussot, Jocelyn

    2016-04-20

    Nonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper we discuss the application of this methodology to a popular remote sensing application called pansharpening, which consists in the fusion of a low resolution multispectral image and a high resolution panchromatic image. We design a complete pansharpening scheme based on the use of morphological half gradients operators and demonstrate the suitability of this algorithm through the comparison with state of the art approaches. Four datasets acquired by the Pleiades, Worldview-2, Ikonos and Geoeye-1 satellites are employed for the performance assessment, testifying the effectiveness of the proposed approach in producing top-class images with a setting independent of the specific sensor.

  20. A Multispectral Micro-Imager for Lunar Field Geology

    Science.gov (United States)

    Nunez, Jorge; Farmer, Jack; Sellar, Glenn; Allen, Carlton

    2009-01-01

    Field geologists routinely assign rocks to one of three basic petrogenetic categories (igneous, sedimentary or metamorphic) based on microtextural and mineralogical information acquired with a simple magnifying lens. Indeed, such observations often comprise the core of interpretations of geological processes and history. The Multispectral Microscopic Imager (MMI) uses multi-wavelength, light-emitting diodes (LEDs) and a substrate-removed InGaAs focal-plane array to create multispectral, microscale reflectance images of geological samples (FOV 32 X 40 mm). Each pixel (62.5 microns) of an image is comprised of 21 spectral bands that extend from 470 to 1750 nm, enabling the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases. MMI images provide crucial context information for in situ robotic analyses using other onboard analytical instruments (e.g. XRD), or for the selection of return samples for analysis in terrestrial labs. To further assess the value of the MMI as a tool for lunar exploration, we used a field-portable, tripod-mounted version of the MMI to image a variety of Apollo samples housed at the Lunar Experiment Laboratory, NASA s Johnson Space Center. MMI images faithfully resolved the microtextural features of samples, while the application of ENVI-based spectral end member mapping methods revealed the distribution of Fe-bearing mineral phases (olivine, pyroxene and magnetite), along with plagioclase feldspars within samples. Samples included a broad range of lithologies and grain sizes. Our MMI-based petrogenetic interpretations compared favorably with thin section-based descriptions published in the Lunar Sample Compendium, revealing the value of MMI images for astronaut and rover-mediated lunar exploration.

  1. Preliminary PCA/TT Results on MRO CRISM Multispectral Images

    Science.gov (United States)

    Klassen, David R.; Smith, M. D.

    2010-10-01

    Mars Reconnaissance Orbiter arrived at Mars in March 2006 and by September had achieved its science-phase orbit with the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) beginning its visible to near-infrared (VIS/NIR) spectral imaging shortly thereafter. One goal of CRISM is to fill in the spatial gaps between the various targeted observations, eventually mapping the entire surface. Due to the large volume of data this would create, the instrument works in a reduced spectral sampling mode creating "multispectral” images. From these data we can create image cubes using 64 wavelengths from 0.410 to 3.923 µm. We present here our analysis of these multispectral mode data products using Principal Components Analysis (PCA) and Target Transformation (TT) [1]. Previous work with ground-based images [2-5] has shown that over an entire visible hemisphere, there are only three to four meaningful components using 32-105 wavelengths over 1.5-4.1 µm the first two are consistent over all temporal scales. The TT retrieved spectral endmembers show nearly the same level of consistency [5]. The preliminary work on the CRISM images cubes implies similar results; three to four significant principal components that are fairly consistent over time. These components are then used in TT to find spectral endmembers which can be used to characterize the surface reflectance for future use in radiative transfer cloud optical depth retrievals. We present here the PCA/TT results comparing the principal components and recovered endmembers from six reconstructed CRISM multi-spectral image cubes. References: [1] Bandfield, J. L., et al. (2000) JGR, 105, 9573. [2] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [3] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [4] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [5] Klassen, D. R. (2009) Icarus, 204, 32.

  2. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  3. Statistical Quality Assessment of Pre-fried Carrots Using Multispectral Imaging

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Clemmensen, Line Katrine Harder; Løje, Hanne

    2013-01-01

    Multispectral imaging is increasingly being used for quality assessment of food items due to its non-invasive benefits. In this paper, we investigate the use of multispectral images of pre-fried carrots, to detect changes over a period of 14 days. The idea is to distinguish changes in quality from...

  4. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    Science.gov (United States)

    Blonski, Slawomir; Glasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2003-01-01

    Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

  5. Hyperspectral and multispectral bioluminescence optical tomography for small animal imaging

    International Nuclear Information System (INIS)

    Chaudhari, Abhijit J; Darvas, Felix; Bading, James R; Moats, Rex A; Conti, Peter S; Smith, Desmond J; Cherry, Simon R; Leahy, Richard M

    2005-01-01

    For bioluminescence imaging studies in small animals, it is important to be able to accurately localize the three-dimensional (3D) distribution of the underlying bioluminescent source. The spectrum of light produced by the source that escapes the subject varies with the depth of the emission source because of the wavelength-dependence of the optical properties of tissue. Consequently, multispectral or hyperspectral data acquisition should help in the 3D localization of deep sources. In this paper, we describe a framework for fully 3D bioluminescence tomographic image acquisition and reconstruction that exploits spectral information. We describe regularized tomographic reconstruction techniques that use semi-infinite slab or FEM-based diffusion approximations of photon transport through turbid media. Singular value decomposition analysis was used for data dimensionality reduction and to illustrate the advantage of using hyperspectral rather than achromatic data. Simulation studies in an atlas-mouse geometry indicated that sub-millimeter resolution may be attainable given accurate knowledge of the optical properties of the animal. A fixed arrangement of mirrors and a single CCD camera were used for simultaneous acquisition of multispectral imaging data over most of the surface of the animal. Phantom studies conducted using this system demonstrated our ability to accurately localize deep point-like sources and show that a resolution of 1.5 to 2.2 mm for depths up to 6 mm can be achieved. We also include an in vivo study of a mouse with a brain tumour expressing firefly luciferase. Co-registration of the reconstructed 3D bioluminescent image with magnetic resonance images indicated good anatomical localization of the tumour

  6. Pulsed Raman fiber laser and multispectral imaging in three dimensions

    DEFF Research Database (Denmark)

    Andersen, Joachim F.; Busck, Jens; Heiselberg, Henning

    2006-01-01

    Raman scattering in single-mode optical fibers is exploited to generate multispectral light from a green nanolaser with high pulse repetition rate. Each pulse triggers a picosecond camera and measures the distance by time-of-flight in each of the 0.5 Mpixels. Three-dimensional images...... are then constructed with submillimeter accuracy for all visible colors. The generation of a series of Stokes peaks by Raman scattering in a Si fiber is discussed in detail and the laser radar technique is demonstrated. The data recording takes only a few seconds, and the high accuracy 3D color imaging works at ranges...... up to ∼200 m. Applications for optical tomography in highly scattering media such as water and human tissue are mentioned. © 2006 Optical Society of America....

  7. An Algorithm for Pedestrian Detection in Multispectral Image Sequences

    Science.gov (United States)

    Kniaz, V. V.; Fedorenko, V. V.

    2017-05-01

    The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.

  8. Multispectral Image classification using the theories of neural networks

    International Nuclear Information System (INIS)

    Ardisasmita, M.S.; Subki, M.I.R.

    1997-01-01

    Image classification is the one of the important part of digital image analysis. the objective of image classification is to identify and regroup the features occurring in an image into one or several classes in terms of the object. basic to the understanding of multispectral classification is the concept of the spectral response of an object as a function of the electromagnetic radiation and the wavelength of the spectrum. new approaches to classification has been developed to improve the result of analysis, these state-of-the-art classifiers are based upon the theories of neural networks. Neural network classifiers are algorithmes which mimic the computational abilities of the human brain. Artificial neurons are simple emulation's of biological neurons; they take in information from sensors or other artificial neurons, perform very simple operations on this data, and pass the result to other recognize the spectral signature of each image pixel. Neural network image classification has been divided into supervised and unsupervised training procedures. In the supervised approach, examples of each cover type can be located and the computer can compute spectral signatures to categorize all pixels in a digital image into several land cover classes. In supervised classification, spectral signatures are generated by mathematically grouping and it does not require analyst-specified training data. Thus, in the supervised approach we define useful information categories and then examine their spectral reparability; in the unsupervised approach the computer determines spectrally sapable classes and then we define thei information value

  9. MultiSpec—a tool for multispectral hyperspectral image data analysis

    Science.gov (United States)

    Biehl, Larry; Landgrebe, David

    2002-12-01

    MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

  10. Determining quality and maturity of pomegranates using multispectral imaging

    Directory of Open Access Journals (Sweden)

    Rasool Khodabakhshian

    2017-10-01

    Full Text Available In this paper, we investigated the use of multispectral imaging technique to quantify pomegranate fruit quality. Three quality factors including total soluble solids (TSS, pH and firmness were studied at four different maturity stages of 88, 109, 124 and 143 days after full bloom (DAFB and were correlated with the spectral information extracted from images taken at four wavelength spectra. TSS, pH and firmness of the same samples were recorded using nondestructive methods and then modeled with their corresponding spectral data using partial least squire regression (PLSR. The correlation coefficient (r, RMSEC and RPD for the calibration models was found to be: r = 0.97, RMSEC = 0.21 °Brix and RPD = 6.7 °Brix for TSS; r = 0.93, RMSEC = 0.035 and RPD = 5.01 for pH; r = 0.95, RMSEC = 0.65 N and RPD = 5.65 N for firmness. Also these parameters for the validation models were as follows: r = 0.97, RMSEP = 0.22 °Brix and RPD = 5.77 °Brix for TSS; r = 0.94, RMSEP = 0.038 and RPD = 4.98 for pH; r = 0.94, RMSEP = 0.68 N and RPD = 5.33 N for firmness. The results demonstrated the capability of multispectral imaging and chemometrics as useful techniques to nondestructively monitoring pomegranate main quality attributes.

  11. Spot-5 multispectral image for 60-75 days of rice mapping

    International Nuclear Information System (INIS)

    Ramli, Mohd Amiruddin; Shariff, Abdul Rashid Mohamed; Bejo, Siti Khairunniza

    2014-01-01

    The objective of this study is to investigate the potential application of Spot-5 multispectral satellite data in monitoring rice cultivation areas in IADA (Integrated Agriculture Development Area) located at Kerian District, Perak Malaysia. Information of the rice cultivation areas is a global economic and environmental significance. Multi-spectral images acquired at high spatial resolution are an important tool, especially in agricultural applications. This paper addresses the relationship between normalize difference vegetation index (NDVI) and ancillary data acquired from Farmers Organization Authority (PPK) for 217 farmer's field in IADA Kerian. The results indicated that NDVI range 0.62 – 0.75 has a strong positive relationship with the ground survey area estimation with (r = 0.85; p <0.01) (r 2 = 0.722). The r 2 value of 0.722 indicated a statistically significant linear relationship between the rice area estimate using NDVI range 0.62 – 0.75 and on the ground surveyed data for 217 farmers' fields. The equation of unstandardized distribution can be described as Ŷ=0.0197+0.852x. The equation for standardized regression formula for this distribution is Ŷ= 0.850x. Thus, the results indicate that 60-75 days of rice area can be estimated from the following equation Ŷ=0.197+0.852x, where Ŷ is the predicted rice area and x is area calculated using NDVI range 0.62-0.75 in IADA Kerian Perak Malaysia. The results appear promising and rice mapping operations using SPOT-5 multispectral image data can be foreseen

  12. Multispectral UV Imaging for Determination of the Tablet Coating Thickness.

    Science.gov (United States)

    Novikova, Anna; Carstensen, Jens M; Zeitler, J Axel; Rades, Thomas; Leopold, Claudia S

    2017-06-01

    The applicability of off-line multispectral UV imaging in combination with multivariate data analysis was investigated to determine the coating thickness and its distribution on the tablet surface during lab-scale coating. The UV imaging results were compared with the weight gain measured for each individual tablet and the corresponding coating thickness and its distribution measured by terahertz pulsed imaging (TPI). Three different tablet formulations were investigated, 2 of which contained UV-active tablet cores. Three coating formulations were applied: Aquacoat® ECD (a mainly translucent coating) and Eudragit® NE (a turbid coating containing solid particles). It was shown that UV imaging is a fast and nondestructive method to predict individual tablet weight gain as well as coating thickness. The coating thickness distribution profiles determined by UV imaging correlated to the results of the TPI measurements. UV imaging appears to hold a significant potential as a process analytical technology tool for determination of the tablet coating thickness and its distribution resulting from its high measurement speed, high molar absorptivity, and a high scattering coefficient, in addition to relatively low costs. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  13. Cloud-based processing of multi-spectral imaging data

    Science.gov (United States)

    Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

    2017-03-01

    Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

  14. Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Clark, B.

    2010-07-01

    The Taita Hills in southeastern Kenya form the northernmost part of Africa's Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor (rho{sub s}). Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable (rho{sub s}) throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular (rho{sub s}) field measurements were taken and where horizontal visibility meteorological data concurrent with image

  15. Spatial clustering of pixels of a multispectral image

    Science.gov (United States)

    Conger, James Lynn

    2014-08-19

    A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

  16. High Throughput Multispectral Image Processing with Applications in Food Science.

    Directory of Open Access Journals (Sweden)

    Panagiotis Tsakanikas

    Full Text Available Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

  17. High Throughput Multispectral Image Processing with Applications in Food Science.

    Science.gov (United States)

    Tsakanikas, Panagiotis; Pavlidis, Dimitris; Nychas, George-John

    2015-01-01

    Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

  18. Assigning Main Orientation to an EOH Descriptor on Multispectral Images

    Directory of Open Access Journals (Sweden)

    Yong Li

    2015-07-01

    Full Text Available This paper proposes an approach to compute an EOH (edge-oriented histogram descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor. In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

  19. Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

    Science.gov (United States)

    Li, Yong; Shi, Xiang; Wei, Lijun; Zou, Junwei; Chen, Fang

    2015-07-01

    This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor). In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

  20. Methods of Evaluating Thermodynamic Properties of Landscape Cover Using Multispectral Reflected Radiation Measurements by the Landsat Satellite

    Directory of Open Access Journals (Sweden)

    Yuriy Puzachenko

    2013-09-01

    Full Text Available The paper discusses methods of evaluating thermodynamic properties of landscape cover based on multi-spectral measurements by the Landsat satellites. Authors demonstrate how these methods could be used for studying functionality of landscapes and for spatial interpolation of Flux NET system measurements.

  1. Edge-based correlation image registration for multispectral imaging

    Science.gov (United States)

    Nandy, Prabal [Albuquerque, NM

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  2. Design and development of an airborne multispectral imaging system

    Science.gov (United States)

    Kulkarni, Rahul R.; Bachnak, Rafic; Lyle, Stacey; Steidley, Carl W.

    2002-08-01

    Advances in imaging technology and sensors have made airborne remote sensing systems viable for many applications that require reasonably good resolution at low cost. Digital cameras are making their mark on the market by providing high resolution at very high rates. This paper describes an aircraft-mounted imaging system (AMIS) that is being designed and developed at Texas A&M University-Corpus Christi (A&M-CC) with the support of a grant from NASA. The approach is to first develop and test a one-camera system that will be upgraded into a five-camera system that offers multi-spectral capabilities. AMIS will be low cost, rugged, portable and has its own battery power source. Its immediate use will be to acquire images of the Coastal area in the Gulf of Mexico for a variety of studies covering vast spectra from near ultraviolet region to near infrared region. This paper describes AMIS and its characteristics, discusses the process for selecting the major components, and presents the progress.

  3. Active multispectral imaging system for photodiagnosis and personalized phototherapies

    Energy Technology Data Exchange (ETDEWEB)

    Ugarte, M. F., E-mail: marta.ugarte@uem.es, E-mail: sbriz@fis.uc3m.es; Chávarri, L.; Padrón, V. M. [Industrial Engineering Department, Universidad Europea de Madrid, C/ Tajo, s/n 28670 Villaviciosa de Odón, Madrid (Spain); Briz, S., E-mail: marta.ugarte@uem.es, E-mail: sbriz@fis.uc3m.es [Physics Department, Universidad Carlos III de Madrid, Avda. de la Universidad, 30,28911 Leganés, Madrid (Spain); García-Cuesta, E. [Computer Science and Telecommunications Department, Universidad Europea de Madrid, C/ Tajo, s/n 28670 Villaviciosa de Odón, Madrid (Spain)

    2014-10-15

    The proposed system has been designed to identify dermatopathologies or to apply personalized phototherapy treatments. The system emits electromagnetic waves in different spectral bands in the range of visible and near infrared to irradiate the target (skin or any other object) to be spectrally characterized. Then, an imaging sensor measures the target response to the stimulus at each spectral band and, after processing, the system displays in real time two images. In one of them the value of each pixel corresponds to the more reflected wavenumber whereas in the other image the pixel value represents the energy absorbed at each band. The diagnosis capability of this system lies in its multispectral design, and the phototherapy treatments are adapted to the patient and his lesion by measuring his absorption capability. This “in situ” absorption measurement allows us to determine the more appropriate duration of the treatment according to the wavelength and recommended dose. The main advantages of this system are its low cost, it does not have moving parts or complex mechanisms, it works in real time, and it is easy to handle. For these reasons its widespread use in dermatologist consultation would facilitate the work of the dermatologist and would improve the efficiency of diagnosis and treatment. In fact the prototype has already been successfully applied to pathologies such as carcinomas, melanomas, keratosis, and nevi.

  4. Active multispectral imaging system for photodiagnosis and personalized phototherapies

    International Nuclear Information System (INIS)

    Ugarte, M. F.; Chávarri, L.; Padrón, V. M.; Briz, S.; García-Cuesta, E.

    2014-01-01

    The proposed system has been designed to identify dermatopathologies or to apply personalized phototherapy treatments. The system emits electromagnetic waves in different spectral bands in the range of visible and near infrared to irradiate the target (skin or any other object) to be spectrally characterized. Then, an imaging sensor measures the target response to the stimulus at each spectral band and, after processing, the system displays in real time two images. In one of them the value of each pixel corresponds to the more reflected wavenumber whereas in the other image the pixel value represents the energy absorbed at each band. The diagnosis capability of this system lies in its multispectral design, and the phototherapy treatments are adapted to the patient and his lesion by measuring his absorption capability. This “in situ” absorption measurement allows us to determine the more appropriate duration of the treatment according to the wavelength and recommended dose. The main advantages of this system are its low cost, it does not have moving parts or complex mechanisms, it works in real time, and it is easy to handle. For these reasons its widespread use in dermatologist consultation would facilitate the work of the dermatologist and would improve the efficiency of diagnosis and treatment. In fact the prototype has already been successfully applied to pathologies such as carcinomas, melanomas, keratosis, and nevi

  5. Multispectral fluorescence imaging techniques for nondestructive food safety inspection

    Science.gov (United States)

    Kim, Moon S.; Lefcourt, Alan M.; Chen, Yud-Ren

    2004-03-01

    The use of spectral sensing has gained acceptance as a rapid means for nondestructive inspection of postharvest food produce. Current technologies generally use color or a single wavelength camera technology. The applicability and sensitivity of these techniques can be expanded through the use of multiple wavelengths. Reflectance in the Vis/NIR is the prevalent spectral technique. Fluorescence, compared to reflectance, is regarded as a more sensitive technique due to its dynamic responses to subtle changes in biological entities. Our laboratory has been exploring fluorescence as a potential means for detection of quality and wholesomeness of food products. Applications of fluorescence sensing require an understanding of the spectral characteristics emanating from constituents and potential contaminants. A number of factors affecting fluorescence emission characteristics are discussed. Because of relatively low fluorescence quantum yield from biological samples, a system with a powerful pulse light source such as a laser coupled with a gated detection device is used to harvest fluorescence, in the presence of ambient light. Several fluorescence sensor platforms developed in our laboratory, including hyperspectral imaging, and laser-induced fluorescence (LIF) and steady-state fluorescence imaging systems with multispectral capabilities are presented. We demonstrate the potential uses of recently developed fluorescence imaging platforms in food safety inspection of apples contaminated with animal feces.

  6. Geo-oculus: high resolution multi-spectral earth imaging mission from geostationary orbit

    Science.gov (United States)

    Vaillon, L.; Schull, U.; Knigge, T.; Bevillon, C.

    2017-11-01

    Geo-Oculus is a GEO-based Earth observation mission studied by Astrium for ESA in 2008-2009 to complement the Sentinel missions, the space component of the GMES (Global Monitoring for Environment & Security). Indeed Earth imaging from geostationary orbit offers new functionalities not covered by existing LEO observation missions, like real-time monitoring and fast revisit capability of any location within the huge area in visibility of the satellite. This high revisit capability is exploited by the Meteosat meteorogical satellites, but with a spatial resolution (500 m nadir for the third generation) far from most of GMES needs (10 to 100 m). To reach such ground resolution from GEO orbit with adequate image quality, large aperture instruments (> 1 m) and high pointing stability (challenges of such missions. To address the requirements from the GMES user community, the Geo-Oculus mission is a combination of routine observations (daily systematic coverage of European coastal waters) with "on-demand" observation for event monitoring (e.g. disasters, fires and oil slicks). The instrument is a large aperture imaging telescope (1.5 m diameter) offering a nadir spatial sampling of 10.5 m (21 m worst case over Europe, below 52.5°N) in a PAN visible channel used for disaster monitoring. The 22 multi-spectral channels have resolutions over Europe ranging from 40 m in UV/VNIR (0.3 to 1 μm) to 750 m in TIR (10-12 μm).

  7. Preliminary Results Of PCA On MRO CRISM Multispectral Images

    Science.gov (United States)

    Klassen, David R.; Smith, M. D.

    2008-09-01

    Mars Reconnaissance Orbiter arrived at Mars in March 2006 and by September had achieved its science-phase orbit with the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) beginning its visible to near-infrared (VIS/NIR) spectral imaging shortly thereafter. One of the goals of CRISM is to fill in the spatial gaps between the various targeted observations, eventually mapping the entire surface. Due to the large volume of data this would create, the instrument works in a reduced spectral sampling mode creating "multispectral” images. From this data we can create image cubes using 70 wavelengths from 0.410 to 3.504 µm. We present here a preliminary analysis of these multispectral mode data products using the technique of Principal Components Analysis. Previous work with ground-based images has shown that over an entire visible hemisphere, there are only three to four meaningful components out of 32-105 wavelengths over 1.5-4.1 µm. The first two of these components are fairly consistent over all time intervals from day-to-day and season-to-season. [1-4] The preliminary work on the CRISM images cubes implies similar results_three to four significant principal components that are fairly consistent over time. We will show these components and a rough linear mixture modeling based on in-data spectral endmembers derived from the extrema of the principal components [5]. References: [1] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [2] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [3] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [4] Klassen, D. R. and Bell III, J. F. (2007) in preparation. [5] Klassen, D. R. and Bell III, J. F. (2000) BAAS, 32, 1105.

  8. Color and textural quality of packaged wild rocket measured by multispectral imaging

    DEFF Research Database (Denmark)

    Løkke, Mette Marie; Seefeldt, Helene Fast; Skov, Thomas

    2013-01-01

    Green color and texture are important attributes for the perception of freshness of wild rocket. Packaging of green leafy vegetables can postpone senescence and yellowing, but a drawback is the risk of anaerobic respiration leading to loss of tissue integrity and development of an olive-brown color....... The hypothesis underlying this paper is that color and textural quality of packaged wild rocket leaves can be predicted by multispectral imaging for faster evaluation of visual quality of leafy green vegetables in scientific experiments. Multispectral imaging was correlated to sensory evaluation of packaged wild...... rocket quality. CIELAB values derived from the multispectral images and from a spectrophotometer changed during storage, but the data were insufficient to describe variation in sensory perceived color and texture. CIELAB values from the multispectral images allowed for a more detailed determination...

  9. Diagnosing hypoxia in murine models of rheumatoid arthritis from reflectance multispectral images

    Science.gov (United States)

    Glinton, Sophie; Naylor, Amy J.; Claridge, Ela

    2017-07-01

    Spectra computed from multispectral images of murine models of Rheumatoid Arthritis show a characteristic decrease in reflectance within the 600-800nm region which is indicative of the reduction in blood oxygenation and is consistent with hypoxia.

  10. Development of a Mobile Multispectral Imaging Platform for Precise Field Phenotyping

    Czech Academy of Sciences Publication Activity Database

    Svensgaard, J.; Roitsch, Thomas; Christensen, C.

    2014-01-01

    Roč. 4, č. 3 (2014), s. 322-336 ISSN 2073-4395 Institutional support: RVO:67179843 Keywords : field phenotyping * multispectral imaging * supervised classification * canonical discriminant analysis * vegetation coverage * NDVI Subject RIV: EH - Ecology, Behaviour

  11. Feasibility study and quality assessment of unmanned aircraft system-derived multispectral images

    Science.gov (United States)

    Chang, Kuo-Jen

    2017-04-01

    The purpose of study is to explore the precision and the applicability of UAS-derived multispectral images. In this study, the Micro-MCA6 multispectral camera was mounted on quadcopter. The Micro-MCA6 shoot images synchronized of each single band. By means of geotagged images and control points, the orthomosaic images of each single band generated firstly by 14cm resolution. The multispectral image was merged complete with 6 bands. In order to improve the spatial resolution, the 6 band image fused with 9cm resolution image taken from RGB camera. Quality evaluation of the image is verified of the each single band by using control points and check points. The standard deviations of errors are within 1 to 2 pixel resolution of each band. The quality of the multispectral image is compared with 3 cm resolution orthomosaic RGB image gathered from UAV in the same mission, as well. The standard deviations of errors are within 2 to 3 pixel resolution. The result shows that the errors resulting from the blurry and the band dislocation of the objects edge identification. To the end, the normalized difference vegetation index (NDVI) extracted from the image to explore the condition of vegetation and the nature of the environment. This study demonstrates the feasibility and the capability of the high resolution multispectral images.

  12. Detecting early stage pressure ulcer on dark skin using multispectral imager

    Science.gov (United States)

    Yi, Dingrong; Kong, Linghua; Sprigle, Stephen; Wang, Fengtao; Wang, Chao; Liu, Fuhan; Adibi, Ali; Tummala, Rao

    2010-02-01

    We are developing a handheld multispectral imaging device to non-invasively inspect stage I pressure ulcers in dark pigmented skins without the need of touching the patient's skin. This paper reports some preliminary test results of using a proof-of-concept prototype. It also talks about the innovation's impact to traditional multispectral imaging technologies and the fields that will potentially benefit from it.

  13. Self-training-based spectral image reconstruction for art paintings with multispectral imaging.

    Science.gov (United States)

    Xu, Peng; Xu, Haisong; Diao, Changyu; Ye, Zhengnan

    2017-10-20

    A self-training-based spectral reflectance recovery method was developed to accurately reconstruct the spectral images of art paintings with multispectral imaging. By partitioning the multispectral images with the k-means clustering algorithm, the training samples are directly extracted from the art painting itself to restrain the deterioration of spectral estimation caused by the material inconsistency between the training samples and the art painting. Coordinate paper is used to locate the extracted training samples. The spectral reflectances of the extracted training samples are acquired indirectly with a spectroradiometer, and the circle Hough transform is adopted to detect the circle measuring area of the spectroradiometer. Through simulation and a practical experiment, the implementation of the proposed method is explained in detail, and it is verified to have better reflectance recovery performance than that using the commercial target and is comparable to the approach using a painted color target.

  14. Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

    Directory of Open Access Journals (Sweden)

    Harvey Neal R

    2007-07-01

    Full Text Available Abstract Background We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis. Results For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum gave a performance increase of 0.57%, compared to performance of the single best RGB band (red. Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains. Conclusion Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery.

  15. Terahertz detectors for long wavelength multi-spectral imaging.

    Energy Technology Data Exchange (ETDEWEB)

    Lyo, Sungkwun Kenneth; Wanke, Michael Clement; Reno, John Louis; Shaner, Eric Arthur; Grine, Albert D.

    2007-10-01

    The purpose of this work was to develop a wavelength tunable detector for Terahertz spectroscopy and imaging. Our approach was to utilize plasmons in the channel of a specially designed field-effect transistor called the grating-gate detector. Grating-gate detectors exhibit narrow-linewidth, broad spectral tunability through application of a gate bias, and no angular dependence in their photoresponse. As such, if suitable sensitivity can be attained, they are viable candidates for Terahertz multi-spectral focal plane arrays. When this work began, grating-gate gate detectors, while having many promising characteristics, had a noise-equivalent power (NEP) of only 10{sup -5} W/{radical}Hz. Over the duration of this project, we have obtained a true NEP of 10{sup -8} W/{radical}Hz and a scaled NEP of 10{sup -9}W/{radical}Hz. The ultimate goal for these detectors is to reach a NEP in the 10{sup -9{yields}-10}W/{radical}Hz range; we have not yet seen a roadblock to continued improvement.

  16. Multiscale, multispectral and multitemporal satellite data to identify archaeological remains in the archaeological area of Tiwanaku (Bolivia)

    Science.gov (United States)

    Masini, Nicola; Lasaponara, Rosa

    2015-04-01

    The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral and multitemporal satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some of these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from multitemporal ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophyical investigations. Reference [1] Lasaponara R., Masini N. 2014. Beyond modern landscape features: New insights in thearchaeological area of Tiwanaku in Bolivia from satellite data. International Journal of Applied Earth Observation and Geoinformation, 26, 464-471, http://dx.doi.org/10.1016/j.jag.2013.09.00. [2] Tapete D., Cigna F., Masini N., Lasaponara R. 2013. Prospection and monitoring of the archaeological heritage of Nasca, Peru, with ENVISAT ASAR, Archaeological Prospection, 20, 133-147, doi: 10.1002/arp.1449. [3] Lasaponara R, N Masini, 2012 Satellite Remote Sensing, A New Tool for Archaeology (Series

  17. Shadow imaging of geosynchronous satellites

    Science.gov (United States)

    Douglas, Dennis Michael

    Geosynchronous (GEO) satellites are essential for modern communication networks. If communication to a GEO satellite is lost and a malfunction occurs upon orbit insertion such as a solar panel not deploying there is no direct way to observe it from Earth. Due to the GEO orbit distance of ~36,000 km from Earth's surface, the Rayleigh criteria dictates that a 14 m telescope is required to conventionally image a satellite with spatial resolution down to 1 m using visible light. Furthermore, a telescope larger than 30 m is required under ideal conditions to obtain spatial resolution down to 0.4 m. This dissertation evaluates a method for obtaining high spatial resolution images of GEO satellites from an Earth based system by measuring the irradiance distribution on the ground resulting from the occultation of the satellite passing in front of a star. The representative size of a GEO satellite combined with the orbital distance results in the ground shadow being consistent with a Fresnel diffraction pattern when observed at visible wavelengths. A measurement of the ground shadow irradiance is used as an amplitude constraint in a Gerchberg-Saxton phase retrieval algorithm that produces a reconstruction of the satellite's 2D transmission function which is analogous to a reverse contrast image of the satellite. The advantage of shadow imaging is that a terrestrial based redundant set of linearly distributed inexpensive small telescopes, each coupled to high speed detectors, is a more effective resolved imaging system for GEO satellites than a very large telescope under ideal conditions. Modeling and simulation efforts indicate sub-meter spatial resolution can be readily achieved using collection apertures of less than 1 meter in diameter. A mathematical basis is established for the treatment of the physical phenomena involved in the shadow imaging process. This includes the source star brightness and angular extent, and the diffraction of starlight from the satellite

  18. A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

    Science.gov (United States)

    Aiello, Martina; Gianinetto, Marco

    2017-10-01

    Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

  19. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  20. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  1. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  2. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  3. Multispectral imaging of organ viability during uterine transplantation surgery

    Science.gov (United States)

    Clancy, Neil T.; Saso, Srdjan; Stoyanov, Danail; Sauvage, Vincent; Corless, David J.; Boyd, Michael; Noakes, David E.; Thum, Meen-Yau; Ghaem-Maghami, Sadaf; Smith, J. R.; Elson, Daniel S.

    2014-02-01

    Uterine transplantation surgery has been proposed as a treatment for permanent absolute uterine factor infertility (AUFI) in the case of loss of the uterus. Due to the complexity of the vasculature correct reanastomosis of the blood supply during transplantation surgery is a crucial step to ensure reperfusion and viability of the organ. While techniques such as fluorescent dye imaging have been proposed to visualise perfusion there is no gold standard for intraoperative visualisation of tissue oxygenation. In this paper results from a liquid crystal tuneable filter (LCTF)-based multispectral imaging (MSI) laparoscope are described. The system was used to monitor uterine oxygen saturation (SaO2) before and after transplantation. Results from surgeries on two animal models (rabbits and sheep) are presented. A feature-based registration algorithm was used to correct for misalignment induced by breathing or peristalsis in the tissues of interest prior to analysis. An absorption spectrum was calculated at each spatial pixel location using reflectance data from a reference standard, and the relative contributions from oxy- and deoxyhaemoglobin were calculated using a least squares regression algorithm with non-negativity constraints. Results acquired during animal surgeries show that cornual oxygenation changes are consistent with those observed in point measurements taken using a pulse oximeter, showing reduced SaO2 following reanastomosis. Values obtained using the MSI laparoscope were lower than those taken with the pulse oximeter, which may be due to the latter's use of the pulsatile arterial blood signal. Future work incorporating immunological test results will help to correlate SaO2 levels with surgical outcomes.

  4. Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

    Science.gov (United States)

    Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

    2014-02-01

    A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

  5. Quantitative imaging of tumor vasculature using multispectral optoacoustic tomography (MSOT)

    Science.gov (United States)

    Tomaszewski, Michal R.; Quiros-Gonzalez, Isabel; Joseph, James; Bohndiek, Sarah E.

    2017-03-01

    The ability to evaluate tumor oxygenation in the clinic could indicate prognosis and enable treatment monitoring, since oxygen deficient cancer cells are often more resistant to chemotherapy and radiotherapy. MultiSpectral Optoacoustic Tomography (MSOT) is a hybrid technique combining the high contrast of optical imaging with spatial resolution and penetration depth similar to ultrasound. We hypothesized that MSOT could reveal both tumor vascular density and function based on modulation of blood oxygenation. We performed MSOT on nude mice (n=8) bearing subcutaneous xenograft PC3 tumors using an inVision 256 (iThera Medical). The mice were maintained under inhalation anesthesia during imaging and respired oxygen content was modified from 21% to 100% and back. After imaging, Hoechst 33348 was injected to indicate vascular perfusion and permeability. Tumors were then extracted for histopathological analysis and fluorescence microscopy. The acquired data was analyzed to extract a bulk measurement of blood oxygenation (SO2MSOT) from the whole tumor using different approaches. The tumors were also automatically segmented into 5 regions to investigate the effect of depth on SO2MSOT. Baseline SO2MSOT values at 21% and 100% oxygen breathing showed no relationship with ex vivo measures of vascular density or function, while the change in SO2MSOT showed a strong negative correlation to Hoechst intensity (r=- 0.92, p=0.0016). Tumor voxels responding to oxygen challenge were spatially heterogeneous. We observed a significant drop in SO2 MSOT value with tumor depth following a switch of respiratory gas from air to oxygen (0.323+/-0.017 vs. 0.11+/-0.05, p=0.009 between 0 and 1.5mm depth), but no such effect for air breathing (0.265+/-0.013 vs. 0.19+/-0.04, p=0.14 between 0 and 1.5mm depth). Our results indicate that in subcutaneous prostate tumors, baseline SO2MSOT levels do not correlate to tumor vascular density or function while the magnitude of the response to oxygen

  6. Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

    Science.gov (United States)

    Awumah, Anna; Mahanti, Prasun; Robinson, Mark

    2016-10-01

    Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

  7. Multispectral UV imaging for surface analysis of MUPS tablets with special focus on the pellet distribution

    DEFF Research Database (Denmark)

    Novikova, Anna; Carstensen, Jens Michael; Rades, Thomas

    2016-01-01

    In the present study the applicability of multispectral UV imaging in combination with multivariate image analysis for surface evaluation of MUPS tablets was investigated with respect to the differentiation of the API pellets from the excipients matrix, estimation of the drug content as well as p...... image analysis is a promising approach for the automatic quality control of MUPS tablets during the manufacturing process....

  8. Multispectral code excited linear prediction coding and its application in magnetic resonance images.

    Science.gov (United States)

    Hu, J H; Wang, Y; Cahill, P T

    1997-01-01

    This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.

  9. Detection of Melanoma Metastases in Resected Human Lymph Nodes by Noninvasive Multispectral Photoacoustic Imaging

    Directory of Open Access Journals (Sweden)

    Gerrit Cornelis Langhout

    2014-01-01

    Full Text Available Objective. Sentinel node biopsy in patients with cutaneous melanoma improves staging, provides prognostic information, and leads to an increased survival in node-positive patients. However, frozen section analysis of the sentinel node is not reliable and definitive histopathology evaluation requires days, preventing intraoperative decision-making and immediate therapy. Photoacoustic imaging can evaluate intact lymph nodes, but specificity can be hampered by other absorbers such as hemoglobin. Near infrared multispectral photoacoustic imaging is a new approach that has the potential to selectively detect melanin. The purpose of the present study is to examine the potential of multispectral photoacoustic imaging to identify melanoma metastasis in human lymph nodes. Methods. Three metastatic and nine benign lymph nodes from eight melanoma patients were scanned ex vivo using a Vevo LAZR© multispectral photoacoustic imager and were spectrally analyzed per pixel. The results were compared to histopathology as gold standard. Results. The nodal volume could be scanned within 20 minutes. An unmixing procedure was proposed to identify melanoma metastases with multispectral photoacoustic imaging. Ultrasound overlay enabled anatomical correlation. The penetration depth of the photoacoustic signal was up to 2 cm. Conclusion. Multispectral three-dimensional photoacoustic imaging allowed for selective identification of melanoma metastases in human lymph nodes.

  10. Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

    Science.gov (United States)

    Moody, Daniela; Wohlberg, Brendt

    2018-01-02

    An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

  11. Predictions of malaria vector distribution in Belize based on multispectral satellite data.

    Science.gov (United States)

    Roberts, D R; Paris, J F; Manguin, S; Harbach, R E; Woodruff, R; Rejmankova, E; Polanco, J; Wullschleger, B; Legters, L J

    1996-03-01

    Use of multispectral satellite data to predict arthropod-borne disease trouble spots is dependent on clear understandings of environmental factors that determine the presence of disease vectors. A blind test of remote sensing-based predictions for the spatial distribution of a malaria vector, Anopheles pseudopunctipennis, was conducted as a follow-up to two years of studies on vector-environmental relationships in Belize. Four of eight sites that were predicted to be high probability locations for presence of An. pseudopunctipennis were positive and all low probability sites (0 of 12) were negative. The absence of An. pseudopunctipennis at four high probability locations probably reflects the low densities that seem to characterize field populations of this species, i.e., the population densities were below the threshold of our sampling effort. Another important malaria vector, An. darlingi, was also present at all high probability sites and absent at all low probability sites. Anopheles darlingi, like An. pseudopunctipennis, is a riverine species. Prior to these collections at ecologically defined locations, this species was last detected in Belize in 1946.

  12. Smoothing of Fused Spectral Consistent Satellite Images

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2006-01-01

    on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. (2005) proposed a method of fusion of satellite images that is based on the properties of imaging physics...

  13. Determining the best phenological state for accurate mapping of Phragmites australis in wetlands using time series multispectral satellite data

    Science.gov (United States)

    Rupasinghe, P. A.; Markle, C. E.; Marcaccio, J. V.; Chow-Fraser, P.

    2017-12-01

    Phragmites australis (European common reed), is a relatively recent invader of wetlands and beaches in Ontario. It can establish large homogenous stands within wetlands and disperse widely throughout the landscape by wind and vehicular traffic. A first step in managing this invasive species includes accurate mapping and quantification of its distribution. This is challenging because Phragimtes is distributed in a large spatial extent, which makes the mapping more costly and time consuming. Here, we used freely available multispectral satellite images taken monthly (cloud free images as available) for the calendar year to determine the optimum phenological state of Phragmites that would allow it to be accurately identified using remote sensing data. We analyzed time series, Landsat-8 OLI and Sentinel-2 images for Big Creek Wildlife Area, ON using image classification (Support Vector Machines), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). We used field sampling data and high resolution image collected using Unmanned Aerial Vehicle (UAV; 8 cm spatial resolution) as training data and for the validation of the classified images. The accuracy for all land cover classes and for Phragmites alone were low at both the start and end of the calendar year, but reached overall accuracy >85% by mid to late summer. The highest classification accuracies for Landsat-8 OLI were associated with late July and early August imagery. We observed similar trends using the Sentinel-2 images, with higher overall accuracy for all land cover classes and for Phragmites alone from late July to late September. During this period, we found the greatest difference between Phragmites and Typha, commonly confused classes, with respect to near-infrared and shortwave infrared reflectance. Therefore, the unique spectral signature of Phragmites can be attributed to both the level of greenness and factors related to water content in the leaves during late

  14. Red to far-red multispectral fluorescence image fusion for detection of fecal contamination on apples

    Science.gov (United States)

    This research developed a multispectral algorithm derived from hyperspectral line-scan fluorescence imaging under violet/blue LED excitation for detection of fecal contamination on Golden Delicious apples. Using a hyperspectral line-scan imaging system consisting of an EMCCD camera, spectrograph, an...

  15. Pseudo colour visualization of fused multispectral laser scattering images for optical diagnosis of rheumatoid arthritis

    Science.gov (United States)

    Zabarylo, U.; Minet, O.

    2010-01-01

    Investigations on the application of optical procedures for the diagnosis of rheumatism using scattered light images are only at the beginning both in terms of new image-processing methods and subsequent clinical application. For semi-automatic diagnosis using laser light, the multispectral scattered light images are registered and overlapped to pseudo-coloured images, which depict diagnostically essential contents by visually highlighting pathological changes.

  16. Mapping bathymetry in an active surf zone with the WorldView2 multispectral satellite

    Science.gov (United States)

    Trimble, S. M.; Houser, C.; Brander, R.; Chirico, P.

    2015-12-01

    Rip currents are strong, narrow seaward flows of water that originate in the surf zones of many global beaches. They are related to hundreds of international drownings each year, but exact numbers are difficult to calculate due to logistical difficulties in obtaining accurate incident reports. Annual average rip current fatalities are estimated to be ~100, 53 and 21 in the United States (US), Costa Rica, and Australia respectively. Current warning systems (e.g. National Weather Service) do not account for fine resolution nearshore bathymetry because it is difficult to capture. The method shown here could provide frequent, high resolution maps of nearshore bathymetry at a scale required for improved rip prediction and warning. This study demonstrates a method for mapping bathymetry in the surf zone (20m deep and less), specifically within rip channels, because rips form at topographically low spots in the bathymetry as a result of feedback amongst waves, substrate, and antecedent bathymetry. The methods employ the Digital Globe WorldView2 (WV2) multispectral satellite and field measurements of depth to generate maps of the changing bathymetry at two embayed, rip-prone beaches: Playa Cocles, Puerto Viejo de Talamanca, Costa Rica, and Bondi Beach, Sydney, Australia. WV2 has a 1.1 day pass-over rate with 1.84m ground pixel resolution of 8 bands, including 'yellow' (585-625 nm) and 'coastal blue' (400-450 nm). The data is used to classify bottom type and to map depth to the return in multiple bands. The methodology is tested at each site for algorithm consistency between dates, and again for applicability between sites.

  17. An image compression method for space multispectral time delay and integration charge coupled device camera

    International Nuclear Information System (INIS)

    Li Jin; Jin Long-Xu; Zhang Ran-Feng

    2013-01-01

    Multispectral time delay and integration charge coupled device (TDICCD) image compression requires a low-complexity encoder because it is usually completed on board where the energy and memory are limited. The Consultative Committee for Space Data Systems (CCSDS) has proposed an image data compression (CCSDS-IDC) algorithm which is so far most widely implemented in hardware. However, it cannot reduce spectral redundancy in multispectral images. In this paper, we propose a low-complexity improved CCSDS-IDC (ICCSDS-IDC)-based distributed source coding (DSC) scheme for multispectral TDICCD image consisting of a few bands. Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient. The output of bit plane extractor will be encoded by a first order entropy coder. Low-density parity-check-based Slepian—Wolf (SW) coder is adopted to implement the DSC strategy. Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band

  18. Multispectral imaging reveals biblical-period inscription unnoticed for half a century.

    Directory of Open Access Journals (Sweden)

    Shira Faigenbaum-Golovin

    Full Text Available Most surviving biblical period Hebrew inscriptions are ostraca-ink-on-clay texts. They are poorly preserved and once unearthed, fade rapidly. Therefore, proper and timely documentation of ostraca is essential. Here we show a striking example of a hitherto invisible text on the back side of an ostracon revealed via multispectral imaging. This ostracon, found at the desert fortress of Arad and dated to ca. 600 BCE (the eve of Judah's destruction by Nebuchadnezzar, has been on display for half a century. Its front side has been thoroughly studied, while its back side was considered blank. Our research revealed three lines of text on the supposedly blank side and four "new" lines on the front side. Our results demonstrate the need for multispectral image acquisition for both sides of all ancient ink ostraca. Moreover, in certain cases we recommend employing multispectral techniques for screening newly unearthed ceramic potsherds prior to disposal.

  19. Mitigating the effect of optical back-scatter in multispectral underwater imaging

    International Nuclear Information System (INIS)

    Mortazavi, Halleh; Oakley, John P; Barkat, Braham

    2013-01-01

    Multispectral imaging is a very useful technique for extracting information from the underwater world. However, optical back-scatter changes the intensity value in each spectral band and this distorts the estimated spectrum. In this work, a filter is used to detect the level of optical back-scatter in each spectral band from a set of multispectral images. Extraction of underwater object spectra can be done by subtracting the estimated level of optical back-scatter and scaling the remainder in each spectral band from the captured image in the corresponding band. An experiment has been designed to show the performance of the proposed filter for correcting the set of multispectral underwater images and recovering the pixel spectra. The multispectral images are captured by a B/W CCD digital camera with a fast tunable liquid-crystal filter in 33 narrow spectral bands in clear and different levels of turbid water. Reference estimates for the optical back-scatter spectra are found by comparing a clear and a degraded set of multispectral images. The accuracy and consistency of the proposed method, the extended Oakley–Bu cost function, is examined by comparing the estimated values with the reference level of an optical back-scatter spectrum. The same comparison is made for the simple estimation approach. The results show that the simple method is not reliable and fail to estimate the level of optical back-scatter spectrum accurately. The results from processing experimental images in turbid water show that the effect of optical back-scatter can be mitigated in the image of each spectral band and, as a result, the spectra of the object can be recovered. However, for a very high level of turbid water the recovery is limited because of the effect of extinction. (paper)

  20. Deblurring sequential ocular images from multi-spectral imaging (MSI) via mutual information.

    Science.gov (United States)

    Lian, Jian; Zheng, Yuanjie; Jiao, Wanzhen; Yan, Fang; Zhao, Bojun

    2018-06-01

    Multi-spectral imaging (MSI) produces a sequence of spectral images to capture the inner structure of different species, which was recently introduced into ocular disease diagnosis. However, the quality of MSI images can be significantly degraded by motion blur caused by the inevitable saccades and exposure time required for maintaining a sufficiently high signal-to-noise ratio. This degradation may confuse an ophthalmologist, reduce the examination quality, or defeat various image analysis algorithms. We propose an early work specially on deblurring sequential MSI images, which is distinguished from many of the current image deblurring techniques by resolving the blur kernel simultaneously for all the images in an MSI sequence. It is accomplished by incorporating several a priori constraints including the sharpness of the latent clear image, the spatial and temporal smoothness of the blur kernel and the similarity between temporally-neighboring images in MSI sequence. Specifically, we model the similarity between MSI images with mutual information considering the different wavelengths used for capturing different images in MSI sequence. The optimization of the proposed approach is based on a multi-scale framework and stepwise optimization strategy. Experimental results from 22 MSI sequences validate that our approach outperforms several state-of-the-art techniques in natural image deblurring.

  1. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    International Nuclear Information System (INIS)

    Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

    2016-01-01

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  2. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    Energy Technology Data Exchange (ETDEWEB)

    Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja [Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh 226028 (India); Bao, Le Nguyen [Duytan University, Danang 550000 (Viet Nam); Lay-Ekuakille, Aimé [Department of Innovation Engineering, University of Salento, Lecce 73100 (Italy); Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn [Duytan University, Danang 550000 (Viet Nam); Haiphong University, Haiphong 180000 (Viet Nam)

    2016-07-15

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  3. A multispectral photon-counting double random phase encoding scheme for image authentication.

    Science.gov (United States)

    Yi, Faliu; Moon, Inkyu; Lee, Yeon H

    2014-05-20

    In this paper, we propose a new method for color image-based authentication that combines multispectral photon-counting imaging (MPCI) and double random phase encoding (DRPE) schemes. The sparsely distributed information from MPCI and the stationary white noise signal from DRPE make intruder attacks difficult. In this authentication method, the original multispectral RGB color image is down-sampled into a Bayer image. The three types of color samples (red, green and blue color) in the Bayer image are encrypted with DRPE and the amplitude part of the resulting image is photon counted. The corresponding phase information that has nonzero amplitude after photon counting is then kept for decryption. Experimental results show that the retrieved images from the proposed method do not visually resemble their original counterparts. Nevertheless, the original color image can be efficiently verified with statistical nonlinear correlations. Our experimental results also show that different interpolation algorithms applied to Bayer images result in different verification effects for multispectral RGB color images.

  4. A Multispectral Photon-Counting Double Random Phase Encoding Scheme for Image Authentication

    Directory of Open Access Journals (Sweden)

    Faliu Yi

    2014-05-01

    Full Text Available In this paper, we propose a new method for color image-based authentication that combines multispectral photon-counting imaging (MPCI and double random phase encoding (DRPE schemes. The sparsely distributed information from MPCI and the stationary white noise signal from DRPE make intruder attacks difficult. In this authentication method, the original multispectral RGB color image is down-sampled into a Bayer image. The three types of color samples (red, green and blue color in the Bayer image are encrypted with DRPE and the amplitude part of the resulting image is photon counted. The corresponding phase information that has nonzero amplitude after photon counting is then kept for decryption. Experimental results show that the retrieved images from the proposed method do not visually resemble their original counterparts. Nevertheless, the original color image can be efficiently verified with statistical nonlinear correlations. Our experimental results also show that different interpolation algorithms applied to Bayer images result in different verification effects for multispectral RGB color images.

  5. Off-Resonance Suppression for Multispectral MR Imaging Near Metallic Implants

    NARCIS (Netherlands)

    den Harder, J. Chiel; van Yperen, Gert H.; Blume, Ulrike A.; Bos, Clemens

    Purpose: Metal artifact reduction in MRI within clinically feasible scan-times without through-plane aliasing. Theory and Methods: Existing metal artifact reduction techniques include view angle tilting (VAT), which resolves in-plane distortions, and multispectral imaging (MSI) techniques, such as

  6. The method of multispectral image processing of phytoplankton processing for environmental control of water pollution

    Science.gov (United States)

    Petruk, Vasil; Kvaternyuk, Sergii; Yasynska, Victoria; Kozachuk, Anastasia; Kotyra, Andrzej; Romaniuk, Ryszard S.; Askarova, Nursanat

    2015-12-01

    The paper presents improvement of the method of environmental monitoring of water bodies based on bioindication by phytoplankton, which identify phytoplankton particles carried out on the basis of comparison array multispectral images using Bayesian classifier of solving function based on Mahalanobis distance. It allows to evaluate objectively complex anthropogenic and technological impacts on aquatic ecosystems.

  7. Multispectral fluorescence image algorithms for detection of frass on mature tomatoes

    Science.gov (United States)

    A multispectral algorithm derived from hyperspectral line-scan fluorescence imaging under violet LED excitation was developed for the detection of frass contamination on mature tomatoes. The algorithm utilized the fluorescence intensities at five wavebands, 515 nm, 640 nm, 664 nm, 690 nm, and 724 nm...

  8. Distant Determination of Bilirubin Distribution in Skin by Multi-Spectral Imaging

    Science.gov (United States)

    Saknite, I.; Jakovels, D.; Spigulis, J.

    2011-01-01

    For mapping the bilirubin distribution in bruised skin the multi-spectral imaging technique was employed, which made it possible to observe temporal changes of the bilirubin content in skin photo-types II and III. The obtained results confirm the clinical potential of this technique for skin bilirubin diagnostics.

  9. Application of multispectral imaging to determine quality attributes and ripeness stage in strawberry fruit.

    Directory of Open Access Journals (Sweden)

    Changhong Liu

    Full Text Available Multispectral imaging with 19 wavelengths in the range of 405-970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS, support vector machine (SVM and back propagation neural network (BPNN, were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit.

  10. Foreign object detection in multispectral X-ray images of food items using sparse discriminant analysis

    DEFF Research Database (Denmark)

    Einarsson, Gudmundur; Jensen, Janus Nørtoft; Paulsen, Rasmus Reinhold

    2017-01-01

    Non-invasive food inspection and quality assurance are becoming viable techniques in food production due to the introduction of fast and accessible multispectral X-ray scanners. However, the novel devices produce massive amount of data and there is a need for fast and accurate algorithms for proc......Non-invasive food inspection and quality assurance are becoming viable techniques in food production due to the introduction of fast and accessible multispectral X-ray scanners. However, the novel devices produce massive amount of data and there is a need for fast and accurate algorithms...... computational properties, which allows for fast classification of items in new images....

  11. Multi sensor satellite imagers for commercial remote sensing

    Science.gov (United States)

    Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

    2005-10-01

    This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

  12. Scattering and absorption measurements of cervical tissues measures using low cost multi-spectral imaging

    Science.gov (United States)

    Bernat, Amir S.; Bar-Am, Kfir; Cataldo, Leigh; Bolton, Frank J.; Kahn, Bruce S.; Levitz, David

    2018-02-01

    Cervical cancer is a leading cause of death for women in low resource settings. In order to better detect cervical dysplasia, a low cost multi-spectral colposcope was developed utilizing low costs LEDs and an area scan camera. The device is capable of both traditional colposcopic imaging and multi-spectral image capture. Following initial bench testing, the device was deployed to a gynecology clinic where it was used to image patients in a colposcopy setting. Both traditional colposcopic images and spectral data from patients were uploaded to a cloud server for remote analysis. Multi-spectral imaging ( 30 second capture) took place before any clinical procedure; the standard of care was followed thereafter. If acetic acid was used in the standard of care, a post-acetowhitening colposcopic image was also captured. In analyzing the data, normal and abnormal regions were identified in the colposcopic images by an expert clinician. Spectral data were fit to a theoretical model based on diffusion theory, yielding information on scattering and absorption parameters. Data were grouped according to clinician labeling of the tissue, as well as any additional clinical test results available (Pap, HPV, biopsy). Altogether, N=20 patients were imaged in this study, with 9 of them abnormal. In comparing normal and abnormal regions of interest from patients, substantial differences were measured in blood content, while differences in oxygen saturation parameters were more subtle. These results suggest that optical measurements made using low cost spectral imaging systems can distinguish between normal and pathological tissues.

  13. A virtual seed file: the use of multispectral image analysis in the management of genebank seed accessions

    DEFF Research Database (Denmark)

    Adsetts Edberg Hansen, Michael; R. Hay, Fiona; Carstensen, Jens Michael

    2015-01-01

    We present a method for multispectral seed phenotyping as a fast and robust tool for managing genebank accessions. A multispectral vision system was used to take images of the seeds of 20 diverse varieties of rice (approximately 30 seeds for each variety). This was followed by extraction of feature...

  14. Classification of Pansharpened Urban Satellite Images

    DEFF Research Database (Denmark)

    Palsson, Frosti; Sveinsson, Johannes R.; Benediktsson, Jon Atli

    2012-01-01

    The classification of high resolution urban remote sensing imagery is addressed with the focus on classification of imagery that has been pansharpened by a number of different pansharpening methods. The pansharpening process introduces some spectral and spatial distortions in the resulting fused...... multispectral image, the amount of which highly varies depending on which pansharpening technique is used. In the majority of the pansharpening techniques that have been proposed, there is a compromise between the spatial enhancement and the spectral consistency. Here we study the effects of the spectral...... information from the panchromatic data. Random Forests (RF) and Support Vector Machines (SVM) will be used as classifiers. Experiments are done for three different datasets that have been obtained by two different imaging sensors, IKONOS and QuickBird. These sensors deliver multispectral images that have four...

  15. Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

    Science.gov (United States)

    Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

    2018-03-01

    Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

  16. An improved feature extraction algorithm based on KAZE for multi-spectral image

    Science.gov (United States)

    Yang, Jianping; Li, Jun

    2018-02-01

    Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

  17. Determination of astaxanthin concentration in Rainbow trout (Oncorhynchus mykiss) by multispectral image analysis

    DEFF Research Database (Denmark)

    Frosch, Stina; Dissing, Bjørn Skovlund; Ersbøll, Bjarne Kjær

    Astaxanthin is the single most expensive constituent in salmonide fish feed. Therefore control and optimization of the astaxanthin concentration from feed to fish is of paramount importance for a cost effective salmonide production. Traditionally, methods for astaxanthin determination include...... extraction of astaxanthin from the minced sample into a suitable solvent such as acetone or hexane before further analysis. The existing methods have several drawbacks including being destructive and labour consuming. Current state-of-the art vision systems for quality and process control in the fish...... to a larger degree than in a trichromatic image. In this study multispectral imaging has been evaluated for characterization of the concentration of astaxanthin in rainbow trout fillets. Rainbow trout’s (Oncorhynchus mykiss), were filleted and imaged using a rapid multispectral imaging device...

  18. Multivariate alteration detection (MAD) in multispectral, bi-temporal image data: A new approach to change detction studies

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut

    This paper introduces a new orthogonal transformation, the multivariate alteration detection (MAD) transformation, based on an established multivariate statistical technique canonical correlation analysis. The theory for canonical correlation analysis is sketched and a result necessary...... for the definition of the MAD transformation is proven. As opposed to traditional univariate change detection schemes our scheme transforms two sets of multivariate observations (e.g. two multispectral satellite images covering the same geographical area acquired at different points in time) into a difference...... between two linear combinations of the original variables explaining maximal change (i.e. the difference explaining maximal variance) in all variables simultaneously. The MAD transformation is invariant to linear scaling. The MAD transformation can be used iteratively. First, it can be used to detect...

  19. [A Method to Reconstruct Surface Reflectance Spectrum from Multispectral Image Based on Canopy Radiation Transfer Model].

    Science.gov (United States)

    Zhao, Yong-guang; Ma, Ling-ling; Li, Chuan-rong; Zhu, Xiao-hua; Tang, Ling-li

    2015-07-01

    Due to the lack of enough spectral bands for multi-spectral sensor, it is difficult to reconstruct surface retlectance spectrum from finite spectral information acquired by multi-spectral instrument. Here, taking into full account of the heterogeneity of pixel from remote sensing image, a method is proposed to simulate hyperspectral data from multispectral data based on canopy radiation transfer model. This method first assumes the mixed pixels contain two types of land cover, i.e., vegetation and soil. The sensitive parameters of Soil-Leaf-Canopy (SLC) model and a soil ratio factor were retrieved from multi-spectral data based on Look-Up Table (LUT) technology. Then, by combined with a soil ratio factor, all the parameters were input into the SLC model to simulate the surface reflectance spectrum from 400 to 2 400 nm. Taking Landsat Enhanced Thematic Mapper Plus (ETM+) image as reference image, the surface reflectance spectrum was simulated. The simulated reflectance spectrum revealed different feature information of different surface types. To test the performance of this method, the simulated reflectance spectrum was convolved with the Landsat ETM + spectral response curves and Moderate Resolution Imaging Spectrometer (MODIS) spectral response curves to obtain the simulated Landsat ETM+ and MODIS image. Finally, the simulated Landsat ETM+ and MODIS images were compared with the observed Landsat ETM+ and MODIS images. The results generally showed high correction coefficients (Landsat: 0.90-0.99, MODIS: 0.74-0.85) between most simulated bands and observed bands and indicated that the simulated reflectance spectrum was well simulated and reliable.

  20. Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

    Science.gov (United States)

    Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

    2017-11-27

    We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

  1. Digital staining for histopathology multispectral images by the combined application of spectral enhancement and spectral transformation.

    Science.gov (United States)

    Bautista, Pinky A; Yagi, Yukako

    2011-01-01

    In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.

  2. Development of a Portable 3CCD Camera System for Multispectral Imaging of Biological Samples

    Science.gov (United States)

    Lee, Hoyoung; Park, Soo Hyun; Noh, Sang Ha; Lim, Jongguk; Kim, Moon S.

    2014-01-01

    Recent studies have suggested the need for imaging devices capable of multispectral imaging beyond the visible region, to allow for quality and safety evaluations of agricultural commodities. Conventional multispectral imaging devices lack flexibility in spectral waveband selectivity for such applications. In this paper, a recently developed portable 3CCD camera with significant improvements over existing imaging devices is presented. A beam-splitter prism assembly for 3CCD was designed to accommodate three interference filters that can be easily changed for application-specific multispectral waveband selection in the 400 to 1000 nm region. We also designed and integrated electronic components on printed circuit boards with firmware programming, enabling parallel processing, synchronization, and independent control of the three CCD sensors, to ensure the transfer of data without significant delay or data loss due to buffering. The system can stream 30 frames (3-waveband images in each frame) per second. The potential utility of the 3CCD camera system was demonstrated in the laboratory for detecting defect spots on apples. PMID:25350510

  3. Panoramic, Macro and Micro Multispectral Imaging: An Affordable System for Mapping Pigments on Artworks

    Directory of Open Access Journals (Sweden)

    Antonino Cosentino

    2015-07-01

    Full Text Available Multispectral imaging systems are used in art examinations to map and identify pigments, binders and areas of retouching. A monochromatic camera is combined with an appropriate wavelength selection system and acquires a variable number of spectral images of a scene. These images are then stacked into a reflectance imaging cube to reconstruct reflectance spectra from each of the images’ pixels. This paper presents an affordable multispectral imaging system composed of a monochromatic CCD camera and a set of only 12 interference filters for mapping pigments on works of art and for the tentative identification of such pigments. This work demonstrates the versatility of this set-up, a versatility enabling it to be applied to different tasks, involving examination and documentation of objects of varying size. Use of this multispectral camera for both panoramic and macro photography is discussed, together with the possibilities facilitated from the coupling of the system to a stereomicroscope and a compound microscope. This system is of particular interest for the cultural heritage sector because of its hardware simplicity and acquisition speed, as well as its lightness and small dimensions.

  4. Science applications of a multispectral microscopic imager for the astrobiological exploration of Mars.

    Science.gov (United States)

    Núñez, Jorge I; Farmer, Jack D; Sellar, R Glenn; Swayze, Gregg A; Blaney, Diana L

    2014-02-01

    Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars. Mars-Microscopic imager-Multispectral imaging-Spectroscopy-Habitability-Arm instrument.

  5. Object-oriented classification using quasi-synchronous multispectral images (optical and radar) over agricultural surface

    Science.gov (United States)

    Marais Sicre, Claire; Baup, Frederic; Fieuzal, Remy

    2015-04-01

    In the context of climate change (with consequences on temperature and precipitation patterns), persons involved in agricultural management have the imperative to combine: sufficient productivity (as a response of the increment of the necessary foods) and durability of the resources (in order to restrain waste of water, fertilizer or environmental damages). To this end, a detailed knowledge of land use will improve the management of food and water, while preserving the ecosystems. Among the wide range of available monitoring tools, numerous studies demonstrated the interest of satellite images for agricultural mapping. Recently, the launch of several radar and optical sensors offer new perspectives for the multi-wavelength crop monitoring (Terrasar-X, Radarsat-2, Sentinel-1, Landsat-8…) allowing surface survey whatever the cloud conditions. Previous studies have demonstrated the interest of using multi-temporal approaches for crop classification, requiring several images for suitable classification results. Unfortunately, these approaches are limited (due to the satellite orbit cycle) and require waiting several days, week or month before offering an accurate land use map. The objective of this study is to compare the accuracy of object-oriented classification (random forest algorithm combined with vector layer coming from segmentation) to map winter crop (barley, rapeseed, grasslands and wheat) and soil states (bare soils with different surface roughness) using quasi-synchronous images. Satellite data are composed of multi-frequency and multi-polarization (HH, VV, HV and VH) images acquired near the 14th of April, 2010, over a studied area (90km²) located close to Toulouse in France. This is a region of alluvial plains and hills, which are mostly mixed farming and governed by a temperate climate. Remote sensing images are provided by Formosat-2 (04/18), Radarsat-2 (C-band, 04/15), Terrasar-X (X-band, 04/14) and ALOS (L-band, 04/14). Ground data are collected

  6. Quantitative functional optical imaging of the human skin using multi-spectral imaging

    International Nuclear Information System (INIS)

    Kainerstorfer, J. M.

    2010-01-01

    Light tissue interactions can be described by the physical principles of absorption and scattering. Based on those parameters, different tissue types and analytes can be distinguished. Extracting blood volume and oxygenation is of particular interest in clinical routines for tumor diagnostics and treatment follow up, since they are parameters of angiogenic processes. The quantification of those analytes in tissue can be done by physical modeling of light tissue interaction. The physical model used here is the random walk theory. However, for quantification and clinical usefulness, one has to account for multiple challenges. First, one must consider the effect of topology of the sample on measured physical parameters. Second, diffusion of light inside the tissue is dependent on the structure of the sample imaged. Thus, the structural conformation has to be taken into account. Third, clinical translation of imaging modalities is often hindered due to the complicated post-processing of data, not providing results in real-time. In this thesis, two imaging modalities are being utilized, where the first one, diffuse multi-spectral imaging, is based on absorption contrast and spectral characteristics and the second one, Optical Coherence Tomography (OCT), is based on scattering changes within the tissue. Multi-spectral imaging can provide spatial distributions of blood volume and blood oxygenation and OCT yields 3D structural images with micrometer resolution. In order to address the challenges mentioned above, a curvature correction algorithm for taking the topology into account was developed. Without taking curvature of the object into account, reconstruction of optical properties is not accurate. The method developed removes this artifact and recovers the underlying data, without the necessity of measuring the object's shape. The next step was to recover blood volume and oxygenation values in real time. Principal Component Analysis (PCA) on multi spectral images is

  7. Quantitatively differentiating microstructural variations of skeletal muscle tissues by multispectral Mueller matrix imaging

    Science.gov (United States)

    Dong, Yang; He, Honghui; He, Chao; Ma, Hui

    2016-10-01

    Polarized light is sensitive to the microstructures of biological tissues and can be used to detect physiological changes. Meanwhile, spectral features of the scattered light can also provide abundant microstructural information of tissues. In this paper, we take the backscattering polarization Mueller matrix images of bovine skeletal muscle tissues during the 24-hour experimental time, and analyze their multispectral behavior using quantitative Mueller matrix parameters. In the processes of rigor mortis and proteolysis of muscle samples, multispectral frequency distribution histograms (FDHs) of the Mueller matrix elements can reveal rich qualitative structural information. In addition, we analyze the temporal variations of the sample using the multispectral Mueller matrix transformation (MMT) parameters. The experimental results indicate that the different stages of rigor mortis and proteolysis for bovine skeletal muscle samples can be judged by these MMT parameters. The results presented in this work show that combining with the multispectral technique, the FDHs and MMT parameters can characterize the microstructural variation features of skeletal muscle tissues. The techniques have the potential to be used as tools for quantitative assessment of meat qualities in food industry.

  8. A Lightweight Compact Multi-Spectral Imager Using Novel Computer-Generated Micro-Optics and Spectral-Extraction Algorithms

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this NASA Early-stage research proposal is to demonstrate an ultra-compact, lightweight broadband hyper- and multi-spectral imaging system that is...

  9. Multispectral confocal microscopy images and artificial neural nets to monitor the photosensitizer uptake and degradation in Candida albicans cells

    Science.gov (United States)

    Romano, Renan A.; Pratavieira, Sebastião.; da Silva, Ana P.; Kurachi, Cristina; Guimarães, Francisco E. G.

    2017-07-01

    This study clearly demonstrates that multispectral confocal microscopy images analyzed by artificial neural networks provides a powerful tool to real-time monitoring photosensitizer uptake, as well as photochemical transformations occurred.

  10. Digital simulation of staining in histopathology multispectral images: enhancement and linear transformation of spectral transmittance.

    Science.gov (United States)

    Bautista, Pinky A; Yagi, Yukako

    2012-05-01

    Hematoxylin and eosin (H&E) stain is currently the most popular for routine histopathology staining. Special and/or immuno-histochemical (IHC) staining is often requested to further corroborate the initial diagnosis on H&E stained tissue sections. Digital simulation of staining (or digital staining) can be a very valuable tool to produce the desired stained images from the H&E stained tissue sections instantaneously. We present an approach to digital staining of histopathology multispectral images by combining the effects of spectral enhancement and spectral transformation. Spectral enhancement is accomplished by shifting the N-band original spectrum of the multispectral pixel with the weighted difference between the pixel's original and estimated spectrum; the spectrum is estimated using M transformed to the spectral configuration associated to its reaction to a specific stain by utilizing an N × N transformation matrix, which is derived through application of least mean squares method to the enhanced and target spectral transmittance samples of the different tissue components found in the image. Results of our experiments on the digital conversion of an H&E stained multispectral image to its Masson's trichrome stained equivalent show the viability of the method.

  11. Application of principal component analysis to multispectral imaging data for evaluation of pigmented skin lesions

    Science.gov (United States)

    Jakovels, Dainis; Lihacova, Ilze; Kuzmina, Ilona; Spigulis, Janis

    2013-11-01

    Non-invasive and fast primary diagnostics of pigmented skin lesions is required due to frequent incidence of skin cancer - melanoma. Diagnostic potential of principal component analysis (PCA) for distant skin melanoma recognition is discussed. Processing of the measured clinical multi-spectral images (31 melanomas and 94 nonmalignant pigmented lesions) in the wavelength range of 450-950 nm by means of PCA resulted in 87 % sensitivity and 78 % specificity for separation between malignant melanomas and pigmented nevi.

  12. Science Applications of a Multispectral Microscopic Imager for the Astrobiological Exploration of Mars

    Science.gov (United States)

    Farmer, Jack D.; Sellar, R. Glenn; Swayze, Gregg A.; Blaney, Diana L.

    2014-01-01

    Abstract Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars. Key Words: Mars—Microscopic imager—Multispectral imaging

  13. Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

    Directory of Open Access Journals (Sweden)

    Irene Erlyn Wina Rachmawan

    2015-06-01

    Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

  14. High performance multi-spectral interrogation for surface plasmon resonance imaging sensors.

    Science.gov (United States)

    Sereda, A; Moreau, J; Canva, M; Maillart, E

    2014-04-15

    Surface plasmon resonance (SPR) sensing has proven to be a valuable tool in the field of surface interactions characterization, especially for biomedical applications where label-free techniques are of particular interest. In order to approach the theoretical resolution limit, most SPR-based systems have turned to either angular or spectral interrogation modes, which both offer very accurate real-time measurements, but at the expense of the 2-dimensional imaging capability, therefore decreasing the data throughput. In this article, we show numerically and experimentally how to combine the multi-spectral interrogation technique with 2D-imaging, while finding an optimum in terms of resolution, accuracy, acquisition speed and reduction in data dispersion with respect to the classical reflectivity interrogation mode. This multi-spectral interrogation methodology is based on a robust five parameter fitting of the spectral reflectivity curve which enables monitoring of the reflectivity spectral shift with a resolution of the order of ten picometers, and using only five wavelength measurements per point. In fine, such multi-spectral based plasmonic imaging system allows biomolecular interaction monitoring in a linear regime independently of variations of buffer optical index, which is illustrated on a DNA-DNA model case. © 2013 Elsevier B.V. All rights reserved.

  15. Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes

    OpenAIRE

    Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.

    2007-01-01

    Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. ...

  16. LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. Tom

    2018-05-01

    Full Text Available Monitoring and analyzing the (decreasing trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m–1000 m satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal. Only the cloud-free (clean pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM. We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  17. Lake Ice Detection in Low-Resolution Optical Satellite Images

    Science.gov (United States)

    Tom, M.; Kälin, U.; Sütterlin, M.; Baltsavias, E.; Schindler, K.

    2018-05-01

    Monitoring and analyzing the (decreasing) trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m-1000 m) satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM) lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen) semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal). Only the cloud-free (clean) pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM). We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  18. A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces

    Science.gov (United States)

    Comelli, Daniela; Valentini, Gianluca; Nevin, Austin; Farina, Andrea; Toniolo, Lucia; Cubeddu, Rinaldo

    2008-08-01

    A portable fluorescence multispectral imaging system was developed and has been used for the analysis of artistic surfaces. The imaging apparatus exploits two UV lamps for fluorescence excitation and a liquid crystal tunable filter coupled to a low-noise charge coupled device as the image detector. The main features of the system are critically presented, outlining the assets, drawbacks, and practical considerations of portability. A multivariate statistical treatment of spectral data is further considered. Finally, the in situ analysis with the new apparatus of recently restored Renaissance wall paintings is presented.

  19. Observing lowermost tropospheric ozone pollution with a new multispectral synergic approach of IASI infrared and GOME-2 ultraviolet satellite measurements

    Science.gov (United States)

    Cuesta, Juan; Foret, Gilles; Dufour, Gaëlle; Eremenko, Maxim; Coman, Adriana; Gaubert, Benjamin; Beekmann, Matthias; Liu, Xiong; Cai, Zhaonan; Von Clarmann, Thomas; Spurr, Robert; Flaud, Jean-Marie

    2014-05-01

    Tropospheric ozone is currently one of the air pollutants posing greatest threats to human health and ecosystems. Monitoring ozone pollution at the regional, continental and global scale is a crucial societal issue. Only spaceborne remote sensing is capable of observing tropospheric ozone at such scales. The spatio-temporal coverage of new satellite-based instruments, such as IASI or GOME-2, offer a great potential for monitoring air quality by synergism with regional chemistry-transport models, for both inter-validation and full data assimilation. However, current spaceborne observations using single-band either UV or IR measurements show limited sensitivity to ozone in the atmospheric boundary layer, which is the major concern for air quality. Very recently, we have developed an innovative multispectral approach, so-called IASI+GOME-2, which combines IASI and GOME-2 observations, respectively in the IR and UV. This unique multispectral approach has allowed the observation of ozone plumes in the lowermost troposphere (LMT, below 3 km of altitude) over Europe, for the first time from space. Our first analyses are focused on typical ozone pollution events during the summer of 2009 over Europe. During these events, LMT ozone plumes at different regions are produced photo-chemically in the boundary layer, transported upwards to the free troposphere and also downwards from the stratosphere. We have analysed them using IASI+GOME-2 observations, in comparison with single-band methods (IASI, GOME-2 and OMI). Only IASI+GOME-2 depicts ozone plumes located below 3 km of altitude (both over land and ocean). Indeed, the multispectral sensitivity in the LMT is greater by 40% and it peaks at 2 to 2.5 km of altitude over land, thus at least 0.8 to 1 km below that for all single-band methods. Over Europe during the summer of 2009, IASI+GOME-2 shows 1% mean bias and 21% precision for direct comparisons with ozonesondes and also good agreement with CHIMERE model simulations

  20. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  1. Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

    Science.gov (United States)

    Xiao, P.; Kelly, M.; Guo, Q.

    2014-12-01

    This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree

  2. Nondestructive and intuitive determination of circadian chlorophyll rhythms in soybean leaves using multispectral imaging

    Science.gov (United States)

    Pan, Wen-Juan; Wang, Xia; Deng, Yong-Ren; Li, Jia-Hang; Chen, Wei; Chiang, John Y.; Yang, Jian-Bo; Zheng, Lei

    2015-01-01

    The circadian clock, synchronized by daily cyclic environmental cues, regulates diverse aspects of plant growth and development and increases plant fitness. Even though much is known regarding the molecular mechanism of circadian clock, it remains challenging to quantify the temporal variation of major photosynthesis products as well as their metabolic output in higher plants in a real-time, nondestructive and intuitive manner. In order to reveal the spatial-temporal scenarios of photosynthesis and yield formation regulated by circadian clock, multispectral imaging technique has been employed for nondestructive determination of circadian chlorophyll rhythms in soybean leaves. By utilizing partial least square regression analysis, the determination coefficients R2, 0.9483 for chlorophyll a and 0.8906 for chlorophyll b, were reached, respectively. The predicted chlorophyll contents extracted from multispectral data showed an approximately 24-h rhythm which could be entrained by external light conditions, consistent with the chlorophyll contents measured by chemical analyses. Visualization of chlorophyll map in each pixel offers an effective way to analyse spatial-temporal distribution of chlorophyll. Our results revealed the potentiality of multispectral imaging as a feasible nondestructive universal assay for examining clock function and robustness, as well as monitoring chlorophyll a and b and other biochemical components in plants. PMID:26059057

  3. A comparison of autonomous techniques for multispectral image analysis and classification

    Science.gov (United States)

    Valdiviezo-N., Juan C.; Urcid, Gonzalo; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso

    2012-10-01

    Multispectral imaging has given place to important applications related to classification and identification of objects from a scene. Because of multispectral instruments can be used to estimate the reflectance of materials in the scene, these techniques constitute fundamental tools for materials analysis and quality control. During the last years, a variety of algorithms has been developed to work with multispectral data, whose main purpose has been to perform the correct classification of the objects in the scene. The present study introduces a brief review of some classical as well as a novel technique that have been used for such purposes. The use of principal component analysis and K-means clustering techniques as important classification algorithms is here discussed. Moreover, a recent method based on the min-W and max-M lattice auto-associative memories, that was proposed for endmember determination in hyperspectral imagery, is introduced as a classification method. Besides a discussion of their mathematical foundation, we emphasize their main characteristics and the results achieved for two exemplar images conformed by objects similar in appearance, but spectrally different. The classification results state that the first components computed from principal component analysis can be used to highlight areas with different spectral characteristics. In addition, the use of lattice auto-associative memories provides good results for materials classification even in the cases where some spectral similarities appears in their spectral responses.

  4. Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.

    Science.gov (United States)

    Alexandridis, Thomas K; Tamouridou, Afroditi Alexandra; Pantazi, Xanthoula Eirini; Lagopodi, Anastasia L; Kashefi, Javid; Ovakoglou, Georgios; Polychronos, Vassilios; Moshou, Dimitrios

    2017-09-01

    In the present study, the detection and mapping of Silybum marianum (L.) Gaertn. weed using novelty detection classifiers is reported. A multispectral camera (green-red-NIR) on board a fixed wing unmanned aerial vehicle (UAV) was employed for obtaining high-resolution images. Four novelty detection classifiers were used to identify S. marianum between other vegetation in a field. The classifiers were One Class Support Vector Machine (OC-SVM), One Class Self-Organizing Maps (OC-SOM), Autoencoders and One Class Principal Component Analysis (OC-PCA). As input features to the novelty detection classifiers, the three spectral bands and texture were used. The S. marianum identification accuracy using OC-SVM reached an overall accuracy of 96%. The results show the feasibility of effective S. marianum mapping by means of novelty detection classifiers acting on multispectral UAV imagery.

  5. Multispectral imaging as a potential tool for seed health testing of spinach (Spinacia oleracea L.)

    DEFF Research Database (Denmark)

    Olesen, M. Halkjaer; Carstensen, Jens Michael; Boelt, B.

    2011-01-01

    Seed health tests are time consuming and require substantial training for characterization of pathogenic fungi on seed. A new approach to use a multispectral vision system for identifying surface properties of different fungal infections has been tested in spinach (Spinacia oleracea L.) at Aarhus...... University. Our study demonstrates that multispectral imaging with wavelengths ranging from 395-970 nm can be used to distinguish between uninfected spinach seeds and seeds infected with Verticillium spp., Fusarium spp., Stemphylium botryosum, Cladosporium spp. and Alternaria alternata. Analytical separation...... based on mean pixel intensity, Canonical Discriminant Analysis (CDA) and classification by Jeffries-Matusita (JM) distance illustrates that a combination of Near Infrared spectra (NIR) and Visual spectra (VIS) is able to identify uninfected seeds from infected seeds ranging from 80-100%. Classification...

  6. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  7. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  8. Optoacoustic multispectral imaging of radiolucent foreign bodies in tissue.

    Science.gov (United States)

    Page, Leland; Maswadi, Saher; Glickman, Randolph D

    2013-01-01

    Optoacoustic imaging is an emerging medical technology that uniquely combines the absorption contrast of optical imaging and the penetration depth of ultrasound. While it is not currently employed as a clinical imaging modality, the results of current research strongly support the use of optoacoustic-based methods in medical imaging. One such application is the diagnosis of the presence of soft tissue foreign bodies. Because many radiolucent foreign bodies have sufficient contrast for imaging in the optical domain, laser-induced optoacoustic imaging could be advantageous for the detection of such objects. Common foreign bodies have been scanned over a range of visible and near infrared wavelengths by using an optoacoustic method to obtain the spectroscopic properties of the materials commonly associated with these foreign bodies. The derived optical absorption spectra compared quite closely to the absorption spectra generated when using a conventional spectrophotometer. By using the probe-beam deflection technique, a novel, pressure-wave detection method, we successfully generated optoacoustic spectroscopic plots of a wooden foreign body embedded in a tissue phantom, which closely resembled the spectrum of the same object obtained in isolation. A practical application of such spectra is to assemble a library of spectroscopic data for radiolucent materials, from which specific characteristic wavelengths can be selected for use in optimizing imaging instrumentation and provide a basis for the identification of the material properties of particular foreign bodies.

  9. The Effect of Multispectral Image Fusion Enhancement on Human Efficiency

    Science.gov (United States)

    2017-03-20

    and discrete wavelet transformation (DWT). A seventh function was added after we noticed a number of cases where PCA produced uninterpretable...component analysis and adjusted PCA Principal component analysis (PCA) is a general math - ematical technique that transforms a set of potentially correlated...equivalent to sampling the image with Laplacian operators of many scales, which tends to enhance salient image features. Discrete wavelet transform The

  10. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  11. Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

    Science.gov (United States)

    Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

    2018-04-01

    Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0

  12. Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

    Science.gov (United States)

    Wittke, S.; Karila, K.; Puttonen, E.; Hellsten, A.; Auvinen, M.; Karjalainen, M.

    2017-05-01

    This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

  13. EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

    Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

  14. SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    A. Sharma

    2015-03-01

    Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

  15. Rational Variety Mapping for Contrast-Enhanced Nonlinear Unsupervised Segmentation of Multispectral Images of Unstained Specimen

    Science.gov (United States)

    Kopriva, Ivica; Hadžija, Mirko; Popović Hadžija, Marijana; Korolija, Marina; Cichocki, Andrzej

    2011-01-01

    A methodology is proposed for nonlinear contrast-enhanced unsupervised segmentation of multispectral (color) microscopy images of principally unstained specimens. The methodology exploits spectral diversity and spatial sparseness to find anatomical differences between materials (cells, nuclei, and background) present in the image. It consists of rth-order rational variety mapping (RVM) followed by matrix/tensor factorization. Sparseness constraint implies duality between nonlinear unsupervised segmentation and multiclass pattern assignment problems. Classes not linearly separable in the original input space become separable with high probability in the higher-dimensional mapped space. Hence, RVM mapping has two advantages: it takes implicitly into account nonlinearities present in the image (ie, they are not required to be known) and it increases spectral diversity (ie, contrast) between materials, due to increased dimensionality of the mapped space. This is expected to improve performance of systems for automated classification and analysis of microscopic histopathological images. The methodology was validated using RVM of the second and third orders of the experimental multispectral microscopy images of unstained sciatic nerve fibers (nervus ischiadicus) and of unstained white pulp in the spleen tissue, compared with a manually defined ground truth labeled by two trained pathophysiologists. The methodology can also be useful for additional contrast enhancement of images of stained specimens. PMID:21708116

  16. Multispectral image feature fusion for detecting land mines

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Fields, D.J.; Sherwood, R.J. [Lawrence Livermore National Lab., CA (United States)] [and others

    1994-11-15

    Our system fuses information contained in registered images from multiple sensors to reduce the effect of clutter and improve the the ability to detect surface and buried land mines. The sensor suite currently consists if a camera that acquires images in sixible wavelength bands, du, dual-band infrared (5 micron and 10 micron) and ground penetrating radar. Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separate in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, holes made by animals and natural processes, etc.) and some artifacts.

  17. Multispectral diagnostic imaging of the iris in pigment dispersion syndrome.

    Science.gov (United States)

    Roberts, Daniel K; Lukic, Ana; Yang, Yongyi; Wilensky, Jacob T; Wernick, Miles N

    2012-08-01

    To determine if wavelength selection with near infrared iris imaging may enhance iris transillumination defects (ITDs) in pigment dispersion syndrome. An experimental apparatus was used to acquire iris images in 6 African-American (AA) and 6 White patients with pigment dispersion syndrome. Light-emitting diode probes of 6 different spectral bands (700 to 950 nm) were used to project light into patients' eyes. Iris patterns were photographed, ITD regions of interest were outlined, and region of interest contrasts were calculated for each spectral band. Contrasts varied as a function of wavelength (Ppigmented eyes may be slightly longer than for less pigmented eyes.

  18. Multiplexing and de-multiplexing with scattering media for large field of view and multispectral imaging

    Science.gov (United States)

    Sahoo, Sujit Kumar; Tang, Dongliang; Dang, Cuong

    2018-02-01

    Large field of view multispectral imaging through scattering medium is a fundamental quest in optics community. It has gained special attention from researchers in recent years for its wide range of potential applications. However, the main bottlenecks of the current imaging systems are the requirements on specific illumination, poor image quality and limited field of view. In this work, we demonstrated a single-shot high-resolution colour-imaging through scattering media using a monochromatic camera. This novel imaging technique is enabled by the spatial, spectral decorrelation property and the optical memory effect of the scattering media. Moreover the use of deconvolution image processing further annihilate above-mentioned drawbacks arise due iterative refocusing, scanning or phase retrieval procedures.

  19. AMARSI: Aerosol modeling and retrieval from multi-spectral imagers

    NARCIS (Netherlands)

    Leeuw, G. de; Curier, R.L.; Staroverova, A.; Kokhanovsky, A.; Hoyningen-Huene, W. van; Rozanov, V.V.; Burrows, J.P.; Hesselmans, G.; Gale, L.; Bouvet, M.

    2008-01-01

    The AMARSI project aims at the development and validation of aerosol retrieval algorithms over ocean. One algorithm will be developed for application with data from the Multi Spectral Imager (MSI) on EarthCARE. A second algorithm will be developed using the combined information from AATSR and MERIS,

  20. Discrimination of haploid and diploid maize kernels via multispectral imaging

    DEFF Research Database (Denmark)

    De La Fuente, Gerald N.; Carstensen, Jens Michael; Adsetts Edberg Hansen, Michael

    2017-01-01

    sorting of haploids would increase the efficiency of DH line development. In this study, six inbred lines were crossed with the maternal haploid inducer ‘RWS/RWK-76’ and a sample of seed was sorted manually for each line. Using the VideometerLab 3 system, spectral imaging techniques were applied...

  1. Compression of Multispectral Images with Comparatively Few Bands Using Posttransform Tucker Decomposition

    Directory of Open Access Journals (Sweden)

    Jin Li

    2014-01-01

    Full Text Available Up to now, data compression for the multispectral charge-coupled device (CCD images with comparatively few bands (MSCFBs is done independently on each multispectral channel. This compression codec is called a “monospectral compressor.” The monospectral compressor does not have a removing spectral redundancy stage. To fill this gap, we propose an efficient compression approach for MSCFBs. In our approach, the one dimensional discrete cosine transform (1D-DCT is performed on spectral dimension to exploit the spectral information, and the posttransform (PT in 2D-DWT domain is performed on each spectral band to exploit the spatial information. A deep coupling approach between the PT and Tucker decomposition (TD is proposed to remove residual spectral redundancy between bands and residual spatial redundancy of each band. Experimental results on multispectral CCD camera data set show that the proposed compression algorithm can obtain a better compression performance and significantly outperforms the traditional compression algorithm-based TD in 2D-DWT and 3D-DCT domain.

  2. Correction of motion artefacts and pseudo colour visualization of multispectral light scattering images for optical diagnosis of rheumatoid arthritis

    Science.gov (United States)

    Minet, Olaf; Scheibe, Patrick; Beuthan, Jürgen; Zabarylo, Urszula

    2010-02-01

    State-of-the-art image processing methods offer new possibilities for diagnosing diseases using scattered light. The optical diagnosis of rheumatism is taken as an example to show that the diagnostic sensitivity can be improved using overlapped pseudo-coloured images of different wavelengths, provided that multispectral images are recorded to compensate for any motion related artefacts which occur during examination.

  3. Using Non-Invasive Multi-Spectral Imaging to Quantitatively Assess Tissue Vasculature

    Energy Technology Data Exchange (ETDEWEB)

    Vogel, A; Chernomordik, V; Riley, J; Hassan, M; Amyot, F; Dasgeb, B; Demos, S G; Pursley, R; Little, R; Yarchoan, R; Tao, Y; Gandjbakhche, A H

    2007-10-04

    This research describes a non-invasive, non-contact method used to quantitatively analyze the functional characteristics of tissue. Multi-spectral images collected at several near-infrared wavelengths are input into a mathematical optical skin model that considers the contributions from different analytes in the epidermis and dermis skin layers. Through a reconstruction algorithm, we can quantify the percent of blood in a given area of tissue and the fraction of that blood that is oxygenated. Imaging normal tissue confirms previously reported values for the percent of blood in tissue and the percent of blood that is oxygenated in tissue and surrounding vasculature, for the normal state and when ischemia is induced. This methodology has been applied to assess vascular Kaposi's sarcoma lesions and the surrounding tissue before and during experimental therapies. The multi-spectral imaging technique has been combined with laser Doppler imaging to gain additional information. Results indicate that these techniques are able to provide quantitative and functional information about tissue changes during experimental drug therapy and investigate progression of disease before changes are visibly apparent, suggesting a potential for them to be used as complementary imaging techniques to clinical assessment.

  4. Externally calibrated parallel imaging for 3D multispectral imaging near metallic implants using broadband ultrashort echo time imaging.

    Science.gov (United States)

    Wiens, Curtis N; Artz, Nathan S; Jang, Hyungseok; McMillan, Alan B; Reeder, Scott B

    2017-06-01

    To develop an externally calibrated parallel imaging technique for three-dimensional multispectral imaging (3D-MSI) in the presence of metallic implants. A fast, ultrashort echo time (UTE) calibration acquisition is proposed to enable externally calibrated parallel imaging techniques near metallic implants. The proposed calibration acquisition uses a broadband radiofrequency (RF) pulse to excite the off-resonance induced by the metallic implant, fully phase-encoded imaging to prevent in-plane distortions, and UTE to capture rapidly decaying signal. The performance of the externally calibrated parallel imaging reconstructions was assessed using phantoms and in vivo examples. Phantom and in vivo comparisons to self-calibrated parallel imaging acquisitions show that significant reductions in acquisition times can be achieved using externally calibrated parallel imaging with comparable image quality. Acquisition time reductions are particularly large for fully phase-encoded methods such as spectrally resolved fully phase-encoded three-dimensional (3D) fast spin-echo (SR-FPE), in which scan time reductions of up to 8 min were obtained. A fully phase-encoded acquisition with broadband excitation and UTE enabled externally calibrated parallel imaging for 3D-MSI, eliminating the need for repeated calibration regions at each frequency offset. Significant reductions in acquisition time can be achieved, particularly for fully phase-encoded methods like SR-FPE. Magn Reson Med 77:2303-2309, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  5. Science applications of a multispectral microscopic imager for the astrobiological exploration of Mars

    Science.gov (United States)

    Nunez, Jorge; Farmer, Jack; Sellar, R. Glenn; Swayze, Gregg A.; Blaney, Diana L.

    2014-01-01

    Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars.

  6. Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

  7. Integration of Satellite Tracking Data and Satellite Images for Detailed Characteristics of Wildlife Habitats

    Science.gov (United States)

    Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.

    2017-12-01

    Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.

  8. Crop status sensing system by multi-spectral imaging sensor, 1: Image processing and paddy field sensing

    International Nuclear Information System (INIS)

    Ishii, K.; Sugiura, R.; Fukagawa, T.; Noguchi, N.; Shibata, Y.

    2006-01-01

    The objective of the study is to construct a sensing system for precision farming. A Multi-Spectral Imaging Sensor (MSIS), which can obtain three images (G. R and NIR) simultaneously, was used for detecting growth status of plants. The sensor was mounted on an unmanned helicopter. An image processing method for acquiring information of crop status with high accuracy was developed. Crop parameters that were measured include SPAD, leaf height, and stems number. Both direct seeding variety and transplant variety of paddy rice were adopted in the research. The result of a field test showed that crop status of both varieties could be detected with sufficient accuracy to apply to precision farming

  9. An operative quantitative analysis of multispectral images of the eyeground

    Science.gov (United States)

    Lisenko, S. A.; Kugeiko, M. M.; Firago, V. A.; Kubarko, A. I.

    2014-09-01

    In the approximation of a four-layer model of the eyeground, we have studied the information content of photographs of the eyeground obtained in different spectral intervals from the visible range of the spectrum. We have shown that, under conditions of a priori uncertainty of all parameters of the eyeground that affect spectral fluxes of light multiply scattered by the eyeground, the two-dimensional distributions of the following parameters can be determined: (i) the contents of hemoglobin and macular pigment in the retina; (ii) the contents of melanin in the pigment epithelium and choroid; (iii) the degree of blood oxygenation; and (iv) the structural parameter of the retina, which characterizes the volume concentration of its effective scatterers. Based on results of a numerical simulation of the light-transfer process in the medium under study, we have determined regression relationships between parameters of the eyeground and spectral characteristics of its image and have proposed a method for the operative retrieval of parameter maps of the eyeground, which uses the determined regressions.

  10. CMOS Time-Resolved, Contact, and Multispectral Fluorescence Imaging for DNA Molecular Diagnostics

    Directory of Open Access Journals (Sweden)

    Nan Guo

    2014-10-01

    Full Text Available Instrumental limitations such as bulkiness and high cost prevent the fluorescence technique from becoming ubiquitous for point-of-care deoxyribonucleic acid (DNA detection and other in-field molecular diagnostics applications. The complimentary metal-oxide-semiconductor (CMOS technology, as benefited from process scaling, provides several advanced capabilities such as high integration density, high-resolution signal processing, and low power consumption, enabling sensitive, integrated, and low-cost fluorescence analytical platforms. In this paper, CMOS time-resolved, contact, and multispectral imaging are reviewed. Recently reported CMOS fluorescence analysis microsystem prototypes are surveyed to highlight the present state of the art.

  11. Transferring results from NIR-hyperspectral to NIR-multispectral imaging systems

    DEFF Research Database (Denmark)

    Calvini, Rosalba; Amigo Rubio, Jose Manuel; Ulrici, Alessandro

    2017-01-01

    commercially available filters matching the selected spectral regions, and used to calculate multivariate classification models with Partial Least Squares-Discriminant Analysis (PLS-DA) and sparse PLS-DA. Proper strategies for the definition of the training set and the selection of the most effective......Due to the differences in terms of both price and quality, the availability of effective instrumentation to discriminate between Arabica and Robusta coffee is extremely important. To this aim, the use of multispectral imaging systems could provide reliable and accurate real-time monitoring...

  12. Multispectral imaging as a potential tool for seed health testing of spinach (Spinacia oleracea L.)

    DEFF Research Database (Denmark)

    Olesen, M. Halkjaer; Carstensen, Jens Michael; Boelt, B.

    2011-01-01

    University. Our study demonstrates that multispectral imaging with wavelengths ranging from 395-970 nm can be used to distinguish between uninfected spinach seeds and seeds infected with Verticillium spp., Fusarium spp., Stemphylium botryosum, Cladosporium spp. and Alternaria alternata. Analytical separation...... using only NIR gave a separation of 26-88% between uninfected and Fusarium spp. infected seeds. Alternaria alternata and Fusarium spp. could be distinguished from each other and from Cladosporium spp., Verticillium spp. and Stemphylium spp. Separation of Cladosporium spp., Verticillium spp....... and Stemphylium spp. needs further development before practical application....

  13. Multi-spectral quantitative phase imaging based on filtration of light via ultrasonic wave

    Science.gov (United States)

    Machikhin, A. S.; Polschikova, O. V.; Ramazanova, A. G.; Pozhar, V. E.

    2017-07-01

    A new digital holographic microscopy scheme for multi-spectral quantitative phase imaging is proposed and implemented. It is based on acousto-optic filtration of wide-band low-coherence light at the entrance of a Mach-Zehnder interferometer, recording and digital processing of interferograms. The key requirements for the acousto-optic filter are discussed. The effectiveness of the technique is demonstrated by calculating the phase maps of human red blood cells at multiple wavelengths in the range 770-810 nm. The scheme can be used for the measurement of dispersion of thin films and biological samples.

  14. An Airborne Multispectral Imaging System Based on Two Consumer-Grade Cameras for Agricultural Remote Sensing

    Directory of Open Access Journals (Sweden)

    Chenghai Yang

    2014-06-01

    Full Text Available This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS sensor with 5616 × 3744 pixels. One camera captures normal color images, while the other is modified to obtain near-infrared (NIR images. The color camera is also equipped with a GPS receiver to allow geotagged images. A remote control is used to trigger both cameras simultaneously. Images are stored in 14-bit RAW and 8-bit JPEG files in CompactFlash cards. The second-order transformation was used to align the color and NIR images to achieve subpixel alignment in four-band images. The imaging system was tested under various flight and land cover conditions and optimal camera settings were determined for airborne image acquisition. Images were captured at altitudes of 305–3050 m (1000–10,000 ft and pixel sizes of 0.1–1.0 m were achieved. Four practical application examples are presented to illustrate how the imaging system was used to estimate cotton canopy cover, detect cotton root rot, and map henbit and giant reed infestations. Preliminary analysis of example images has shown that this system has potential for crop condition assessment, pest detection, and other agricultural applications.

  15. Multispectral analysis tools can increase utility of RGB color images in histology

    Science.gov (United States)

    Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

    2018-04-01

    Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

  16. Empirical water depth predictions in Dublin Bay based on satellite EO multispectral imagery and multibeam data using spatially weighted geographical analysis

    Science.gov (United States)

    Monteys, Xavier; Harris, Paul; Caloca, Silvia

    2014-05-01

    The coastal shallow water zone can be a challenging and expensive environment within which to acquire bathymetry and other oceanographic data using traditional survey methods. Dangers and limited swath coverage make some of these areas unfeasible to survey using ship borne systems, and turbidity can preclude marine LIDAR. As a result, an extensive part of the coastline worldwide remains completely unmapped. Satellite EO multispectral data, after processing, allows timely, cost efficient and quality controlled information to be used for planning, monitoring, and regulating coastal environments. It has the potential to deliver repetitive derivation of medium resolution bathymetry, coastal water properties and seafloor characteristics in shallow waters. Over the last 30 years satellite passive imaging methods for bathymetry extraction, implementing analytical or empirical methods, have had a limited success predicting water depths. Different wavelengths of the solar light penetrate the water column to varying depths. They can provide acceptable results up to 20 m but become less accurate in deeper waters. The study area is located in the inner part of Dublin Bay, on the East coast of Ireland. The region investigated is a C-shaped inlet covering an area of 10 km long and 5 km wide with water depths ranging from 0 to 10 m. The methodology employed on this research uses a ratio of reflectance from SPOT 5 satellite bands, differing to standard linear transform algorithms. High accuracy water depths were derived using multibeam data. The final empirical model uses spatially weighted geographical tools to retrieve predicted depths. The results of this paper confirm that SPOT satellite scenes are suitable to predict depths using empirical models in very shallow embayments. Spatial regression models show better adjustments in the predictions over non-spatial models. The spatial regression equation used provides realistic results down to 6 m below the water surface, with

  17. A fast and automatic mosaic method for high-resolution satellite images

    Science.gov (United States)

    Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

    2015-12-01

    We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

  18. Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

    Directory of Open Access Journals (Sweden)

    Shaodan Li

    2017-11-01

    Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

  19. TREE SPECIES CLASSIFICATION OF BROADLEAVED FORESTS IN NAGANO, CENTRAL JAPAN, USING AIRBORNE LASER DATA AND MULTISPECTRAL IMAGES

    Directory of Open Access Journals (Sweden)

    S. Deng

    2017-10-01

    Full Text Available This study attempted to classify three coniferous and ten broadleaved tree species by combining airborne laser scanning (ALS data and multispectral images. The study area, located in Nagano, central Japan, is within the broadleaved forests of the Afan Woodland area. A total of 235 trees were surveyed in 2016, and we recorded the species, DBH, and tree height. The geographical position of each tree was collected using a Global Navigation Satellite System (GNSS device. Tree crowns were manually detected using GNSS position data, field photographs, true-color orthoimages with three bands (red-green-blue, RGB, 3D point clouds, and a canopy height model derived from ALS data. Then a total of 69 features, including 27 image-based and 42 point-based features, were extracted from the RGB images and the ALS data to classify tree species. Finally, the detected tree crowns were classified into two classes for the first level (coniferous and broadleaved trees, four classes for the second level (Pinus densiflora, Larix kaempferi, Cryptomeria japonica, and broadleaved trees, and 13 classes for the third level (three coniferous and ten broadleaved species, using the 27 image-based features, 42 point-based features, all 69 features, and the best combination of features identified using a neighborhood component analysis algorithm, respectively. The overall classification accuracies reached 90 % at the first and second levels but less than 60 % at the third level. The classifications using the best combinations of features had higher accuracies than those using the image-based and point-based features and the combination of all of the 69 features.

  20. A methodology for calibration of hyperspectral and multispectral satellite data in coastal areas

    Science.gov (United States)

    Pennucci, Giuliana; Fargion, Giulietta; Alvarez, Alberto; Trees, Charles; Arnone, Robert

    2012-06-01

    The objective of this work is to determine the location(s) in any given oceanic area during different temporal periods where in situ sampling for Calibration/Validation (Cal/Val) provides the best capability to retrieve accurate radiometric and derived product data (lowest uncertainties). We present a method to merge satellite imagery with in situ measurements, to determine the best in situ sampling strategy suitable for satellite Cal/Val and to evaluate the present in situ locations through uncertainty indices. This analysis is required to determine if the present in situ sites are adequate for assessing uncertainty and where additional sites and ship programs should be located to improve Calibration/Validation (Cal/Val) procedures. Our methodology uses satellite acquisitions to build a covariance matrix encoding the spatial-temporal variability of the area of interest. The covariance matrix is used in a Bayesian framework to merge satellite and in situ data providing a product with lower uncertainty. The best in situ location for Cal/Val is then identified by using a design principle (A-optimum design) that looks for minimizing the estimated variance of the merged products. Satellite products investigated in this study include Ocean Color water leaving radiance, chlorophyll, and inherent and apparent optical properties (retrieved from MODIS and VIIRS). In situ measurements are obtained from systems operated on fixed deployment platforms (e.g., sites of the Ocean Color component of the AErosol RObotic NETwork- AERONET-OC), moorings (e.g, Marine Optical Buoy-MOBY), ships or autonomous vehicles (such as Autonomous Underwater Vehicles and/or Gliders).

  1. Classification of high resolution satellite images

    OpenAIRE

    Karlsson, Anders

    2003-01-01

    In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

  2. Multispectral imaging of the ocular fundus using light emitting diode illumination.

    Science.gov (United States)

    Everdell, N L; Styles, I B; Calcagni, A; Gibson, J; Hebden, J; Claridge, E

    2010-09-01

    We present an imaging system based on light emitting diode (LED) illumination that produces multispectral optical images of the human ocular fundus. It uses a conventional fundus camera equipped with a high power LED light source and a highly sensitive electron-multiplying charge coupled device camera. It is able to take pictures at a series of wavelengths in rapid succession at short exposure times, thereby eliminating the image shift introduced by natural eye movements (saccades). In contrast with snapshot systems the images retain full spatial resolution. The system is not suitable for applications where the full spectral resolution is required as it uses discrete wavebands for illumination. This is not a problem in retinal imaging where the use of selected wavelengths is common. The modular nature of the light source allows new wavelengths to be introduced easily and at low cost. The use of wavelength-specific LEDs as a source is preferable to white light illumination and subsequent filtering of the remitted light as it minimizes the total light exposure of the subject. The system is controlled via a graphical user interface that enables flexible control of intensity, duration, and sequencing of sources in synchrony with the camera. Our initial experiments indicate that the system can acquire multispectral image sequences of the human retina at exposure times of 0.05 s in the range of 500-620 nm with mean signal to noise ratio of 17 dB (min 11, std 4.5), making it suitable for quantitative analysis with application to the diagnosis and screening of eye diseases such as diabetic retinopathy and age-related macular degeneration.

  3. Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit.

    Science.gov (United States)

    Liu, Changhong; Liu, Wei; Chen, Wei; Yang, Jianbo; Zheng, Lei

    2015-04-15

    Tomato is an important health-stimulating fruit because of the antioxidant properties of its main bioactive compounds, dominantly lycopene and phenolic compounds. Nowadays, product differentiation in the fruit market requires an accurate evaluation of these value-added compounds. An experiment was conducted to simultaneously and non-destructively measure lycopene and phenolic compounds content in intact tomatoes using multispectral imaging combined with chemometric methods. Partial least squares (PLS), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) were applied to develop quantitative models. Compared with PLS and LS-SVM, BPNN model considerably improved the performance with coefficient of determination in prediction (RP(2))=0.938 and 0.965, residual predictive deviation (RPD)=4.590 and 9.335 for lycopene and total phenolics content prediction, respectively. It is concluded that multispectral imaging is an attractive alternative to the standard methods for determination of bioactive compounds content in intact tomatoes, providing a useful platform for infield fruit sorting/grading. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Galileo multispectral imaging of the north polar and eastern limb regions of the moon

    Science.gov (United States)

    Belton, M.J.S.; Greeley, R.; Greenberg, R.; McEwen, A.; Klaasen, K.P.; Head, J. W.; Pieters, C.; Neukum, G.; Chapman, C.R.; Geissler, P.; Heffernan, C.; Breneman, H.; Anger, C.; Carr, M.H.; Davies, M.E.; Fanale, F.P.; Gierasch, P.J.; Ingersoll, A.P.; Johnson, T.V.; Pilcher, C.B.; Thompson, W.R.; Veverka, J.; Sagan, C.

    1994-01-01

    Multispectral images obtained during the Galileo probe's second encounter with the moon reveal the compositional nature of the north polar regions and the northeastern limb. Mare deposits in these regions are found to be primarily low to medium titanium lavas and, as on the western limb, show only slight spectral heterogeneity. The northern light plains are found to have the spectral characteristics of highlands materials, show little evidence for the presence of cryptomaria, and were most likely emplaced by impact processes regardless of their age.Multispectral images obtained during the Galileo probe's second encounter with the moon reveal the compositional nature of the north polar regions and the northeastern limb. Mare deposits in these regions are found to be primarily low to medium titanium lavas and, as on the western limb, show only slight spectral heterogeneity. The northern light plains are found to have the spectral characteristics of highlands materials, show little evidence for the presence of cryptomaria, and were most likely emplaced by impact processes regardless of their age.

  5. A Method of High Throughput Monitoring Crop Physiology Using Chlorophyll Fluorescence and Multispectral Imaging.

    Science.gov (United States)

    Wang, Heng; Qian, Xiangjie; Zhang, Lan; Xu, Sailong; Li, Haifeng; Xia, Xiaojian; Dai, Liankui; Xu, Liang; Yu, Jingquan; Liu, Xu

    2018-01-01

    We present a high throughput crop physiology condition monitoring system and corresponding monitoring method. The monitoring system can perform large-area chlorophyll fluorescence imaging and multispectral imaging. The monitoring method can determine the crop current condition continuously and non-destructively. We choose chlorophyll fluorescence parameters and relative reflectance of multispectral as the indicators of crop physiological status. Using tomato as experiment subject, the typical crop physiological stress, such as drought, nutrition deficiency and plant disease can be distinguished by the monitoring method. Furthermore, we have studied the correlation between the physiological indicators and the degree of stress. Besides realizing the continuous monitoring of crop physiology, the monitoring system and method provide the possibility of machine automatic diagnosis of the plant physiology. Highlights: A newly designed high throughput crop physiology monitoring system and the corresponding monitoring method are described in this study. Different types of stress can induce distinct fluorescence and spectral characteristics, which can be used to evaluate the physiological status of plants.

  6. Classification of peacock feather reflectance using principal component analysis similarity factors from multispectral imaging data.

    Science.gov (United States)

    Medina, José M; Díaz, José A; Vukusic, Pete

    2015-04-20

    Iridescent structural colors in biology exhibit sophisticated spatially-varying reflectance properties that depend on both the illumination and viewing angles. The classification of such spectral and spatial information in iridescent structurally colored surfaces is important to elucidate the functional role of irregularity and to improve understanding of color pattern formation at different length scales. In this study, we propose a non-invasive method for the spectral classification of spatial reflectance patterns at the micron scale based on the multispectral imaging technique and the principal component analysis similarity factor (PCASF). We demonstrate the effectiveness of this approach and its component methods by detailing its use in the study of the angle-dependent reflectance properties of Pavo cristatus (the common peacock) feathers, a species of peafowl very well known to exhibit bright and saturated iridescent colors. We show that multispectral reflectance imaging and PCASF approaches can be used as effective tools for spectral recognition of iridescent patterns in the visible spectrum and provide meaningful information for spectral classification of the irregularity of the microstructure in iridescent plumage.

  7. Building Keypoint Mappings on Multispectral Images by a Cascade of Classifiers with a Resurrection Mechanism

    Directory of Open Access Journals (Sweden)

    Yong Li

    2015-05-01

    Full Text Available Inspired by the boosting technique for detecting objects, this paper proposes a cascade structure with a resurrection mechanism to establish keypoint mappings on multispectral images. The cascade structure is composed of four steps by utilizing best bin first (BBF, color and intensity distribution of segment (CIDS, global information and the RANSAC process to remove outlier keypoint matchings. Initial keypoint mappings are built with the descriptors associated with keypoints; then, at each step, only a small number of keypoint mappings of a high confidence are classified to be incorrect. The unclassified keypoint mappings will be passed on to subsequent steps for determining whether they are correct. Due to the drawback of a classification rule, some correct keypoint mappings may be misclassified as incorrect at a step. Observing this, we design a resurrection mechanism, so that they will be reconsidered and evaluated by the rules utilized in subsequent steps. Experimental results show that the proposed cascade structure combined with the resurrection mechanism can effectively build more reliable keypoint mappings on multispectral images than existing methods.

  8. Spatial Data Exploring by Satellite Image Distributed Processing

    Science.gov (United States)

    Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

    2012-04-01

    Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands

  9. Multispectral Thermal Imager Optical Assembly Performance and Integration of the Flight Focal Plane Assembly

    International Nuclear Information System (INIS)

    Blake, Dick; Byrd, Don; Christensen, Wynn; Henson, Tammy; Krumel, Les; Rappoport, William; Shen, Gon-Yen

    1999-01-01

    The Multispectral Thermal Imager Optical Assembly (OA) has been fabricated, assembled, successfully performance tested, and integrated into the flight payload structure with the flight Focal Plane Assembly (FPA) integrated and aligned to it. This represents a major milestone achieved towards completion of this earth observing E-O imaging sensor that is to be operated in low earth orbit. The OA consists of an off-axis three mirror anastigmatic (TMA) telescope with a 36 cm unobscured clear aperture, a wide-field-of-view (WFOV) of 1.82 along the direction of spacecraft motion and 1.38 across the direction of spacecraft motion. It also contains a comprehensive on-board radiometric calibration system. The OA is part of a multispectral pushbroom imaging sensor which employs a single mechanically cooled focal plane with 15 spectral bands covering a wavelength range from 0.45 to 10.7 m. The OA achieves near diffraction-limited performance from visible to the long-wave infrared (LWIR) wavelengths. The two major design drivers for the OA are 80% enpixeled energy in the visible bands and radiometric stability. Enpixeled energy in the visible bands also drove the alignment of the FPA detectors to the OA image plane to a requirement of less than 20 m over the entire visible detector field of view (FOV). Radiometric stability requirements mandated a cold Lyot stop for stray light rejection and thermal background reduction. The Lyot stop is part of the FPA assembly and acts as the aperture stop for the imaging system. The alignment of the Lyot stop to the OA drove the centering and to some extent the tilt alignment requirements of the FPA to the OA

  10. Method using in vivo quantitative spectroscopy to guide design and optimization of low-cost, compact clinical imaging devices: emulation and evaluation of multispectral imaging systems

    Science.gov (United States)

    Saager, Rolf B.; Baldado, Melissa L.; Rowland, Rebecca A.; Kelly, Kristen M.; Durkin, Anthony J.

    2018-04-01

    With recent proliferation in compact and/or low-cost clinical multispectral imaging approaches and commercially available components, questions remain whether they adequately capture the requisite spectral content of their applications. We present a method to emulate the spectral range and resolution of a variety of multispectral imagers, based on in-vivo data acquired from spatial frequency domain spectroscopy (SFDS). This approach simulates spectral responses over 400 to 1100 nm. Comparing emulated data with full SFDS spectra of in-vivo tissue affords the opportunity to evaluate whether the sparse spectral content of these imagers can (1) account for all sources of optical contrast present (completeness) and (2) robustly separate and quantify sources of optical contrast (crosstalk). We validate the approach over a range of tissue-simulating phantoms, comparing the SFDS-based emulated spectra against measurements from an independently characterized multispectral imager. Emulated results match the imager across all phantoms (<3 % absorption, <1 % reduced scattering). In-vivo test cases (burn wounds and photoaging) illustrate how SFDS can be used to evaluate different multispectral imagers. This approach provides an in-vivo measurement method to evaluate the performance of multispectral imagers specific to their targeted clinical applications and can assist in the design and optimization of new spectral imaging devices.

  11. Optical perception for detection of cutaneous T-cell lymphoma by multi-spectral imaging

    International Nuclear Information System (INIS)

    Hsiao, Yu-Ping; Wang, Hsiang-Chen; Chen, Shih-Hua; Tsai, Chung-Hung; Yang, Jen-Hung

    2014-01-01

    In this study, the spectrum of each picture element of the patient’s skin image was obtained by multi-spectral imaging technology. Spectra of normal or pathological skin were collected from 15 patients. Principal component analysis and principal component scores of skin spectra were employed to distinguish the spectral characteristics with different diseases. Finally, skin regions with suspected cutaneous T-cell lymphoma (CTCL) lesions were successfully predicted by evaluation and classification of the spectra of pathological skin. The sensitivity and specificity of this technique were 89.65% and 95.18% after the analysis of about 109 patients. The probability of atopic dermatitis and psoriasis patients misinterpreted as CTCL were 5.56% and 4.54%, respectively. (paper)

  12. Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

    Science.gov (United States)

    García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

    2018-04-01

    Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important

  13. Water Quality Determination of Küçükçekmece Lake, Turkey by Using Multispectral Satellite Data

    Directory of Open Access Journals (Sweden)

    Erhan Alparslan

    2009-01-01

    Full Text Available This study focuses on the analysis of the Landsat-5 TM + SPOT-Pan (1992, IRS-1C/D LISS + Pan (2000, and Landsat-5 TM (2006 satellite images that reflect the drastic land use/land cover changes in the Küçükçekmece Lake region, Istanbul. Landsat-5 TM satellite data dated 2006 was used for mapping water quality. A multiple regression analysis was carried out between the unitless planetary reflectance values derived from the satellite image and in situ water quality parameters chlorophyll a, total phosphorus, total nitrogen, turbidity, and biological and chemical oxygen demand measured at a number of stations homogenously distributed over the lake surface. The results of this study provided valuable information to local administrators on the water quality of Küçükçekmece Lake, which is a large water resource of the Istanbul Metropolitan Area. Results also show that such a methodology structured by use of reflectance values provided from satellite imagery, in situ water quality measurements, and basin land use/land cover characteristics obtained from images can serve as a powerful and rapid monitoring tool for the drinking water basins that suffer from rapid urbanization and pollution, all around the world.

  14. Blind source separation of ex-vivo aorta tissue multispectral images.

    Science.gov (United States)

    Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

    2015-05-01

    Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method's performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue.

  15. Multispectral fluorescence imaging of human ovarian and Fallopian tube tissue for early stage cancer detection

    Science.gov (United States)

    Tate, Tyler; Baggett, Brenda; Rice, Photini; Watson, Jennifer; Orsinger, Gabe; Nymeyer, Ariel C.; Welge, Weston A.; Keenan, Molly; Saboda, Kathylynn; Roe, Denise J.; Hatch, Kenneth; Chambers, Setsuko; Black, John; Utzinger, Urs; Barton, Jennifer

    2015-03-01

    With early detection, five year survival rates for ovarian cancer are over 90%, yet no effective early screening method exists. Emerging consensus suggests that perhaps over 50% of the most lethal form of the disease, high grade serous ovarian cancer, originates in the Fallopian tube. Cancer changes molecular concentrations of various endogenous fluorophores. Using specific excitation wavelengths and emissions bands on a Multispectral Fluorescence Imaging (MFI) system, spatial and spectral data over a wide field of view can be collected from endogenous fluorophores. Wavelength specific reflectance images provide additional information to normalize for tissue geometry and blood absorption. Ratiometric combination of the images may create high contrast between neighboring normal and abnormal tissue. Twenty-six women undergoing oophorectomy or debulking surgery consented the use of surgical discard tissue samples for MFI imaging. Forty-nine pieces of ovarian tissue and thirty-two pieces of Fallopian tube tissue were collected and imaged with excitation wavelengths between 280 nm and 550 nm. After imaging, each tissue sample was fixed, sectioned and HE stained for pathological evaluation. Comparison of mean intensity values between normal, benign, and cancerous tissue demonstrate a general trend of increased fluorescence of benign tissue and decreased fluorescence of cancerous tissue when compared to normal tissue. The predictive capabilities of the mean intensity measurements are tested using multinomial logistic regression and quadratic discriminant analysis. Adaption of the system for in vivo Fallopian tube and ovary endoscopic imaging is possible and is briefly described.

  16. Backthinned TDI CCD image sensor design and performance for the Pleiades high resolution Earth observation satellites

    Science.gov (United States)

    Materne, A.; Bardoux, A.; Geoffray, H.; Tournier, T.; Kubik, P.; Morris, D.; Wallace, I.; Renard, C.

    2017-11-01

    The PLEIADES-HR Earth observing satellites, under CNES development, combine a 0.7m resolution panchromatic channel, and a multispectral channel allowing a 2.8 m resolution, in 4 spectral bands. The 2 satellites will be placed on a sun-synchronous orbit at an altitude of 695 km. The camera operates in push broom mode, providing images across a 20 km swath. This paper focuses on the specifications, design and performance of the TDI detectors developed by e2v technologies under CNES contract for the panchromatic channel. Design drivers, derived from the mission and satellite requirements, architecture of the sensor and measurement results for key performances of the first prototypes are presented.

  17. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.

    2006-01-01

    Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

  18. High throughput phenotyping of tomato spotted wilt disease in peanuts using unmanned aerial systems and multispectral imaging

    Science.gov (United States)

    The amount of visible and near infrared light reflected by plants varies depending on their health. In this study, multispectral images were acquired by quadcopter for detecting tomato spot wilt virus amongst twenty genetic varieties of peanuts. The plants were visually assessed to acquire ground ...

  19. Radical advancement in multi-spectral imaging for autonomous vehicles (UAVs, UGVs, and UUVs) using active compensation.

    Energy Technology Data Exchange (ETDEWEB)

    Clark, Brian F.; Bagwell, Brett E.; Wick, David Victor

    2007-01-01

    The purpose of this LDRD was to demonstrate a compact, multi-spectral, refractive imaging systems using active optical compensation. Compared to a comparable, conventional lens system, our system has an increased operational bandwidth, provides for spectral selectivity and, non-mechanically corrects aberrations induced by the wavelength dependent properties of a passive refractive optical element (i.e. lens). The compact nature and low power requirements of the system lends itself to small platforms such as autonomous vehicles. In addition, the broad spectral bandwidth of our system would allow optimized performance for both day/night use, and the multi-spectral capability allows for spectral discrimination and signature identification.

  20. Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

    Science.gov (United States)

    Holben, Brent N.; Shimabukuro, Yosio E.

    1993-01-01

    A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

  1. Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour

    Directory of Open Access Journals (Sweden)

    Puneet Mishra

    2015-06-01

    Full Text Available In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and compared with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

  2. Northern Everglades, Florida, satellite image map

    Science.gov (United States)

    Thomas, Jean-Claude; Jones, John W.

    2002-01-01

    These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

  3. South Florida Everglades: satellite image map

    Science.gov (United States)

    Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

    2001-01-01

    These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

  4. Fundamental Limitations for Imaging GEO Satellites

    Science.gov (United States)

    2015-10-18

    Fundamental limitations for imaging GEO satellites D. Mozurkewich Seabrook Engineering , Seabrook, MD 20706 USA H. R. Schmitt, J. T. Armstrong Naval...higher spatial frequency. Send correspondence to David Mozurkewich, Seabrook Engineering , 9310 Dubarry Ave., Seabrook MD 20706 E-mail: dave

  5. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

    Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...

  6. Ex vivo photometric and polarimetric multilayer characterization of human healthy colon by multispectral Mueller imaging.

    Science.gov (United States)

    Pierangelo, Angelo; Manhas, Sandeep; Benali, Abdelali; Fallet, Clément; Antonelli, Maria-Rosaria; Novikova, Tatiana; Gayet, Brice; Validire, Pierre; De Martino, Antonello

    2012-06-01

    Healthy human colon samples were analyzed ex vivo with a multispectral imaging Mueller polarimeter operating from 500 to 700 nm in a backscattering configuration with diffuse light illumination impinging on the innermost tissue layer, the mucosa. The intensity and polarimetric responses were taken on whole tissues first and after progressive exfoliation of the outer layers afterwards. Moreover, these measurements were carried out with two different substrates (one bright and the other dark) successively placed beneath each sample, allowing a reasonably accurate evaluation of the contributions to the overall backscattered light by the various layers. For the shorter investigated wavelengths (500 to 550 nm) the major contribution comes from mucosa and submucosa, while for the longer wavelengths (650 to 700 nm) muscular tissue and fat also contribute significantly. The depolarization has also been studied and is found to be stronger in the red part of the spectrum, mainly due to the highly depolarizing power of the muscular and fat layers.

  7. MONSTIR II: A 32-channel, multispectral, time-resolved optical tomography system for neonatal brain imaging

    Energy Technology Data Exchange (ETDEWEB)

    Cooper, Robert J., E-mail: robert.cooper@ucl.ac.uk; Magee, Elliott; Everdell, Nick; Magazov, Salavat; Varela, Marta; Airantzis, Dimitrios; Gibson, Adam P.; Hebden, Jeremy C. [Biomedical Optics Research Laboratory, Department of Medical Physics and Bioengineering, University College London, London WC1E 6BT (United Kingdom)

    2014-05-15

    We detail the design, construction and performance of the second generation UCL time-resolved optical tomography system, known as MONSTIR II. Intended primarily for the study of the newborn brain, the system employs 32 source fibres that sequentially transmit picosecond pulses of light at any four wavelengths between 650 and 900 nm. The 32 detector channels each contain an independent photo-multiplier tube and temporally correlated photon-counting electronics that allow the photon transit time between each source and each detector position to be measured with high temporal resolution. The system's response time, temporal stability, cross-talk, and spectral characteristics are reported. The efficacy of MONSTIR II is demonstrated by performing multi-spectral imaging of a simple phantom.

  8. Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging

    International Nuclear Information System (INIS)

    Wang, Hsiang-Chen; Tsai, Meng-Tsan; Chiang, Chun-Ping

    2013-01-01

    Color reproduction systems based on the multi-spectral imaging technique (MSI) for both directly estimating reflection spectra and direct visualization of oral tissues using various light sources are proposed. Images from three oral cancer patients were taken as the experimental samples, and spectral differences between pre-cancerous and normal oral mucosal tissues were calculated at three time points during 5-aminolevulinic acid photodynamic therapy (ALA-PDT) to analyze whether they were consistent with disease processes. To check the successful treatment of oral cancer with ALA-PDT, oral cavity images by swept source optical coherence tomography (SS-OCT) are demonstrated. This system can also reproduce images under different light sources. For pre-cancerous detection, the oral images after the second ALA-PDT are assigned as the target samples. By using RGB LEDs with various correlated color temperatures (CCTs) for color difference comparison, the light source with a CCT of about 4500 K was found to have the best ability to enhance the color difference between pre-cancerous and normal oral mucosal tissues in the oral cavity. Compared with the fluorescent lighting commonly used today, the color difference can be improved by 39.2% from 16.5270 to 23.0023. Hence, this light source and spectral analysis increase the efficiency of the medical diagnosis of oral cancer and aid patients in receiving early treatment. (paper)

  9. Multispectral photoacoustic characterization of ICG and porcine blood using an LED-based photoacoustic imaging system

    Science.gov (United States)

    Shigeta, Yusuke; Sato, Naoto; Kuniyil Ajith Singh, Mithun; Agano, Toshitaka

    2018-02-01

    Photoacoustic imaging is a hybrid biomedical imaging modality that has emerged over the last decade. In photoacoustic imaging, pulsed-light absorbed by the target emits ultrasound that can be detected using a conventional ultrasound array. This ultrasound data can be used to reconstruct the location and spatial details of the intrinsic/extrinsic light absorbers in the tissue. Recently we reported on the development of a multi-wavelength high frame-rate LED-based photoacoustic/ultrasound imaging system (AcousticX). In this work, we photoacoustically characterize the absorption spectrum of ICG and porcine blood using LED arrays with multiple wavelengths (405, 420, 470, 520, 620, 660, 690, 750, 810, 850, 925, 980 nm). Measurements were performed in a simple reflection mode configuration in which LED arrays where fixed on both sides of the linear array ultrasound probe. Phantom used consisted of micro-test tubes filled with ICG and porcine blood, which were placed in a tank filled with water. The photoacoustic spectrum obtained from our measurements matches well with the reference absorption spectrum. These results demonstrate the potential capability of our system in performing clinical/pre-clinical multispectral photoacoustic imaging.

  10. SENSOR CORRECTION AND RADIOMETRIC CALIBRATION OF A 6-BAND MULTISPECTRAL IMAGING SENSOR FOR UAV REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    J. Kelcey

    2012-07-01

    Full Text Available The increased availability of unmanned aerial vehicles (UAVs has resulted in their frequent adoption for a growing range of remote sensing tasks which include precision agriculture, vegetation surveying and fine-scale topographic mapping. The development and utilisation of UAV platforms requires broad technical skills covering the three major facets of remote sensing: data acquisition, data post-processing, and image analysis. In this study, UAV image data acquired by a miniature 6-band multispectral imaging sensor was corrected and calibrated using practical image-based data post-processing techniques. Data correction techniques included dark offset subtraction to reduce sensor noise, flat-field derived per-pixel look-up-tables to correct vignetting, and implementation of the Brown- Conrady model to correct lens distortion. Radiometric calibration was conducted with an image-based empirical line model using pseudo-invariant features (PIFs. Sensor corrections and radiometric calibration improve the quality of the data, aiding quantitative analysis and generating consistency with other calibrated datasets.

  11. Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging

    Science.gov (United States)

    Wang, Hsiang-Chen; Tsai, Meng-Tsan; Chiang, Chun-Ping

    2013-05-01

    Color reproduction systems based on the multi-spectral imaging technique (MSI) for both directly estimating reflection spectra and direct visualization of oral tissues using various light sources are proposed. Images from three oral cancer patients were taken as the experimental samples, and spectral differences between pre-cancerous and normal oral mucosal tissues were calculated at three time points during 5-aminolevulinic acid photodynamic therapy (ALA-PDT) to analyze whether they were consistent with disease processes. To check the successful treatment of oral cancer with ALA-PDT, oral cavity images by swept source optical coherence tomography (SS-OCT) are demonstrated. This system can also reproduce images under different light sources. For pre-cancerous detection, the oral images after the second ALA-PDT are assigned as the target samples. By using RGB LEDs with various correlated color temperatures (CCTs) for color difference comparison, the light source with a CCT of about 4500 K was found to have the best ability to enhance the color difference between pre-cancerous and normal oral mucosal tissues in the oral cavity. Compared with the fluorescent lighting commonly used today, the color difference can be improved by 39.2% from 16.5270 to 23.0023. Hence, this light source and spectral analysis increase the efficiency of the medical diagnosis of oral cancer and aid patients in receiving early treatment.

  12. Use of high resolution satellite images for monitoring of earthquakes and volcano activity.

    Science.gov (United States)

    Arellano-Baeza, Alonso A.

    Our studies have shown that the strain energy accumulation deep in the Earth's crust that precedes a strong earthquake can be detected by applying a lineament extraction technique to the high-resolution multispectral satellite images. A lineament is a straight or a somewhat curved feature in a satellite image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. We analyzed tens of earthquakes occurred in the Pacific coast of the South America with the Richter scale magnitude ˜4.5, using ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changed significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth's crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion. The results obtained made it possible to include this research as a part of scientific program of Chilean Remote Sensing Satellite mission to be launched in 2010.

  13. Selection of optimal multispectral imaging system parameters for small joint arthritis detection

    Science.gov (United States)

    Dolenec, Rok; Laistler, Elmar; Stergar, Jost; Milanic, Matija

    2018-02-01

    Early detection and treatment of arthritis is essential for a successful outcome of the treatment, but it has proven to be very challenging with existing diagnostic methods. Novel methods based on the optical imaging of the affected joints are becoming an attractive alternative. A non-contact multispectral imaging (MSI) system for imaging of small joints of human hands and feet is being developed. In this work, a numerical simulation of the MSI system is presented. The purpose of the simulation is to determine the optimal design parameters. Inflamed and unaffected human joint models were constructed with a realistic geometry and tissue distributions, based on a MRI scan of a human finger with a spatial resolution of 0.2 mm. The light transport simulation is based on a weighted-photon 3D Monte Carlo method utilizing CUDA GPU acceleration. An uniform illumination of the finger within the 400-1100 nm spectral range was simulated and the photons exiting the joint were recorded using different acceptance angles. From the obtained reflectance and transmittance images the spectral and spatial features most indicative of inflammation were identified. Optimal acceptance angle and spectral bands were determined. This study demonstrates that proper selection of MSI system parameters critically affects ability of a MSI system to discriminate the unaffected and inflamed joints. The presented system design optimization approach could be applied to other pathologies.

  14. An Effective Palmprint Recognition Approach for Visible and Multispectral Sensor Images.

    Science.gov (United States)

    Gumaei, Abdu; Sammouda, Rachid; Al-Salman, Abdul Malik; Alsanad, Ahmed

    2018-05-15

    Among several palmprint feature extraction methods the HOG-based method is attractive and performs well against changes in illumination and shadowing of palmprint images. However, it still lacks the robustness to extract the palmprint features at different rotation angles. To solve this problem, this paper presents a hybrid feature extraction method, named HOG-SGF that combines the histogram of oriented gradients (HOG) with a steerable Gaussian filter (SGF) to develop an effective palmprint recognition approach. The approach starts by processing all palmprint images by David Zhang's method to segment only the region of interests. Next, we extracted palmprint features based on the hybrid HOG-SGF feature extraction method. Then, an optimized auto-encoder (AE) was utilized to reduce the dimensionality of the extracted features. Finally, a fast and robust regularized extreme learning machine (RELM) was applied for the classification task. In the evaluation phase of the proposed approach, a number of experiments were conducted on three publicly available palmprint databases, namely MS-PolyU of multispectral palmprint images and CASIA and Tongji of contactless palmprint images. Experimentally, the results reveal that the proposed approach outperforms the existing state-of-the-art approaches even when a small number of training samples are used.

  15. Off-resonance suppression for multispectral MR imaging near metallic implants.

    Science.gov (United States)

    den Harder, J Chiel; van Yperen, Gert H; Blume, Ulrike A; Bos, Clemens

    2015-01-01

    Metal artifact reduction in MRI within clinically feasible scan-times without through-plane aliasing. Existing metal artifact reduction techniques include view angle tilting (VAT), which resolves in-plane distortions, and multispectral imaging (MSI) techniques, such as slice encoding for metal artifact correction (SEMAC) and multi-acquisition with variable resonances image combination (MAVRIC), that further reduce image distortions, but significantly increase scan-time. Scan-time depends on anatomy size and anticipated total spectral content of the signal. Signals outside the anticipated spatial region may cause through-plane back-folding. Off-resonance suppression (ORS), using different gradient amplitudes for excitation and refocusing, is proposed to provide well-defined spatial-spectral selectivity in MSI to allow scan-time reduction and flexibility of scan-orientation. Comparisons of MSI techniques with and without ORS were made in phantom and volunteer experiments. Off-resonance suppressed SEMAC (ORS-SEMAC) and outer-region suppressed MAVRIC (ORS-MAVRIC) required limited through-plane phase encoding steps compared with original MSI. Whereas SEMAC (scan time: 5'46") and MAVRIC (4'12") suffered from through-plane aliasing, ORS-SEMAC and ORS-MAVRIC allowed alias-free imaging in the same scan-times. ORS can be used in MSI to limit the selected spatial-spectral region and contribute to metal artifact reduction in clinically feasible scan-times while avoiding slice aliasing. © 2014 Wiley Periodicals, Inc.

  16. Predicting Electron Population Characteristics in 2-D Using Multispectral Ground-Based Imaging

    Science.gov (United States)

    Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Jahn, Jorg-Micha

    2018-01-01

    Ground-based imaging and in situ sounding rocket data are compared to electron transport modeling for an active inverted-V type auroral event. The Ground-to-Rocket Electrodynamics-Electrons Correlative Experiment (GREECE) mission successfully launched from Poker Flat, Alaska, on 3 March 2014 at 11:09:50 UT and reached an apogee of approximately 335 km over the aurora. Multiple ground-based electron-multiplying charge-coupled device (EMCCD) imagers were positioned at Venetie, Alaska, and aimed toward magnetic zenith. The imagers observed the intensity of different auroral emission lines (427.8, 557.7, and 844.6 nm) at the magnetic foot point of the rocket payload. Emission line intensity data are correlated with electron characteristics measured by the GREECE onboard electron spectrometer. A modified version of the GLobal airglOW (GLOW) model is used to estimate precipitating electron characteristics based on optical emissions. GLOW predicted the electron population characteristics with 20% error given the observed spectral intensities within 10° of magnetic zenith. Predictions are within 30% of the actual values within 20° of magnetic zenith for inverted-V-type aurora. Therefore, it is argued that this technique can be used, at least in certain types of aurora, such as the inverted-V type presented here, to derive 2-D maps of electron characteristics. These can then be used to further derive 2-D maps of ionospheric parameters as a function of time, based solely on multispectral optical imaging data.

  17. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

    Science.gov (United States)

    Song, Huihui

    -MODIS image pairs, we build the corresponding relationship between the difference images of MODIS and ETM+ by training a low- and high-resolution dictionary pair from the given prior image pairs. In the second scenario, i.e., only one Landsat- MODIS image pair being available, we directly correlate MODIS and ETM+ data through an image degradation model. Then, the fusion stage is achieved by super-resolving the MODIS image combining the high-pass modulation in a two-layer fusion framework. Remarkably, the proposed spatial-temporal fusion methods form a unified framework for blending remote sensing images with phenology change or land-cover-type change. Based on the proposed spatial-temporal fusion models, we propose to monitor the land use/land cover changes in Shenzhen, China. As a fast-growing city, Shenzhen faces the problem of detecting the rapid changes for both rational city planning and sustainable development. However, the cloudy and rainy weather in region Shenzhen located makes the capturing circle of high-quality satellite images longer than their normal revisit periods. Spatial-temporal fusion methods are capable to tackle this problem by improving the spatial resolution of images with coarse spatial resolution but frequent temporal coverage, thereby making the detection of rapid changes possible. On two Landsat-MODIS datasets with annual and monthly changes, respectively, we apply the proposed spatial-temporal fusion methods to the task of multiple change detection. Afterward, we propose a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning and sparse non-negative matrix factorization. By combining the spectral information from hyperspectral image, which is characterized by low spatial resolution but high spectral resolution and abbreviated as LSHS, and the spatial information from multispectral image, which is featured by high spatial resolution but low spectral

  18. Detection and monitoring of two dust storm events by multispectral modis images.

    Digital Repository Service at National Institute of Oceanography (India)

    Mehta P.S.; Kunte, P.D.

    of Oman, over Arabian Sea to the coast of Pakistan. The dust storm lasted over the Arabian Sea till 30th March. MODIS sensors on both Terra and Aqua Satellites captured images of both events. From the difference in emissive/transmissive nature...

  19. Primer on Use of Multi-Spectral and Infra Red Imaging for On-Site Inspections

    Energy Technology Data Exchange (ETDEWEB)

    Henderson, J R

    2010-10-26

    The purpose of an On-Site Inspection (OSI) is to determine whether a nuclear explosion has occurred in violation of the Comprehensive Nuclear Test Ban Treaty (CTBT), and to gather information which might assist in identifying the violator (CTBT, Article IV, Paragraph 35) Multi-Spectral and Infra Red Imaging (MSIR) is allowed by the treaty to detect observables which might help reduce the search area and thus expedite an OSI and make it more effective. MSIR is permitted from airborne measurements, and at and below the surface to search for anomalies and artifacts (CTBT, Protocol, Part II, Paragraph 69b). The three broad types of anomalies and artifacts MSIR is expected to be capable of observing are surface disturbances (disturbed earth, plant stress or anomalous surface materials), human artifacts (man-made roads, buildings and features), and thermal anomalies. The purpose of this Primer is to provide technical information on MSIR relevant to its use for OSI. It is expected that this information may be used for general background information, to inform decisions about the selection and testing of MSIR equipment, to develop operational guidance for MSIR use during an OSI, and to support the development of a training program for OSI Inspectors. References are provided so readers can pursue a topic in more detail than the summary information provided here. The following chapters will provide more information on how MSIR can support an OSI (Section 2), a short summary what Multi-Spectral Imaging and Infra Red Imaging is (Section 3), guidance from the CTBT regarding the use of MSIR (Section 4), and a description of several nuclear explosion scenarios (Section 5) and consequent observables (Section 6). The remaining sections focus on practical aspects of using MSIR for an OSI, such as specification and selection of MSIR equipment, operational considerations for deployment of MISR equipment from an aircraft, and the conduct of field exercises to mature MSIR for an OSI

  20. Mapping Aquatic Vegetation in a Tropical Wetland Using High Spatial Resolution Multispectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Timothy G. Whiteside

    2015-09-01

    Full Text Available Vegetation plays a key role in the environmental function of wetlands. The Ramsar-listed wetlands of the Magela Creek floodplain in Northern Australia are identified as being at risk from weeds, fire and climate change. In addition, the floodplain is a downstream receiving environment for the Ranger Uranium Mine. Accurate methods for mapping wetland vegetation are required to provide contemporary baselines of annual vegetation dynamics on the floodplain to assist with analysing any potential change during and after minesite rehabilitation. The aim of this study was to develop and test the applicability of geographic object-based image analysis including decision tree classification to classify WorldView-2 imagery and LiDAR-derived ancillary data to map the aquatic vegetation communities of the Magela Creek floodplain. Results of the decision tree classification were compared against a Random Forests classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010. The decision tree classification method provided an overall accuracy of 78% which was significantly higher than the overall accuracy of the Random Forests classification (67%. Most of the error in both classifications was associated with confusion between spectrally similar classes dominated by grasses, such as Hymenachne and Pseudoraphis. In addition, the extent of the sedge Eleocharis was under-estimated in both cases. This suggests the method could be useful for mapping wetlands where statistical-based supervised classifications have achieved less than satisfactory results. Based upon the results, the decision tree method will form part of an ongoing operational monitoring program.

  1. Detection of rice sheath blight using an unmanned aerial system with high-resolution color and multispectral imaging.

    Science.gov (United States)

    Zhang, Dongyan; Zhou, Xingen; Zhang, Jian; Lan, Yubin; Xu, Chao; Liang, Dong

    2018-01-01

    Detection and monitoring are the first essential step for effective management of sheath blight (ShB), a major disease in rice worldwide. Unmanned aerial systems have a high potential of being utilized to improve this detection process since they can reduce the time needed for scouting for the disease at a field scale, and are affordable and user-friendly in operation. In this study, a commercialized quadrotor unmanned aerial vehicle (UAV), equipped with digital and multispectral cameras, was used to capture imagery data of research plots with 67 rice cultivars and elite lines. Collected imagery data were then processed and analyzed to characterize the development of ShB and quantify different levels of the disease in the field. Through color features extraction and color space transformation of images, it was found that the color transformation could qualitatively detect the infected areas of ShB in the field plots. However, it was less effective to detect different levels of the disease. Five vegetation indices were then calculated from the multispectral images, and ground truths of disease severity and GreenSeeker measured NDVI (Normalized Difference Vegetation Index) were collected. The results of relationship analyses indicate that there was a strong correlation between ground-measured NDVIs and image-extracted NDVIs with the R2 of 0.907 and the root mean square error (RMSE) of 0.0854, and a good correlation between image-extracted NDVIs and disease severity with the R2 of 0.627 and the RMSE of 0.0852. Use of image-based NDVIs extracted from multispectral images could quantify different levels of ShB in the field plots with an accuracy of 63%. These results demonstrate that a customer-grade UAV integrated with digital and multispectral cameras can be an effective tool to detect the ShB disease at a field scale.

  2. Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

    Energy Technology Data Exchange (ETDEWEB)

    Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

    2010-10-21

    The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

  3. Geomorphology of coastal environments from satellite images

    International Nuclear Information System (INIS)

    Da Rocha Ribeiro, R.; Velho, L.; Schossler, V.

    2010-01-01

    This study aims at recognizing coastal environments supported by data from the Landsat Thematic Mapper (TM) satellite. The digital processing of images, System Information Geographic (SIG) techniques and field observation in one section of the “Província Costeira do Rio Grande do Sul” between the Rio Grande and the São Gonçalo channels - resulted in a geomorphologic profile and mapping

  4. New multispectral MRI data fusion technique for white matter lesion segmentation: method and comparison with thresholding in FLAIR images

    International Nuclear Information System (INIS)

    Del C Valdes Hernandez, Maria; Ferguson, Karen J.; Chappell, Francesca M.; Wardlaw, Joanna M.

    2010-01-01

    Brain tissue segmentation by conventional threshold-based techniques may have limited accuracy and repeatability in older subjects. We present a new multispectral magnetic resonance (MR) image analysis approach for segmenting normal and abnormal brain tissue, including white matter lesions (WMLs). We modulated two 1.5T MR sequences in the red/green colour space and calculated the tissue volumes using minimum variance quantisation. We tested it on 14 subjects, mean age 73.3 ± 10 years, representing the full range of WMLs and atrophy. We compared the results of WML segmentation with those using FLAIR-derived thresholds, examined the effect of sampling location, WML amount and field inhomogeneities, and tested observer reliability and accuracy. FLAIR-derived thresholds were significantly affected by the location used to derive the threshold (P = 0.0004) and by WML volume (P = 0.0003), and had higher intra-rater variability than the multispectral technique (mean difference ± SD: 759 ± 733 versus 69 ± 326 voxels respectively). The multispectral technique misclassified 16 times fewer WMLs. Initial testing suggests that the multispectral technique is highly reproducible and accurate with the potential to be applied to routinely collected clinical MRI data. (orig.)

  5. Evaluation of non-invasive multispectral imaging as a tool for measuring the effect of systemic therapy in Kaposi sarcoma.

    Directory of Open Access Journals (Sweden)

    Jana M Kainerstorfer

    Full Text Available Diffuse multi-spectral imaging has been evaluated as a potential non-invasive marker of tumor response. Multi-spectral images of Kaposi sarcoma skin lesions were taken over the course of treatment, and blood volume and oxygenation concentration maps were obtained through principal component analysis (PCA of the data. These images were compared with clinical and pathological responses determined by conventional means. We demonstrate that cutaneous lesions have increased blood volume concentration and that changes in this parameter are a reliable indicator of treatment efficacy, differentiating responders and non-responders. Blood volume decreased by at least 20% in all lesions that responded by clinical criteria and increased in the two lesions that did not respond clinically. Responses as assessed by multi-spectral imaging also generally correlated with overall patient clinical response assessment, were often detectable earlier in the course of therapy, and are less subject to observer variability than conventional clinical assessment. Tissue oxygenation was more variable, with lesions often showing decreased oxygenation in the center surrounded by a zone of increased oxygenation. This technique could potentially be a clinically useful supplement to existing response assessment in KS, providing an early, quantitative, and non-invasive marker of treatment effect.

  6. Determining fast orientation changes of multi-spectral line cameras from the primary images

    Science.gov (United States)

    Wohlfeil, Jürgen

    2012-01-01

    Fast orientation changes of airborne and spaceborne line cameras cannot always be avoided. In such cases it is essential to measure them with high accuracy to ensure a good quality of the resulting imagery products. Several approaches exist to support the orientation measurement by using optical information received through the main objective/telescope. In this article an approach is proposed that allows the determination of non-systematic orientation changes between every captured line. It does not require any additional camera hardware or onboard processing capabilities but the payload images and a rough estimate of the camera's trajectory. The approach takes advantage of the typical geometry of multi-spectral line cameras with a set of linear sensor arrays for different spectral bands on the focal plane. First, homologous points are detected within the heavily distorted images of different spectral bands. With their help a connected network of geometrical correspondences can be built up. This network is used to calculate the orientation changes of the camera with the temporal and angular resolution of the camera. The approach was tested with an extensive set of aerial surveys covering a wide range of different conditions and achieved precise and reliable results.

  7. Airborne Thermal Infrared Multispectral Scanner (TIMS) images over disseminated gold deposits, Osgood Mountains, Humboldt County, Nevada

    Science.gov (United States)

    Krohn, M. Dennis

    1986-01-01

    The U.S. Geological Survey (USGS) acquired airborne Thermal Infrared Multispectral Scanner (TIMS) images over several disseminated gold deposits in northern Nevada in 1983. The aerial surveys were flown to determine whether TIMS data could depict jasperoids (siliceous replacement bodies) associated with the gold deposits. The TIMS data were collected over the Pinson and Getchell Mines in the Osgood Mountains, the Carlin, Maggie Creek, Bootstrap, and other mines in the Tuscarora Mountains, and the Jerritt Canyon Mine in the Independence Mountains. The TIMS data seem to be a useful supplement to conventional geochemical exploration for disseminated gold deposits in the western United States. Siliceous outcrops are readily separable in the TIMS image from other types of host rocks. Different forms of silicification are not readily separable, yet, due to limitations of spatial resolution and spectral dynamic range. Features associated with the disseminated gold deposits, such as the large intrusive bodies and fault structures, are also resolvable on TIMS data. Inclusion of high-resolution thermal inertia data would be a useful supplement to the TIMS data.

  8. Rotational multispectral fluorescence lifetime imaging and intravascular ultrasound: bimodal system for intravascular applications

    Science.gov (United States)

    Ma, Dinglong; Bec, Julien; Yankelevich, Diego R.; Gorpas, Dimitris; Fatakdawala, Hussain; Marcu, Laura

    2014-01-01

    Abstract. We report the development and validation of a hybrid intravascular diagnostic system combining multispectral fluorescence lifetime imaging (FLIm) and intravascular ultrasound (IVUS) for cardiovascular imaging applications. A prototype FLIm system based on fluorescence pulse sampling technique providing information on artery biochemical composition was integrated with a commercial IVUS system providing information on artery morphology. A customized 3-Fr bimodal catheter combining a rotational side-view fiberoptic and a 40-MHz IVUS transducer was constructed for sequential helical scanning (rotation and pullback) of tubular structures. Validation of this bimodal approach was conducted in pig heart coronary arteries. Spatial resolution, fluorescence detection efficiency, pulse broadening effect, and lifetime measurement variability of the FLIm system were systematically evaluated. Current results show that this system is capable of temporarily resolving the fluorescence emission simultaneously in multiple spectral channels in a single pullback sequence. Accurate measurements of fluorescence decay characteristics from arterial segments can be obtained rapidly (e.g., 20 mm in 5 s), and accurate co-registration of fluorescence and ultrasound features can be achieved. The current finding demonstrates the compatibility of FLIm instrumentation with in vivo clinical investigations and its potential to complement conventional IVUS during catheterization procedures. PMID:24898604

  9. Multispectral Imaging Analysis of Circulating Tumor Cells in Negatively Enriched Peripheral Blood Samples.

    Science.gov (United States)

    Miller, Brandon; Lustberg, Maryam; Summers, Thomas A; Chalmers, Jeffrey J

    2017-01-01

    A variety of biomarkers are present on cells in peripheral blood of patients with a variety of disorders, including solid tumor malignancies. While rare, characterization of these cells for specific protein levels with the advanced technology proposed, will lead to future validation studies of blood samples as "liquid biopsies" for the evaluation of disease status and therapeutic response. While circulating tumor cells (CTCs) have been isolated in the blood samples of patients with solid tumors, the exact role of CTCs as clinically useful predictive markers is still debated. Current commercial technology has significant bias in that a positive selection technology is used that preassumes specific cell surface markers (such as EpCAM) are present on CTCs. However, CTCs with low EpCAM expression have been experimentally demonstrated to be more likely to be missed by this method. In contrast, this application uses a previously developed, technology that performs a purely negative enrichment methodology on peripheral blood, yielding highly enriched blood samples that contain CTCs as well as other, undefined cell types. The focus of this contribution is the use of multispectral imaging of epifluorescent, microscopic images of these enriched cells in order to help develop clinically relevant liquid biopsies from peripheral blood samples.

  10. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

  11. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Directory of Open Access Journals (Sweden)

    Liang Lu

    2018-03-01

    Full Text Available Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

  12. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Science.gov (United States)

    Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

    2018-01-01

    Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

  13. Considerations and methods for the changes detection using satellite images in the Municipality of Paipa

    International Nuclear Information System (INIS)

    Riano M, Orlando

    2002-01-01

    In this article the considerations and methods are presented for the changes detection in the earth covering, using two images Landsat TM of different dates for an area of the municipality of Paipa, Boyaca. The changes detection has become an important application of the multi-spectral data and multi-temporal of the satellites programs for studies of natural resources Landsat, TM and Spot, in such a way that is possible to determine the types and extension of the changes that are given in the environment. To carry out this process some digital techniques they have been used for changes detection, such as: images superposition, differences between images and analysis of main components. These techniques allowed to observe and to analyze changes in the use and covering of the earth in this municipality

  14. INTRODUCING A LOW-COST MINI-UAV FOR THERMAL- AND MULTISPECTRAL-IMAGING

    Directory of Open Access Journals (Sweden)

    J. Bendig

    2012-07-01

    100 m, the camera's image covers an area of approx. 50 by 40 m. The sensor's resolution is 160 x 120 pixel and the field of view is 28° (H x 21° (V. According to the producer, absolute accuracy for temperature is ±1 °C and the thermal sensitivity is >0.1 K. Additionally, the MK-Okto is equipped with Tetracam's Mini MCA. The Mini MCA in our study is a four band multispectral imaging system. Total weight is 700 g and spectral characteristics can be modified by filters between 400 and 1000 nm. In this study, three bands with a width of 10 nm (green: 550 nm, red: 671 nm, NIR1: 800 nm and one band of 20 nm width (NIR2: 950 nm have been used. Even so the MK-Okto is able to carry both sensors at the same time, the imaging systems were used separately for this contribution. First results of a combined thermal- and multispectral MK-Okto campaign in 2011 are presented and evaluated for a sugarbeet field experiment examining pathogens and drought stress.

  15. Introducing a Low-Cost Mini-Uav for - and Multispectral-Imaging

    Science.gov (United States)

    Bendig, J.; Bolten, A.; Bareth, G.

    2012-07-01

    's image covers an area of approx. 50 by 40 m. The sensor's resolution is 160 x 120 pixel and the field of view is 28° (H) x 21° (V). According to the producer, absolute accuracy for temperature is ±1 °C and the thermal sensitivity is >0.1 K. Additionally, the MK-Okto is equipped with Tetracam's Mini MCA. The Mini MCA in our study is a four band multispectral imaging system. Total weight is 700 g and spectral characteristics can be modified by filters between 400 and 1000 nm. In this study, three bands with a width of 10 nm (green: 550 nm, red: 671 nm, NIR1: 800 nm) and one band of 20 nm width (NIR2: 950 nm) have been used. Even so the MK-Okto is able to carry both sensors at the same time, the imaging systems were used separately for this contribution. First results of a combined thermal- and multispectral MK-Okto campaign in 2011 are presented and evaluated for a sugarbeet field experiment examining pathogens and drought stress.

  16. Detection of jet contrails from satellite images

    Science.gov (United States)

    Meinert, Dieter

    1994-02-01

    In order to investigate the influence of modern technology on the world climate it is important to have automatic detection methods for man-induced parameters. In this case the influence of jet contrails on the greenhouse effect shall be investigated by means of images from polar orbiting satellites. Current methods of line recognition and amplification cannot distinguish between contrails and rather sharp edges of natural cirrus or noise. They still rely on human control. Through the combination of different methods from cloud physics, image comparison, pattern recognition, and artificial intelligence we try to overcome this handicap. Here we will present the basic methods applied to each image frame, and list preliminary results derived this way.

  17. GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    Catherine Mering

    2011-05-01

    Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

  18. An investigation of multispectral imaging for the mapping of pigments in paintings

    Science.gov (United States)

    Zhao, Yonghui; Berns, Roy S.; Taplin, Lawrence A.; Coddington, James

    2008-02-01

    Compared with colorimetric imaging, multispectral imaging has the advantage of retrieving spectral reflectance factor of each pixel of a painting. Using this spectral information, pigment mapping is concerned with decomposing the spectrum into its constituent pigments and their relative contributions. The output of pigment mapping is a series of spatial concentration maps of the pigments comprising the painting. This approach was used to study Vincent van Gogh's The Starry Night. The artist's palette was approximated using ten oil pigments, selected from a large database of pigments used in oil paintings and a priori analytical research on one of his self portraits, executed during the same time period. The pigment mapping was based on single-constant Kubelka-Munk theory. It was found that the region of blue sky where the stars were located contained, predominantly, ultramarine blue while the swirling sky and region surrounding the moon contained, predominantly, cobalt blue. Emerald green, used in light bluish-green brushstrokes surrounding the moon, was not used to create the dark green in the cypresses. A measurement of lead white from Georges Seurat's La Grande Jatte was used as the white when mapping The Starry Night. The absorption and scattering properties of this white were replaced with a modern dispersion of lead white in linseed oil and used to simulate the painting's appearance before the natural darkening and yellowing of lead white oil paint. Pigment mapping based on spectral imaging was found to be a viable and practical approach for analyzing pigment composition, providing new insight into an artist's working method, the possibility for aiding in restorative inpainting, and lighting design.

  19. Multispectral Enhancement Method to Increase the Visual Differences of Tissue Structures in Stained Histopathology Images

    Directory of Open Access Journals (Sweden)

    Pinky A. Bautista

    2012-01-01

    Full Text Available In this paper we proposed a multispectral enhancement scheme in which the spectral colors of the stained tissue-structure of interest and its background can be independently modified by the user to further improve their visualization and color discrimination. The colors of the background objects are modified by transforming their N-band spectra through an NxN transformation matrix, which is derived by mapping the representative samples of their original spectra to the spectra of their target colors using least mean square method. On the other hand, the color of the tissue structure of interest is modified by modulating the transformed spectra with the sum of the pixel’s spectral residual-errors at specific bands weighted through an NxN weighting matrix; the spectral error is derived by taking the difference between the pixel’s original spectrum and its reconstructed spectrum using the first M dominant principal component vectors in principal component analysis. Promising results were obtained on the visualization of the collagen fiber and the non-collagen tissue structures, e.g., nuclei, cytoplasm and red blood cells (RBC, in a hematoxylin and eosin (H&E stained image.

  20. Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA

  1. Geometric Calibration and Radiometric Correction of the Maia Multispectral Camera

    Science.gov (United States)

    Nocerino, E.; Dubbini, M.; Menna, F.; Remondino, F.; Gattelli, M.; Covi, D.

    2017-10-01

    Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper.

  2. FFT-enhanced IHS transform method for fusing high-resolution satellite images

    Science.gov (United States)

    Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

    2007-01-01

    Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

  3. Medical image transmission via communication satellite: evaluation of ultrasonographic images.

    Science.gov (United States)

    Suzuki, H; Horikoshi, H; Shiba, H; Shimamoto, S

    1996-01-01

    As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment.

  4. Low SWaP multispectral sensors using dichroic filter arrays

    Science.gov (United States)

    Dougherty, John; Varghese, Ron

    2015-06-01

    The benefits of multispectral imaging are well established in a variety of applications including remote sensing, authentication, satellite and aerial surveillance, machine vision, biomedical, and other scientific and industrial uses. However, many of the potential solutions require more compact, robust, and cost-effective cameras to realize these benefits. The next generation of multispectral sensors and cameras needs to deliver improvements in size, weight, power, portability, and spectral band customization to support widespread deployment for a variety of purpose-built aerial, unmanned, and scientific applications. A novel implementation uses micro-patterning of dichroic filters1 into Bayer and custom mosaics, enabling true real-time multispectral imaging with simultaneous multi-band image acquisition. Consistent with color image processing, individual spectral channels are de-mosaiced with each channel providing an image of the field of view. This approach can be implemented across a variety of wavelength ranges and on a variety of detector types including linear, area, silicon, and InGaAs. This dichroic filter array approach can also reduce payloads and increase range for unmanned systems, with the capability to support both handheld and autonomous systems. Recent examples and results of 4 band RGB + NIR dichroic filter arrays in multispectral cameras are discussed. Benefits and tradeoffs of multispectral sensors using dichroic filter arrays are compared with alternative approaches - including their passivity, spectral range, customization options, and scalable production.

  5. Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

    Science.gov (United States)

    Kemper, Thomas; Gueguen, Lionel; Soille, Pierre

    2012-06-01

    The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

  6. ASTER 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  7. MODIS 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  8. Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

    Science.gov (United States)

    Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

    2018-02-01

    This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

  9. Multispectral imaging system based on laser-induced fluorescence for security applications

    Science.gov (United States)

    Caneve, L.; Colao, F.; Del Franco, M.; Palucci, A.; Pistilli, M.; Spizzichino, V.

    2016-10-01

    The development of portable sensors for fast screening of crime scenes is required to reduce the number of evidences useful to be collected, optimizing time and resources. Laser based spectroscopic techniques are good candidates to this scope due to their capability to operate in field, in remote and rapid way. In this work, the prototype of a multispectral imaging LIF (Laser Induced Fluorescence) system able to detect evidence of different materials on large very crowded and confusing areas at distances up to some tens of meters will be presented. Data collected as both 2D fluorescence images and LIF spectra are suitable to the identification and the localization of the materials of interest. A reduced scan time, preserving at the same time the accuracy of the results, has been taken into account as a main requirement in the system design. An excimer laser with high energy and repetition rate coupled to a gated high sensitivity ICCD assures very good performances for this purpose. Effort has been devoted to speed up the data processing. The system has been tested in outdoor and indoor real scenarios and some results will be reported. Evidence of the plastics polypropylene (PP) and polyethilene (PE) and polyester have been identified and their localization on the examined scenes has been highlighted through the data processing. By suitable emission bands, the instrument can be used for the rapid detection of other material classes (i.e. textiles, woods, varnishes). The activities of this work have been supported by the EU-FP7 FORLAB project (Forensic Laboratory for in-situ evidence analysis in a post blast scenario).

  10. Polar-Orbiting Satellite (POES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...

  11. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete

    2009-01-01

    -based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters......Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy...

  12. A comparison of dimension reduction methods with application to multi-spectral images of sand used in concrete

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Hansen, M. E.; Ersbøll, Bjarne Kjær

    2010-01-01

    This paper presents a comparison of dimension reduction methods based on a novel machine vision application for estimating moisture content in sand used to make concrete. For the application in question it is very important to know the moisture content of the sand so as to ensure good-quality...... sand types were examined with 20-60 images for each type. To reduce the amount of data, features were extracted from the multi-spectral images; the features were summary statistics on single bands and pairs of bands as well as morphological summaries. The number of features (2,016) is high in relation...

  13. Dual light-emitting diode-based multichannel microscopy for whole-slide multiplane, multispectral and phase imaging.

    Science.gov (United States)

    Liao, Jun; Wang, Zhe; Zhang, Zibang; Bian, Zichao; Guo, Kaikai; Nambiar, Aparna; Jiang, Yutong; Jiang, Shaowei; Zhong, Jingang; Choma, Michael; Zheng, Guoan

    2018-02-01

    We report the development of a multichannel microscopy for whole-slide multiplane, multispectral and phase imaging. We use trinocular heads to split the beam path into 6 independent channels and employ a camera array for parallel data acquisition, achieving a maximum data throughput of approximately 1 gigapixel per second. To perform single-frame rapid autofocusing, we place 2 near-infrared light-emitting diodes (LEDs) at the back focal plane of the condenser lens to illuminate the sample from 2 different incident angles. A hot mirror is used to direct the near-infrared light to an autofocusing camera. For multiplane whole-slide imaging (WSI), we acquire 6 different focal planes of a thick specimen simultaneously. For multispectral WSI, we relay the 6 independent image planes to the same focal position and simultaneously acquire information at 6 spectral bands. For whole-slide phase imaging, we acquire images at 3 focal positions simultaneously and use the transport-of-intensity equation to recover the phase information. We also provide an open-source design to further increase the number of channels from 6 to 15. The reported platform provides a simple solution for multiplexed fluorescence imaging and multimodal WSI. Acquiring an instant focal stack without z-scanning may also enable fast 3-dimensional dynamic tracking of various biological samples. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

    Science.gov (United States)

    Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

    2018-03-01

    Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

  15. Automated melanoma detection with a novel multispectral imaging system: results of a prospective study

    International Nuclear Information System (INIS)

    Tomatis, Stefano; Carrara, Mauro; Bono, Aldo; Bartoli, Cesare; Lualdi, Manuela; Tragni, Gabrina; Colombo, Ambrogio; Marchesini, Renato

    2005-01-01

    The aim of this research was to evaluate the performance of a new spectroscopic system in the diagnosis of melanoma. This study involves a consecutive series of 1278 patients with 1391 cutaneous pigmented lesions including 184 melanomas. In an attempt to approach the 'real world' of lesion population, a further set of 1022 not excised clinically reassuring lesions was also considered for analysis. Each lesion was imaged in vivo by a multispectral imaging system. The system operates at wavelengths between 483 and 950 nm by acquiring 15 images at equally spaced wavelength intervals. From the images, different lesion descriptors were extracted related to the colour distribution and morphology of the lesions. Data reduction techniques were applied before setting up a neural network classifier designed to perform automated diagnosis. The data set was randomly divided into three sets: train (696 lesions, including 90 melanomas) and verify (348 lesions, including 53 melanomas) for the instruction of a proper neural network, and an independent test set (347 lesions, including 41 melanomas). The neural network was able to discriminate between melanomas and non-melanoma lesions with a sensitivity of 80.4% and a specificity of 75.6% in the 1391 histologized cases data set. No major variations were found in classification scores when train, verify and test subsets were separately evaluated. Following receiver operating characteristic (ROC) analysis, the resulting area under the curve was 0.85. No significant differences were found among areas under train, verify and test set curves, supporting the good network ability to generalize for new cases. In addition, specificity and area under ROC curve increased up to 90% and 0.90, respectively, when the additional set of 1022 lesions without histology was added to the test set. Our data show that performance of an automated system is greatly population dependent, suggesting caution in the comparison with results reported in the

  16. AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

  17. LANDSAT 8 MULTISPECTRAL AND PANSHARPENED IMAGERY PROCESSING ON THE STUDY OF CIVIL ENGINEERING ISSUES

    Directory of Open Access Journals (Sweden)

    M. A. Lazaridou

    2016-06-01

    Full Text Available Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM – Landsat 8 is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion – pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  18. Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

    Science.gov (United States)

    Lazaridou, M. A.; Karagianni, A. Ch.

    2016-06-01

    Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  19. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Bamyan mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  20. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ahankashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008, 2009, 2010),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this

  1. Automated Recognition of Vegetation and Water Bodies on the Territory of Megacities in Satellite Images of Visible and IR Bands

    Science.gov (United States)

    Mozgovoy, Dmitry k.; Hnatushenko, Volodymyr V.; Vasyliev, Volodymyr V.

    2018-04-01

    Vegetation and water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. A methodology of automated recognition of vegetation and water bodies on the territory of megacities in satellite images of sub-meter spatial resolution of the visible and IR bands is proposed. By processing multispectral images from the satellite SuperView-1A, vector layers of recognized plant and water objects were obtained. Analysis of the results of image processing showed a sufficiently high accuracy of the delineation of the boundaries of recognized objects and a good separation of classes. The developed methodology provides a significant increase of the efficiency and reliability of updating maps of large cities while reducing financial costs. Due to the high degree of automation, the proposed methodology can be implemented in the form of a geo-information web service functioning in the interests of a wide range of public services and commercial institutions.

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

  3. Imaging the distribution of photoswitchable probes with temporally-unmixed multispectral optoacoustic tomography

    Science.gov (United States)

    Deán-Ben, X. Luís.; Stiel, Andre C.; Jiang, Yuanyuan; Ntziachristos, Vasilis; Westmeyer, Gil G.; Razansky, Daniel

    2016-03-01

    Synthetic and genetically encoded chromo- and fluorophores have become indispensable tools for biomedical research enabling a myriad of applications in imaging modalities based on biomedical optics. The versatility offered by the optoacoustic (photoacoustic) contrast mechanism enables to detect signals from any substance absorbing light, and hence these probes can be used as optoacoustic contrast agents. While contrast versatility generally represents an advantage of optoacoustics, the strong background signal generated by light absorption in endogeneous chromophores hampers the optoacoustic capacity to detect a photo-absorbing agent of interest. Increasing the optoacoustic sensitivity is then determined by the capability to differentiate specific features of such agent. For example, multispectral optoacoustic tomography (MSOT) exploits illuminating the tissue at multiple optical wavelengths to spectrally resolve (unmix) the contribution of different chromophores. Herein, we present an alternative approach to enhance the sensitivity and specificity in the detection of optoacoustic contrast agents. This is achieved with photoswitchable probes that change optical absorption upon illumination with specific optical wavelengths. Thereby, temporally unmixed MSOT (tuMSOT) is based on photoswitching the compounds according to defined schedules to elicit specific time-varying optoacoustic signals, and then use temporal unmixing algorithms to locate the contrast agent based on their particular temporal profile. The photoswitching kinetics is further affected by light intensity, so that tuMSOT can be employed to estimate the light fluence distribution in a biological sample. The performance of the method is demonstrated herein with the reversibly switchable fluorescent protein Dronpa and its fast-switching fatigue resistant variant Dronpa-M159T.

  4. Robust and adaptive band-to-band image transform of UAS miniature multi-lens multispectral camera

    Science.gov (United States)

    Jhan, Jyun-Ping; Rau, Jiann-Yeou; Haala, Norbert

    2018-03-01

    Utilizing miniature multispectral (MS) or hyperspectral (HS) cameras by mounting them on an Unmanned Aerial System (UAS) has the benefits of convenience and flexibility to collect remote sensing imagery for precision agriculture, vegetation monitoring, and environment investigation applications. Most miniature MS cameras adopt a multi-lens structure to record discrete MS bands of visible and invisible information. The differences in lens distortion, mounting positions, and viewing angles among lenses mean that the acquired original MS images have significant band misregistration errors. We have developed a Robust and Adaptive Band-to-Band Image Transform (RABBIT) method for dealing with the band co-registration of various types of miniature multi-lens multispectral cameras (Mini-MSCs) to obtain band co-registered MS imagery for remote sensing applications. The RABBIT utilizes modified projective transformation (MPT) to transfer the multiple image geometry of a multi-lens imaging system to one sensor geometry, and combines this with a robust and adaptive correction (RAC) procedure to correct several systematic errors and to obtain sub-pixel accuracy. This study applies three state-of-the-art Mini-MSCs to evaluate the RABBIT method's performance, specifically the Tetracam Miniature Multiple Camera Array (MiniMCA), Micasense RedEdge, and Parrot Sequoia. Six MS datasets acquired at different target distances and dates, and locations are also applied to prove its reliability and applicability. Results prove that RABBIT is feasible for different types of Mini-MSCs with accurate, robust, and rapid image processing efficiency.

  5. Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Elizabeth J. Botha

    2016-05-01

    Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

  6. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of the Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  7. Mosaic of 2m bathymetry derived from multispectral IKONOS World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  8. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

  9. Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

    Science.gov (United States)

    Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

    2018-01-01

    The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

  10. Review and Implementation of the Emerging CCSDS Recommended Standard for Multispectral and Hyperspectral Lossless Image Coding

    Science.gov (United States)

    Sanchez, Jose Enrique; Auge, Estanislau; Santalo, Josep; Blanes, Ian; Serra-Sagrista, Joan; Kiely, Aaron

    2011-01-01

    A new standard for image coding is being developed by the MHDC working group of the CCSDS, targeting onboard compression of multi- and hyper-spectral imagery captured by aircraft and satellites. The proposed standard is based on the "Fast Lossless" adaptive linear predictive compressor, and is adapted to better overcome issues of onboard scenarios. In this paper, we present a review of the state of the art in this field, and provide an experimental comparison of the coding performance of the emerging standard in relation to other state-of-the-art coding techniques. Our own independent implementation of the MHDC Recommended Standard, as well as of some of the other techniques, has been used to provide extensive results over the vast corpus of test images from the CCSDS-MHDC.

  11. Demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data

    Science.gov (United States)

    Butera, M. K.

    1979-01-01

    The success of remotely mapping wetland vegetation of the southwestern coast of Florida is examined. A computerized technique to process aircraft and LANDSAT multispectral scanner data into vegetation classification maps was used. The cost effectiveness of this mapping technique was evaluated in terms of user requirements, accuracy, and cost. Results indicate that mangrove communities are classified most cost effectively by the LANDSAT technique, with an accuracy of approximately 87 percent and with a cost of approximately 3 cent per hectare compared to $46.50 per hectare for conventional ground survey methods.

  12. Detecting aircrafts from satellite images using saliency and conical ...

    Indian Academy of Sciences (India)

    Samik Banerjee

    automatically detect all kinds of interesting targets in satellite images. .... which is used for text and image categorization, has been also introduced for object ...... 3.4 GHz processor, 32 GB RAM and Windows 7 (64 bit). Operating System. 6.

  13. Characteristics of Xanthosoma sagittifolium roots during cooking, using physicochemical analysis, uniaxial compression, multispectral imaging and low field NMR spectroscopy

    DEFF Research Database (Denmark)

    Boakye, Abena Achiaa; Gudjónsdóttir, María; Skytte, Jacob Lercke

    2017-01-01

    and white varieties of cocoyam roots were thus analysed by low field nuclear magnetic resonance relaxometry, multispectral imaging, uniaxial compression testing, and relevant physicochemical analysis in the current study. Both varieties had similar dry matter content, as well as physical and mechanical...... of that spectral region for rapid analysis of dry matter and water content of the roots. The small, but significant differences in the structural and gelatinization characteristics of the two varieties indicated that they may not be equally suited for further processing, e.g. to flours or starches. Processors thus...

  14. The Application of Chinese High-Spatial Remote Sensing Satellite Image in Land Law Enforcement Information Extraction

    Science.gov (United States)

    Wang, N.; Yang, R.

    2018-04-01

    Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.

  15. Use of multispectral satellite remote sensing to assess mixing of suspended sediment downstream of large river confluences

    Science.gov (United States)

    Umar, M.; Rhoads, Bruce L.; Greenberg, Jonathan A.

    2018-01-01

    Although past work has noted that contrasts in turbidity often are detectable on remotely sensed images of rivers downstream from confluences, no systematic methodology has been developed for assessing mixing over distance of confluent flows with differing surficial suspended sediment concentrations (SSSC). In contrast to field measurements of mixing below confluences, satellite remote-sensing can provide detailed information on spatial distributions of SSSC over long distances. This paper presents a methodology that uses remote-sensing data to estimate spatial patterns of SSSC downstream of confluences along large rivers and to determine changes in the amount of mixing over distance from confluences. The method develops a calibrated Random Forest (RF) model by relating training SSSC data from river gaging stations to derived spectral indices for the pixels corresponding to gaging-station locations. The calibrated model is then used to predict SSSC values for every river pixel in a remotely sensed image, which provides the basis for mapping of spatial variability in SSSCs along the river. The pixel data are used to estimate average surficial values of SSSC at cross sections spaced uniformly along the river. Based on the cross-section data, a mixing metric is computed for each cross section. The spatial pattern of change in this metric over distance can be used to define rates and length scales of surficial mixing of suspended sediment downstream of a confluence. This type of information is useful for exploring the potential influence of various controlling factors on mixing downstream of confluences, for evaluating how mixing in a river system varies over time and space, and for determining how these variations influence water quality and ecological conditions along the river.

  16. Multispectral UV imaging for fast and non-destructive quality control of chemical and physical tablet attributes

    DEFF Research Database (Denmark)

    Klukkert, Marten; Wu, Jian X; Rantanen, Jukka

    2016-01-01

    Monitoring of tablet quality attributes in direct vicinity of the production process requires analytical techniques that allow fast, non-destructive, and accurate tablet characterization. The overall objective of this study was to investigate the applicability of multispectral UV imaging...... as a reliable, rapid technique for estimation of the tablet API content and tablet hardness, as well as determination of tablet intactness and the tablet surface density profile. One of the aims was to establish an image analysis approach based on multivariate image analysis and pattern recognition to evaluate...... the potential of UV imaging for automatized quality control of tablets with respect to their intactness and surface density profile. Various tablets of different composition and different quality regarding their API content, radial tensile strength, intactness, and surface density profile were prepared using...

  17. Mapping within-field variations of soil organic carbon content using UAV multispectral visible near-infrared images

    Science.gov (United States)

    Gilliot, Jean-Marc; Vaudour, Emmanuelle; Michelin, Joël

    2016-04-01

    This study was carried out in the framework of the PROSTOCK-Gessol3 project supported by the French Environment and Energy Management Agency (ADEME), the TOSCA-PLEIADES-CO project of the French Space Agency (CNES) and the SOERE PRO network working on environmental impacts of Organic Waste Products recycling on field crops at long time scale. The organic matter is an important soil fertility parameter and previous studies have shown the potential of spectral information measured in the laboratory or directly in the field using field spectro-radiometer or satellite imagery to predict the soil organic carbon (SOC) content. This work proposes a method for a spatial prediction of bare cultivated topsoil SOC content, from Unmanned Aerial Vehicle (UAV) multispectral imagery. An agricultural plot of 13 ha, located in the western region of Paris France, was analysed in April 2013, shortly before sowing while it was still bare soil. Soils comprised haplic luvisols, rendzic cambisols and calcaric or colluvic cambisols. The UAV platform used was a fixed wing provided by Airinov® flying at an altitude of 150m and was equipped with a four channels multispectral visible near-infrared camera MultiSPEC 4C® (550nm, 660nm, 735 nm and 790 nm). Twenty three ground control points (GCP) were sampled within the plot according to soils descriptions. GCP positions were determined with a centimetric DGPS. Different observations and measurements were made synchronously with the drone flight: soil surface description, spectral measurements (with ASD FieldSpec 3® spectroradiometer), roughness measurements by a photogrammetric method. Each of these locations was sampled for both soil standard physico-chemical analysis and soil water content. A Structure From Motion (SFM) processing was done from the UAV imagery to produce a 15 cm resolution multispectral mosaic using the Agisoft Photoscan® software. The SOC content was modelled by partial least squares regression (PLSR) between the

  18. THERMAL AND VISIBLE SATELLITE IMAGE FUSION USING WAVELET IN REMOTE SENSING AND SATELLITE IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    A. H. Ahrari

    2017-09-01

    Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.

  19. Using Multispectral False Color Imaging to Characterize Tropical Cyclone Structure and Environment

    Science.gov (United States)

    Cossuth, J.; Bankert, R.; Richardson, K.; Surratt, M. L.

    2016-12-01

    The Naval Research Laboratory's (NRL) tropical cyclone (TC) web page (http://www.nrlmry.navy.mil/TC.html) has provided nearly two decades of near real-time access to TC-centric images and products by TC forecasters and enthusiasts around the world. Particularly, microwave imager and sounder information that is featured on this site provides crucial internal storm structure information by allowing users to perceive hydrometeor structure, providing key details beyond cloud top information provided by visible and infrared channels. Towards improving TC analysis techniques and helping advance the utility of the NRL TC webpage resource, new research efforts are presented. This work demonstrates results as well as the methodology used to develop new automated, objective satellite-based TC structure and intensity guidance and enhanced data fusion imagery products that aim to bolster and streamline TC forecast operations. This presentation focuses on the creation and interpretation of false color RGB composite imagery that leverages the different emissive and scattering properties of atmospheric ice, liquid, and vapor water as well as ocean surface roughness as seen by microwave radiometers. Specifically, a combination of near-realtime data and a standardized digital database of global TCs in microwave imagery from 1987-2012 is employed as a climatology of TC structures. The broad range of TC structures, from pinhole eyes through multiple eyewall configurations, is characterized as resolved by passive microwave sensors. The extraction of these characteristic features from historical data also lends itself to statistical analysis. For example, histograms of brightness temperature distributions allows a rigorous examination of how structural features are conveyed in image products, allowing a better representation of colors and breakpoints as they relate to physical features. Such climatological work also suggests steps to better inform the near-real time application of

  20. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be

  4. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  6. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match

  7. Virtual Satellite Construction and Application for Image Classification

    International Nuclear Information System (INIS)

    Su, W G; Su, F Z; Zhou, C H

    2014-01-01

    Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively

  8. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA

  9. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  10. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  11. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  12. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  13. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

  14. Multispectral image analysis of the Palo Duro Basin, Texas: Final report

    International Nuclear Information System (INIS)

    Andre, C.G.

    1986-09-01

    The objectives of this remote sensing study of the Palo Duro Basin are to: (1) detect the surface expression of regional subsurface structure; (2) locate previously unrecognized fractures; (3) interpret the data in terms of the geologic history of the Palo Duro Basin. Linear and circular surface features were mapped from Landsat 4 Thematic Mapper and NOAA-7 Advanced Very High Resolution Radiometer digital images of visible, near-infrared and thermal infrared bands. The density and orientation of features mapped are shown to be related to geological features, such as faults, structural arches, paleoerosion topography and salt dissolution zones. The approximate area covered by the three 185 km /times/ 170 km Thematic Mapper images studied extends southward from the Canadian River Breaks to the Sand Hills and eastward from the western Mountains in Oklahoma. The day and night thermal infrared images from the NOAA-7 satellite encompass an area that includes the northern half of Texas and most of the surrounding states to the east, west and north. 4 refs

  15. Low-cost multispectral imaging for remote sensing of lettuce health

    Science.gov (United States)

    Ren, David D. W.; Tripathi, Siddhant; Li, Larry K. B.

    2017-01-01

    In agricultural remote sensing, unmanned aerial vehicle (UAV) platforms offer many advantages over conventional satellite and full-scale airborne platforms. One of the most important advantages is their ability to capture high spatial resolution images (1-10 cm) on-demand and at different viewing angles. However, UAV platforms typically rely on the use of multiple cameras, which can be costly and difficult to operate. We present the development of a simple low-cost imaging system for remote sensing of crop health and demonstrate it on lettuce (Lactuca sativa) grown in Hong Kong. To identify the optimal vegetation index, we recorded images of both healthy and unhealthy lettuce, and used them as input in an expectation maximization cluster analysis with a Gaussian mixture model. Results from unsupervised and supervised clustering show that, among four widely used vegetation indices, the blue wide-dynamic range vegetation index is the most accurate. This study shows that it is readily possible to design and build a remote sensing system capable of determining the health status of lettuce at a reasonably low cost (lettuce growers.

  16. Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei

    Science.gov (United States)

    Seutloali, Khoboso E.; Dube, Timothy; Mutanga, Onisimo

    2017-08-01

    Soil erosion is increasingly recognised as the principal cause of land degradation, loss of agricultural land area and siltation of surrounding water waterbodies. Accurate and up-to-date soil erosion mapping is key in understanding its severity if these negative impacts are to be minimised and affected areas rehabilitated. The aim of this work was to map the severity of soil erosion, based on the 30-m Landsat series multispectral satellite data in the former South African homelands of Transkei between the year 1994 and 2010. Further, the study assessed if the observed soil erosion trends and morphology that existed in this area could be explained by biophysical factors (i.e. slope, stream erosivity, topographic wetness index) retrieved from the 30-m ASTER Digital Elevation Model (DEM). The results of this study indicate that the Transkei region experiences varying erosion levels from moderate to very severe. The large portion of the land area under the former homelands was largely affected by rill erosion with approximately 74% occurring in the year 1984 and 54% in 2010. The results also revealed specific thresholds of soil erosion drivers. These include steeper areas (≥30°), high stream power index greater than 2.0 (stream erosivity), relatively lower vegetation cover (≤15%) and low topographic wetness index (≤5%). The results of this work demonstrate the severity of soil erosion in the Southern African former homelands of Transkei for the year 1984 and 2010. Additionally, this work has demonstrated the significance of the 30-m Landsat multispectral sensor in examining soil erosion occurrence at a regional scale where in-depth field work still remains a challenging task.

  17. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: Chapter DD in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such

  18. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: Chapter EE in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image

  19. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  20. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  4. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

  6. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  7. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  8. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  9. The best printing methods to print satellite images

    OpenAIRE

    G.A. Yousif; R.Sh. Mohamed

    2011-01-01

    Printing systems operate in general as a system of color its color scale is limited as compared with the system color satellite images. Satellite image is building from very small cell named pixel, which represents the picture element and the unity of color when the image is displayed on the screen, this unit becomes lesser in size and called screen point. This unit posseses different size and shape from the method of printing to another, depending on the output resolution, tools and material...

  10. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

  11. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

  12. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  13. Satellite Image Classification of Building Damages Using Airborne and Satellite Image Samples in a Deep Learning Approach

    Science.gov (United States)

    Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

    2018-05-01

    The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image

  14. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  15. Optical design of an optical coherence tomography and multispectral fluorescence imaging endoscope to detect early stage ovarian cancer

    Science.gov (United States)

    Tate, Tyler; Keenan, Molly; Swan, Elizabeth; Black, John; Utzinger, Urs; Barton, Jennifer

    2014-12-01

    The five year survival rate for ovarian cancer is over 90% if early detection occurs, yet no effective early screening method exists. We have designed and are constructing a dual modality Optical Coherence Tomography (OCT) and Multispectral Fluorescence Imaging (MFI) endoscope to optically screen the Fallopian tube and ovary for early stage cancer. The endoscope reaches the ovary via the natural pathway of the vagina, cervix, uterus and Fallopian tube. In order to navigate the Fallopian tube the endoscope must have an outer diameter of 600 μm, be highly flexible, steerable, tracking and nonperforating. The imaging systems consists of six optical subsystems, two from OCT and four from MFI. The optical subsystems have independent and interrelated design criteria. The endoscope will be tested on realistic tissue models and ex vivo tissue to prove feasibility of future human trials. Ultimately the project aims to provide women the first effective ovarian cancer screening technique.

  16. Automated object-based classification of rain-induced landslides with VHR multispectral images in Madeira Island

    Science.gov (United States)

    Heleno, S.; Matias, M.; Pina, P.; Sousa, A. J.

    2015-09-01

    A method for semi-automatic landslide detection, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a Support Vector Machine classifier on a GeoEye-1 multispectral image, sensed 3 days after the major damaging landslide event that occurred in Madeira island (20 February 2010), with a pre-event LIDAR Digital Elevation Model. The testing is developed in a 15 km2-wide study area, where 95 % of the landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier east facing-slopes.

  17. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

    Science.gov (United States)

    Heleno, Sandra; Matias, Magda; Pina, Pedro; Sousa, António Jorge

    2016-04-01

    A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area, where 95 % of the number of landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area, with commission errors below 26 % and omission errors below 24 %. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier, east-facing slopes.

  18. Multispectral imaging based on a Smartphone with an external C-MOS camera for detection of seborrheic dermatitis on the scalp

    Science.gov (United States)

    Kim, Manjae; Kim, Sewoong; Hwang, Minjoo; Kim, Jihun; Je, Minkyu; Jang, Jae Eun; Lee, Dong Hun; Hwang, Jae Youn

    2017-02-01

    To date, the incident rates of various skin diseases have increased due to hereditary and environmental factors including stress, irregular diet, pollution, etc. Among these skin diseases, seborrheic dermatitis and psoriasis are a chronic/relapsing dermatitis involving infection and temporary alopecia. However, they typically exhibit similar symptoms, thus resulting in difficulty in discrimination between them. To prevent their associated complications and appropriate treatments for them, it is crucial to discriminate between seborrheic dermatitis and psoriasis with high specificity and sensitivity and further continuously/quantitatively to monitor the skin lesions during their treatment at other locations besides a hospital. Thus, we here demonstrate a mobile multispectral imaging system connected to a smartphone for selfdiagnosis of seborrheic dermatitis and further discrimination between seborrheic dermatitis and psoriasis on the scalp, which is the more challenging case. Using the system developed, multispectral imaging and analysis of seborrheic dermatitis and psoriasis on the scalp was carried out. It was here found that the spectral signatures of seborrheic dermatitis and psoriasis were discernable and thus seborrheic dermatitis on the scalp could be distinguished from psoriasis by using the system. In particular, the smartphone-based multispectral imaging and analysis moreover offered better discrimination between seborrheic dermatitis and psoriasis than the RGB imaging and analysis. These results suggested that the multispectral imaging system based on a smartphone has the potential for self-diagnosis of seborrheic dermatitis with high portability and specificity.

  19. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

    2017-03-01

    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  20. Detection of live larvae in cocoons of Bathyplectes curculionis (Hymenoptera Ichneumonidae) using visible/near-infrared multispectral imaging

    DEFF Research Database (Denmark)

    Shrestha, Santosh; Topbjerg, Henrik Bak; Ytting, Nanna Karkov

    2018-01-01

    BACKGROUND: The multispectral (MS) imaging system is a non-destructive method with potential to reduce the labour and time required for quality control in the production of beneficial arthropods such as the parasitoid Bathyplectes curculionis. In Denmark, a project is being undertaken that focuse...

  1. Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

  2. Kansas Satellite Image Database (KSID) 2004-2005

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...

  3. Velocity estimation of an airplane through a single satellite image

    Institute of Scientific and Technical Information of China (English)

    Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

    2012-01-01

    The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

  4. Identification of a murine erythroblast subpopulation enriched in enucleating events by multi-spectral imaging flow cytometry.

    Science.gov (United States)

    Konstantinidis, Diamantis G; Pushkaran, Suvarnamala; Giger, Katie; Manganaris, Stefanos; Zheng, Yi; Kalfa, Theodosia A

    2014-06-06

    Erythropoiesis in mammals concludes with the dramatic process of enucleation that results in reticulocyte formation. The mechanism of enucleation has not yet been fully elucidated. A common problem encountered when studying the localization of key proteins and structures within enucleating erythroblasts by microscopy is the difficulty to observe a sufficient number of cells undergoing enucleation. We have developed a novel analysis protocol using multiparameter high-speed cell imaging in flow (Multi-Spectral Imaging Flow Cytometry), a method that combines immunofluorescent microscopy with flow cytometry, in order to identify efficiently a significant number of enucleating events, that allows to obtain measurements and perform statistical analysis. We first describe here two in vitro erythropoiesis culture methods used in order to synchronize murine erythroblasts and increase the probability of capturing enucleation at the time of evaluation. Then, we describe in detail the staining of erythroblasts after fixation and permeabilization in order to study the localization of intracellular proteins or lipid rafts during enucleation by multi-spectral imaging flow cytometry. Along with size and DNA/Ter119 staining which are used to identify the orthochromatic erythroblasts, we utilize the parameters "aspect ratio" of a cell in the bright-field channel that aids in the recognition of elongated cells and "delta centroid XY Ter119/Draq5" that allows the identification of cellular events in which the center of Ter119 staining (nascent reticulocyte) is far apart from the center of Draq5 staining (nucleus undergoing extrusion), thus indicating a cell about to enucleate. The subset of the orthochromatic erythroblast population with high delta centroid and low aspect ratio is highly enriched in enucleating cells.

  5. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  6. Creating Orthographically Rectified Satellite Multi-Spectral Imagery with High Resolution Digital Elevation Model from LiDAR: A Tutorial

    Science.gov (United States)

    2014-08-15

    EGM96 refers to the equipotential gravity field depicting mean-sea-level across the Earth that is commonly called the geoid...raster and commercial satellite MSI data that are combined in the process of making orthoimages, where feature extraction for models of surface material...peaks along the waveform that show a strong returned laser signal reflected from a rela- tively solid terrain surface or subsurface for the entire

  7. Multispectral Emissions of Lanthanide-Doped Gadolinium Oxide Nanophosphors for Cathodoluminescence and Near-Infrared Upconversion/Downconversion Imaging

    Directory of Open Access Journals (Sweden)

    Doan Thi Kim Dung

    2016-09-01

    Full Text Available Comprehensive imaging of a biological individual can be achieved by utilizing the variation in spatial resolution, the scale of cathodoluminescence (CL, and near-infrared (NIR, as favored by imaging probe Gd2O3 co-doped lanthanide nanophosphors (NPPs. A series of Gd2O3:Ln3+/Yb3+ (Ln3+: Tm3+, Ho3+, Er3+ NPPs with multispectral emission are prepared by the sol-gel method. The NPPs show a wide range of emissions spanning from the visible to the NIR region under 980 nm excitation. The dependence of the upconverting (UC/downconverting (DC emission intensity on the dopant ratio is investigated. The optimum ratios of dopants obtained for emissions in the NIR regions at 810 nm, 1200 nm, and 1530 nm are applied to produce nanoparticles by the homogeneous precipitation (HP method. The nanoparticles produced from the HP method are used to investigate the dual NIR and CL imaging modalities. The results indicate the possibility of using Gd2O3 co-doped Ln3+/Yb3+ (Ln3+: Tm3+, Ho3+, Er3+ in correlation with NIR and CL imaging. The use of Gd2O3 promises an extension of the object dimension to the whole-body level by employing magnetic resonance imaging (MRI.

  8. Satellite images to aircraft in flight. [GEOS image transmission feasibility analysis

    Science.gov (United States)

    Camp, D.; Luers, J. K.; Kadlec, P. W.

    1977-01-01

    A study has been initiated to evaluate the feasibility of transmitting selected GOES images to aircraft in flight. Pertinent observations that could be made from satellite images on board aircraft include jet stream activity, cloud/wind motion, cloud temperatures, tropical storm activity, and location of severe weather. The basic features of the Satellite Aircraft Flight Environment System (SAFES) are described. This system uses East GOES and West GOES satellite images, which are interpreted, enhanced, and then retransmitted to designated aircraft.

  9. Water Mapping Using Multispectral Airborne LIDAR Data

    Science.gov (United States)

    Yan, W. Y.; Shaker, A.; LaRocque, P. E.

    2018-04-01

    This study investigates the use of the world's first multispectral airborne LiDAR sensor, Optech Titan, manufactured by Teledyne Optech to serve the purpose of automatic land-water classification with a particular focus on near shore region and river environment. Although there exist recent studies utilizing airborne LiDAR data for shoreline detection and water surface mapping, the majority of them only perform experimental testing on clipped data subset or rely on data fusion with aerial/satellite image. In addition, most of the existing approaches require manual intervention or existing tidal/datum data for sample collection of training data. To tackle the drawbacks of previous approaches, we propose and develop an automatic data processing workflow for land-water classification using multispectral airborne LiDAR data. Depending on the nature of the study scene, two methods are proposed for automatic training data selection. The first method utilizes the elevation/intensity histogram fitted with Gaussian mixture model (GMM) to preliminarily split the land and water bodies. The second method mainly relies on the use of a newly developed scan line elevation intensity ratio (SLIER) to estimate the water surface data points. Regardless of the training methods being used, feature spaces can be constructed using the multispectral LiDAR intensity, elevation and other features derived from these parameters. The comprehensive workflow was tested with two datasets collected for different near shore region and river environment, where the overall accuracy yielded better than 96 %.

  10. Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory

    Science.gov (United States)

    Anderson, Ryan B.; Bell, James F.

    2013-03-01

    In an effort to infer compositional information about distant targets based on multispectral imaging data, we investigated methods of relating Mars Exploration Rover (MER) Pancam multispectral remote sensing observations to in situ alpha particle X-ray spectrometer (APXS)-derived elemental abundances and Mössbauer (MB)-derived abundances of Fe-bearing phases at the MER field sites in Gusev crater and Meridiani Planum. The majority of the partial correlation coefficients between these data sets were not statistically significant. Restricting the targets to those that were abraded by the rock abrasion tool (RAT) led to improved Pearson’s correlations, most notably between the red-blue ratio (673 nm/434 nm) and Fe3+-bearing phases, but partial correlations were not statistically significant. Partial Least Squares (PLS) calculations relating Pancam 11-color visible to near-IR (VNIR; ∼400-1000 nm) “spectra” to APXS and Mössbauer element or mineral abundances showed generally poor performance, although the presence of compositional outliers led to improved PLS results for data from Meridiani. When the Meridiani PLS model for pyroxene was tested by predicting the pyroxene content of Gusev targets, the results were poor, indicating that the PLS models for Meridiani are not applicable to data from other sites. Soft Independent Modeling of Class Analogy (SIMCA) classification of Gusev crater data showed mixed results. Of the 24 Gusev test regions of interest (ROIs) with known classes, 11 had >30% of the pixels in the ROI classified correctly, while others were mis-classified or unclassified. k-Means clustering of APXS and Mössbauer data was used to assign Meridiani targets to compositional classes. The clustering-derived classes corresponded to meaningful geologic and/or color unit differences, and SIMCA classification using these classes was somewhat successful, with >30% of pixels correctly classified in 9 of the 11 ROIs with known classes. This work shows that

  11. An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

    Science.gov (United States)

    Jaggi, S.

    1993-01-01

    A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

  12. Very high resolution satellite data: New challenges in image analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...

  13. Satellite-generated radar images of the earth

    International Nuclear Information System (INIS)

    Schanda, E.

    1980-01-01

    The Synthetic Aperture Radar (SAR) on board of SEASAT was the first non-military satellite-borne radar producing high-resolution images of the earth. Several examples of European scenes are discussed to demonstrate the properties of presently available optically processes images. (orig.)

  14. Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

    2016-09-01

    In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

  15. Medical image transmission via communication satellite. Evaluation of bone scintigraphy

    International Nuclear Information System (INIS)

    Suzuki, Hideki; Inoue, Tomio; Endo, Keigo; Shimamoto, Shigeru.

    1995-01-01

    As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT 1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical imagings by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6±2.6% via satellite, and 93.2±2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes. (author)

  16. [Medical image transmission via communication satellite: evaluation of bone scintigraphy].

    Science.gov (United States)

    Suzuki, H; Inoue, T; Endo, K; Shimamoto, S

    1995-10-01

    As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical images by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6 +/- 2.6% via satellite, and 93.2 +/- 2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes.

  17. UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

    Directory of Open Access Journals (Sweden)

    S. Havivi

    2016-06-01

    Full Text Available Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD for SAR data and Covariance Equalization (CE for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a

  18. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

    Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

  19. Generating Multispectral VIIRS Imagery in Near Real-Time for Use by the National Weather Service in Alaska

    Science.gov (United States)

    Broderson, D.; Dierking, C.; Stevens, E.; Heinrichs, T. A.; Cherry, J. E.

    2016-12-01

    The Geographic Information Network of Alaska (GINA) at the University of Alaska Fairbanks (UAF) uses two direct broadcast antennas to receive data from a number of polar-orbiting weather satellites, including the Suomi National Polar Partnership (S-NPP) satellite. GINA uses data from S-NPP's Visible Infrared Imaging Radiometer Suite (VIIRS) to generate a variety of multispectral imagery products developed with the needs of the National Weather Service operational meteorologist in mind. Multispectral products have two primary advantages over single-channel products. First, they can more clearly highlight some terrain and meteorological features which are less evident in the component single channels. Second, multispectral present the information from several bands through just one image, thereby sparing the meteorologist unnecessary time interrogating the component single bands individually. With 22 channels available from the VIIRS instrument, the number of possible multispectral products is theoretically huge. A small number of products will be emphasized in this presentation, with the products chosen based on their proven utility in the forecasting environment. Multispectral products can be generated upstream of the end user or by the end user at their own workstation. The advantage and disadvantages of both approaches will be outlined. Lastly, the technique of improving the appearance of multispectral imagery by correcting for atmospheric reflectance at the shorter wavelengths will be described.

  20. Vicarious calibration campaign in Argentina for radiometric calibration of a multispectral imager onboard sumbandila satellite

    CSIR Research Space (South Africa)

    Griffith, DJ

    2011-07-01

    Full Text Available Espaciales (CONAE), Centro de Investigaciones ?pticas (CIOP), from Consejo Nacional deInvestigaciones Cient?ficas y T?cnicas (CONICET) and Comisi?n de Investigaciones Cient?ficas de la Provincia de Buenos Aires (CIC) Facultad de Ciencias Agrarias y... Cient?ficas de la Provincia de Buenos Aires (CIC) Facultad de Ciencias Agrarias y Forestales, Universidad Nacional de La Plata (FCAyF, UNLP) in Argentina for help in our Argentina field campaign. The authors thank the CSIR, DST and CONAE for funding...

  1. The best printing methods to print satellite images

    Directory of Open Access Journals (Sweden)

    G.A. Yousif

    2011-12-01

    In this paper different printing systems were used to print an image of SPOT-4 satellite, caver part of Sharm Elshekh area, Sinai, Egypt, on the same type of paper as much as possible, especially in the photography. This step is followed by measuring the experimental data, and analyzed colors to determine the best printing systems for satellite image printing data. The laser system is the more printing system where produce a wider range of color and highest densities of ink and access much color detail. Followed by the offset system which it recorded the best dot gain. Moreover, the study shows that it can use the advantages of each method according to the satellite image color and quantity to be produced.

  2. 3D modeling of satellite spectral images, radiation budget and energy budget of urban landscapes

    Science.gov (United States)

    Gastellu-Etchegorry, J. P.

    2008-12-01

    DART EB is a model that is being developed for simulating the 3D (3 dimensional) energy budget of urban and natural scenes, possibly with topography and atmosphere. It simulates all non radiative energy mechanisms (heat conduction, turbulent momentum and heat fluxes, water reservoir evolution, etc.). It uses DART model (Discrete Anisotropic Radiative Transfer) for simulating radiative mechanisms: 3D radiative budget of 3D scenes and their remote sensing images expressed in terms of reflectance or brightness temperature values, for any atmosphere, wavelength, sun/view direction, altitude and spatial resolution. It uses an innovative multispectral approach (ray tracing, exact kernel, discrete ordinate techniques) over the whole optical domain. This paper presents two major and recent improvements of DART for adapting it to urban canopies. (1) Simulation of the geometry and optical characteristics of urban elements (houses, etc.). (2) Modeling of thermal infrared emission by vegetation and urban elements. The new DART version was used in the context of the CAPITOUL project. For that, districts of the Toulouse urban data base (Autocad format) were translated into DART scenes. This allowed us to simulate visible, near infrared and thermal infrared satellite images of Toulouse districts. Moreover, the 3D radiation budget was used by DARTEB for simulating the time evolution of a number of geophysical quantities of various surface elements (roads, walls, roofs). Results were successfully compared with ground measurements of the CAPITOUL project.

  3. Detecting early stage pressure ulcer on dark skin using multispectral imager

    Science.gov (United States)

    Kong, Linghua; Sprigle, Stephen; Yi, Dingrong; Wang, Chao; Wang, Fengtao; Liu, Fuhan; Wang, Jiwu; Zhao, Futing

    2009-10-01

    This paper introduces a novel idea, innovative technology in building multi spectral imaging based device. The benefit from them is people can have low cost, handheld and standing alone device which makes acquire multi spectral images real time with just a snapshot. The paper for the first time publishes some images got from such prototyped miniaturized multi spectral imager.

  4. Multispectral colormapping using penalized least square regression

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Carstensen, Jens Michael; Larsen, Rasmus

    2010-01-01

    The authors propose a novel method to map a multispectral image into the device independent color space CIE-XYZ. This method provides a way to visualize multispectral images by predicting colorvalues from spectral values while maintaining interpretability and is tested on a light emitting diode...... that the interpretability improves significantly but comes at the cost of slightly worse predictability....

  5. Potential use of multispectral imaging technology to identify moisture content and water-holding capacity in cooked pork sausages.

    Science.gov (United States)

    Ma, Fei; Zhang, Bin; Wang, Wu; Li, Peijun; Niu, Xiangli; Chen, Conggui; Zheng, Lei

    2018-03-01

    The traditional detection methods for moisture content (MC) and water-holding capacity (WHC) in cooked pork sausages (CPS) are destructive, time consuming, require skilled personnel and are not suitable for online industry applications. The goal of this work was to explore the potential of multispectral imaging (MSI) in combination with multivariate analysis for the identification of MC and WHC in CPS. Spectra and textures of 156 CPS treated by six salt concentrations (0-2.5%) were analyzed using different calibration models to find the most optimal results of predicting MC and WHC in CPS. By using the fused data of spectra and textures, partial least squares regression models performed well for determining the MC and WHC, with a correlation coefficient (r) of 0.949 and 0.832, respectively. Additionally, their spatial distribution in CPS could be visualized via applying prediction equations to transfer each pixel in the image. Results of satisfactory detection and visualization of the MC and WHC showed that MSI has the potential to serve as a rapid and non-destructive method for use in sausage industry. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  6. Dual-Modality Imaging of the Human Finger Joint Systems by Using Combined Multispectral Photoacoustic Computed Tomography and Ultrasound Computed Tomography

    Directory of Open Access Journals (Sweden)

    Yubin Liu

    2016-01-01

    Full Text Available We developed a homemade dual-modality imaging system that combines multispectral photoacoustic computed tomography and ultrasound computed tomography for reconstructing the structural and functional information of human finger joint systems. The fused multispectral photoacoustic-ultrasound computed tomography (MPAUCT system was examined by the phantom and in vivo experimental tests. The imaging results indicate that the hard tissues such as the bones and the soft tissues including the blood vessels, the tendon, the skins, and the subcutaneous tissues in the finger joints systems can be effectively recovered by using our multimodality MPAUCT system. The developed MPAUCT system is able to provide us with more comprehensive information of the human finger joints, which shows its potential for characterization and diagnosis of bone or joint diseases.

  7. Study on the detection of three-dimensional soot temperature and volume fraction fields of a laminar flame by multispectral imaging system

    International Nuclear Information System (INIS)

    Ni, Mingjiang; Zhang, Haidan; Wang, Fei; Xie, Zhengchao; Huang, Qunxing; Yan, Jianhua; Cen, Kefa

    2016-01-01

    Highlights: • Multispectral flame images were used to reconstruct the soot temperature and volume fraction. • The proposed multi-wavelength method and the original two-color method were compared. • The effect of signal to noise ratio (SNR) was discussed. • The best number of selected wavelengths was determined to be 6–11. - Abstract: Charge-coupled device (CCD) cameras with liquid crystal tunable filters (LCTF) were introduced to capture the multispectral flame images for obtaining the line-of-sight radiation intensities. A least square QR decomposition method was applied to solve the reconstruction matrix equation and obtain the multi-wavelength local emission distributions from which temperature and volume fraction profiles can be retrieved. Compared with the original two-color method, the use of a wide range of spectral data was proved to be capable of reducing the reconstruction error. Reconstruction results of the two methods with different signal to noise ratio (SNR) were discussed. The effect of selected wavelength number is analyzed and the best number is determined to be in the range of 6–11. The proposed multispectral imaging system was verified to be feasible for the reconstruction of temperature and soot volume fraction distributions according to the experimental measurement results.

  8. Tree Species Classification in Temperate Forests Using Formosat-2 Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    David Sheeren

    2016-09-01

    Full Text Available Mapping forest composition is a major concern for forest management, biodiversity assessment and for understanding the potential impacts of climate change on tree species distribution. In this study, the suitability of a dense high spatial resolution multispectral Formosat-2 satellite image time-series (SITS to discriminate tree species in temperate forests is investigated. Based on a 17-date SITS acquired across one year, thirteen major tree species (8 broadleaves and 5 conifers are classified in a study area of southwest France. The performance of parametric (GMM and nonparametric (k-NN, RF, SVM methods are compared at three class hierarchy levels for different versions of the SITS: (i a smoothed noise-free version based on the Whittaker smoother; (ii a non-smoothed cloudy version including all the dates; (iii a non-smoothed noise-free version including only 14 dates. Noise refers to pixels contaminated by clouds and cloud shadows. The results of the 108 distinct classifications show a very high suitability of the SITS to identify the forest tree species based on phenological differences (average κ = 0 . 93 estimated by cross-validation based on 1235 field-collected plots. SVM is found to be the best classifier with very close results from the other classifiers. No clear benefit of removing noise by smoothing can be observed. Classification accuracy is even improved using the non-smoothed cloudy version of the SITS compared to the 14 cloud-free image time series. However conclusions of the results need to be considered with caution because of possible overfitting. Disagreements also appear between the maps produced by the classifiers for complex mixed forests, suggesting a higher classification uncertainty in these contexts. Our findings suggest that time-series data can be a good alternative to hyperspectral data for mapping forest types. It also demonstrates the potential contribution of the recently launched Sentinel-2 satellite for

  9. Development of a software for monitoring of seismic activity through the analysis of satellite images

    Science.gov (United States)

    Soto-Pinto, C.; Poblete, A.; Arellano-Baeza, A. A.; Sanchez, G.

    2010-12-01

    A software for extraction and analysis of the lineaments has been developed and applied for the tracking of the accumulation/relaxation of stress in the Earth’s crust due to seismic and volcanic activity. A lineament is a straight or a somewhat curved feature in a satellite image, which reflects, at least partially, presence of faults in the crust. The technique of lineament extraction is based on the application of directional filters and Hough transform. The software has been checked for several earthquakes occurred in the Pacific coast of the South America with the magnitude > 4 Mw, analyzing temporal sequences of the ASTER/TERRA multispectral satellite images for the regions around an epicenter. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changes significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth’s crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion.

  10. Autonomous Planetary 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz

    1999-01-01

    is discussed.Based on such features, 3-D representations may be compiled from two or more 2-D satellite images. The main purposes of such a mapping system are extraction of landing sites, objects of scientific interest and general planetary surveying. All data processing is performed autonomously onboard...

  11. A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

    Science.gov (United States)

    Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

    2017-12-01

    The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

  12. Final Report on LDRD project 130784 : functional brain imaging by tunable multi-spectral Event-Related Optical Signal (EROS).

    Energy Technology Data Exchange (ETDEWEB)

    Speed, Ann Elizabeth; Spahn, Olga Blum; Hsu, Alan Yuan-Chun

    2009-09-01

    Functional brain imaging is of great interest for understanding correlations between specific cognitive processes and underlying neural activity. This understanding can provide the foundation for developing enhanced human-machine interfaces, decision aides, and enhanced cognition at the physiological level. The functional near infrared spectroscopy (fNIRS) based event-related optical signal (EROS) technique can provide direct, high-fidelity measures of temporal and spatial characteristics of neural networks underlying cognitive behavior. However, current EROS systems are hampered by poor signal-to-noise-ratio (SNR) and depth of measure, limiting areas of the brain and associated cognitive processes that can be investigated. We propose to investigate a flexible, tunable, multi-spectral fNIRS EROS system which will provide up to 10x greater SNR as well as improved spatial and temporal resolution through significant improvements in electronics, optoelectronics and optics, as well as contribute to the physiological foundation of higher-order cognitive processes and provide the technical foundation for miniaturized portable neuroimaging systems.

  13. The cradle of pyramids in satellite images

    OpenAIRE

    Sparavigna, Amelia Carolina

    2011-01-01

    We propose the use of image processing to enhance the Google Maps of some archaeological areas of Egypt. In particular we analyse that place which is considered the cradle of pyramids, where it was announced the discovery of a new pyramid by means of an infrared remote sensing.

  14. Multispectral fluorescence imaging technique for discrimination of cucumber (Cucumis Sativus) seed viability

    Science.gov (United States)

    In this study, we developed a nondestructive method for discriminating viable cucumber (Cucumis sativus) seeds based on hyperspectral fluorescence imaging. The fluorescence spectra of cucumber seeds in the 420–700 nm range were extracted from hyperspectral fluorescence images obtained using 365 nm u...

  15. Rapid Assessment of Tablet Film Coating Quality by Multispectral UV Imaging

    DEFF Research Database (Denmark)

    Klukkert, Marten; Wu, Jian X.; Rantanen, Jukka

    2016-01-01

    and coated with a polyvinyl alcohol-polyethylene glycol graft copolymer using a pan coater. It was demonstrated that the coating intactness can be assessed accurately and fast by UV imaging. The different types of coating defects could be differentiated and localized based on multivariate image analysis...

  16. An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiao Ling

    2016-08-01

    Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

  17. Landsat sattelite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation districts of lower Rio Grande Valley of Texas

    Science.gov (United States)

    The Lower Rio Grande Valley in the south of Texas is experiencing rapid increase of population to bring up urban growth that continues influencing on the irrigation districts in the region. This study evaluated the Landsat satellite multi-spectral imagery to provide information for GIS-based urbaniz...

  18. Automated registration of multispectral MR vessel wall images of the carotid artery

    Energy Technology Data Exchange (ETDEWEB)

    Klooster, R. van ' t; Staring, M.; Reiber, J. H. C.; Lelieveldt, B. P. F.; Geest, R. J. van der, E-mail: rvdgeest@lumc.nl [Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden (Netherlands); Klein, S. [Department of Radiology and Department of Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam 3015 GE (Netherlands); Kwee, R. M.; Kooi, M. E. [Department of Radiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht 6202 AZ (Netherlands)

    2013-12-15

    Purpose: Atherosclerosis is the primary cause of heart disease and stroke. The detailed assessment of atherosclerosis of the carotid artery requires high resolution imaging of the vessel wall using multiple MR sequences with different contrast weightings. These images allow manual or automated classification of plaque components inside the vessel wall. Automated classification requires all sequences to be in alignment, which is hampered by patient motion. In clinical practice, correction of this motion is performed manually. Previous studies applied automated image registration to correct for motion using only nondeformable transformation models and did not perform a detailed quantitative validation. The purpose of this study is to develop an automated accurate 3D registration method, and to extensively validate this method on a large set of patient data. In addition, the authors quantified patient motion during scanning to investigate the need for correction. Methods: MR imaging studies (1.5T, dedicated carotid surface coil, Philips) from 55 TIA/stroke patients with ipsilateral <70% carotid artery stenosis were randomly selected from a larger cohort. Five MR pulse sequences were acquired around the carotid bifurcation, each containing nine transverse slices: T1-weighted turbo field echo, time of flight, T2-weighted turbo spin-echo, and pre- and postcontrast T1-weighted turbo spin-echo images (T1W TSE). The images were manually segmented by delineating the lumen contour in each vessel wall sequence and were manually aligned by applying throughplane and inplane translations to the images. To find the optimal automatic image registration method, different masks, choice of the fixed image, different types of the mutual information image similarity metric, and transformation models including 3D deformable transformation models, were evaluated. Evaluation of the automatic registration results was performed by comparing the lumen segmentations of the fixed image and

  19. Automated registration of multispectral MR vessel wall images of the carotid artery

    International Nuclear Information System (INIS)

    Klooster, R. van 't; Staring, M.; Reiber, J. H. C.; Lelieveldt, B. P. F.; Geest, R. J. van der; Klein, S.; Kwee, R. M.; Kooi, M. E.

    2013-01-01

    Purpose: Atherosclerosis is the primary cause of heart disease and stroke. The detailed assessment of atherosclerosis of the carotid artery requires high resolution imaging of the vessel wall using multiple MR sequences with different contrast weightings. These images allow manual or automated classification of plaque components inside the vessel wall. Automated classification requires all sequences to be in alignment, which is hampered by patient motion. In clinical practice, correction of this motion is performed manually. Previous studies applied automated image registration to correct for motion using only nondeformable transformation models and did not perform a detailed quantitative validation. The purpose of this study is to develop an automated accurate 3D registration method, and to extensively validate this method on a large set of patient data. In addition, the authors quantified patient motion during scanning to investigate the need for correction. Methods: MR imaging studies (1.5T, dedicated carotid surface coil, Philips) from 55 TIA/stroke patients with ipsilateral <70% carotid artery stenosis were randomly selected from a larger cohort. Five MR pulse sequences were acquired around the carotid bifurcation, each containing nine transverse slices: T1-weighted turbo field echo, time of flight, T2-weighted turbo spin-echo, and pre- and postcontrast T1-weighted turbo spin-echo images (T1W TSE). The images were manually segmented by delineating the lumen contour in each vessel wall sequence and were manually aligned by applying throughplane and inplane translations to the images. To find the optimal automatic image registration method, different masks, choice of the fixed image, different types of the mutual information image similarity metric, and transformation models including 3D deformable transformation models, were evaluated. Evaluation of the automatic registration results was performed by comparing the lumen segmentations of the fixed image and

  20. Identifying fecal matter contamination in produce fields using multispectral reflectance imaging under ambient solar illumination

    Science.gov (United States)

    Everard, Colm D.; Kim, Moon S.; Lee, Hoonsoo; O'Donnell, Colm P.

    2016-05-01

    An imaging device to detect fecal contamination in fresh produce fields could allow the producer avoid harvesting fecal contaminated produce. E.coli O157:H7 outbreaks have been associated with fecal contaminated leafy greens. In this study, in-field spectral profiles of bovine fecal matter, soil, and spinach leaves are compared. A common aperture imager designed with two identical monochromatic cameras, a beam splitter, and optical filters was used to simultaneously capture two-spectral images of leaves contaminated with both fecal matter and soil. The optical filters where 10 nm full width half maximum bandpass filters, one at 690 nm and the second at 710 nm. These were mounted in front of the object lenses. New images were created using the ratio of these two spectral images on a pixel by pixel basis. Image analysis results showed that the fecal matter contamination could be distinguished from soil and leaf on the ratio images. The use of this technology has potential to allow detection of fecal contamination in produce fields which can be a source of foodbourne illnesses. It has the added benefit of mitigating cross-contamination during harvesting and processing.

  1. Comparison of hyperspectral transformation accuracies of multispectral Landsat TM, ETM+, OLI and EO-1 ALI images for detecting minerals in a geothermal prospect area

    Science.gov (United States)

    Hoang, Nguyen Tien; Koike, Katsuaki

    2018-03-01

    Hyperspectral remote sensing generally provides more detailed spectral information and greater accuracy than multispectral remote sensing for identification of surface materials. However, there have been no hyperspectral imagers that cover the entire Earth surface. This lack points to a need for producing pseudo-hyperspectral imagery by hyperspectral transformation from multispectral images. We have recently developed such a method, a Pseudo-Hyperspectral Image Transformation Algorithm (PHITA), which transforms Landsat 7 ETM+ images into pseudo-EO-1 Hyperion images using multiple linear regression models of ETM+ and Hyperion band reflectance data. This study extends the PHITA to transform TM, OLI, and EO-1 ALI sensor images into pseudo-Hyperion images. By choosing a part of the Fish Lake Valley geothermal prospect area in the western United States for study, the pseudo-Hyperion images produced from the TM, ETM+, OLI, and ALI images by PHITA were confirmed to be applicable to mineral mapping. Using a reference map as the truth, three main minerals (muscovite and chlorite mixture, opal, and calcite) were identified with high overall accuracies from the pseudo-images (> 95% and > 42% for excluding and including unclassified pixels, respectively). The highest accuracy was obtained from the ALI image, followed by ETM+, TM, and OLI images in descending order. The TM, OLI, and ALI images can be alternatives to ETM+ imagery for the hyperspectral transformation that aids the production of pseudo-Hyperion images for areas without high-quality ETM+ images because of scan line corrector failure, and for long-term global monitoring of land surfaces.

  2. 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz

    1999-01-01

    of planetary surfaces, but other purposes is considered as well. The system performance is measured with respect to the precision and the time consumption.The reconstruction process is divided into four major areas: Acquisition, calibration, matching/reconstruction and presentation. Each of these areas...... are treated individually. A detailed treatment of various lens distortions is required, in order to correct for these problems. This subject is included in the acquisition part. In the calibration part, the perspective distortion is removed from the images. Most attention has been paid to the matching problem...

  3. Shoreline change assessment using multi-temporal satellite images: a case study of Lake Sapanca, NW Turkey.

    Science.gov (United States)

    Duru, Umit

    2017-08-01

    The research summarized here determines historical shoreline changes along Lake Sapanca by using Remote Sensing (RS) and Geographical Information Systems (GIS). Six multi-temporal satellite images of Landsat Multispectral Scanner (L1-5 MMS), Enhanced Thematic Mapper Plus (L7 ETM+), and Operational Land Imager Sensors (L8 OLI), covering the period between 17 June 1975 and 15 July 2016, were used to monitor shoreline positions and estimate change rates along the coastal zone. After pre-possessing routines, the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and supervised classification techniques were utilized to extract six different shorelines. Digital Shoreline Analysis System (DSAS), a toolbox that enables transect-based computations of shoreline displacement, was used to compute historical shoreline change rates. The average rate of shoreline change for the entire cost was 2.7 m/year of progradation with an uncertainty of 0.2 m/year. While the great part of the lake shoreline remained stable, the study concluded that the easterly and westerly coasts and deltaic coasts are more vulnerable to shoreline displacements over the last four decades. The study also reveals that anthropogenic activities, more specifically over extraction of freshwater from the lake, cyclic variation in rainfall, and deposition of sediment transported by the surrounding creeks dominantly control spatiotemporal shoreline changes in the region. Monitoring shoreline changes using multi-temporal satellite images is a significant component for the coastal decision-making and management.

  4. RELIABILITY OF CONFOCAL MICROSCOPY SPECTRAL IMAGING SYSTEMS: USE OF MULTISPECTRAL BEADS

    Science.gov (United States)

    Background: There is a need for a standardized, impartial calibration, and validation protocol on confocal spectral imaging (CSI) microscope systems. To achieve this goal, it is necessary to have testing tools to provide a reproducible way to evaluate instrument performance. ...

  5. Use of partial least squares discriminant analysis on visible-near infrared multispectral image data to examine germination ability and germ length in spinach seeds

    DEFF Research Database (Denmark)

    Shetty, Nisha; Olesen, Merete Halkjær; Gislum, René

    2012-01-01

    Because of the difficulties in obtaining homogenous germination of spinach seeds for baby leaf production, the possibility of using partial least squares discriminant analysis (PLS-DA) on features extracted from multispectral images of spinach seeds was investigated. The objective has been...... to discriminate between different seed sizes, as well as to predict germination ability and germ length. Images of 300 seeds including small, medium, and large seeds were taken, and the seeds were examined for germination ability and germ length. PLS-DA loadings plots were used to reduce the multidimensional...

  6. Development of a mobile multispectral imaging platform for precise field phenotyping

    DEFF Research Database (Denmark)

    Svensgaard, Jesper; Roitsch, Thomas Georg; Christensen, Svend

    2014-01-01

    nitrogen levels, replicated on two different soil types at four different dates from 15 May (BBCH 13) to 18 June (BBCH 41 to 57). The images were analyzed and derived vegetation coverage and Normalized Difference Vegetation index (NDVI) were used to assess varietal differences. The results showed...... potentials for differentiating between the varieties using both vegetation coverage and NDVI, especially at the early growth stages. The perspectives of high-precision and high-throughput imaging for field phenotyping are discussed including the potentials of measuring varietal differences via spectral...

  7. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  8. Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations

    Science.gov (United States)

    Jorgensen, A.; Schmitt, H.; Mozurkewich, D.; Armstrong, J.; Restaino, S.; Hindsley, R.

    2011-09-01

    Geostationary satellites are generally too small to image at high resolution with conventional single-dish telescopes. Obtaining many resolution elements across a typical geostationary satellite body requires a single-dish telescope with a diameter of 10’s of m or more, with a good adaptive optics system. An alternative is to use an optical/infrared interferometer consisting of multiple smaller telescopes in an array configuration. In this paper and companion papers1, 2 we discuss the performance of a common-mount 30-element interferometer. The instrument design is presented by Mozurkewich et al.,1 and imaging performance is presented by Schmitt et al.2 In this paper we discuss signal-to-noise ratio for both fringe-tracking and imaging. We conclude that the common-mount interferometer is sufficiently sensitive to track fringes on the majority of geostationary satellites. We also find that high-fidelity images can be obtained after a short integration time of a few minutes to a few tens of minutes.

  9. The fusion of satellite and UAV data: simulation of high spatial resolution band

    Science.gov (United States)

    Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

    2017-10-01

    Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

  10. Identifying fecal matter contamination in produce fields using multispectral reflectance imaging under ambient solar illumination

    Science.gov (United States)

    An imaging device to detect fecal contamination in fresh produce fields could allow the producer to avoid harvesting fecal-contaminated produce. E.coli O157:H7 outbreaks have been associated with fecal-contaminated leafy greens. In this study, in-field spectral profiles of bovine fecal matter, soil,...

  11. Multispectral fluorescence imaging for detection of bovine feces on Romaine lettuce and baby spinach leaves

    Science.gov (United States)

    Hyperspectral fluorescence imaging with ultraviolet-A excitation was used to evaluate the feasibility of two-waveband fluorescence algorithms for the detection of bovine fecal contaminants on the abaxial and adaxial surfaces of Romaine lettuce and baby spinach leaves. Correlation analysis was used t...

  12. Multitemporal Satellite Images for Knowledge of the Assyrian Capital Cities and for Monitoring Landscape Transformations in the Upper Course of Tigris River

    Directory of Open Access Journals (Sweden)

    Giuseppe Scardozzi

    2011-01-01

    Full Text Available The paper is concerned with the contribution that a rich documentation of multitemporal optical satellite images with high resolution provides for the knowledge of the five great Assyrian capital cities (Ashur, Kar-Tukulti-Ninurta, Kalhu, Dur-Sharrukin, and Nineveh, in northern Iraq. These images also allow monitoring changes of landscape in the higher course of the Tigris during the last half century and document damages in archaeological sites during the two Gulf Wars. The data set, available for each city, consists of panchromatic and multispectral images taken between 2001 and 2007 by modern commercial satellites (Ikonos-2, QuickBird-2, and WorldView-1 and of panchromatic photographs of U.S. spy satellites operating between 1965 and 1969 (Corona KH-4B and Gambit KH-7. These photos were taken before diffusion of mechanized agriculture and the expansion of urban areas, so they are very useful to document many archaeological features and the landscape that has been modified in the last decades, as shown by recent satellite images.

  13. Radiometric Cross-Calibration of GF-4 in Multispectral Bands

    Directory of Open Access Journals (Sweden)

    Aixia Yang

    2017-03-01

    Full Text Available The GaoFen-4 (GF-4, launched at the end of December 2015, is China’s first high-resolution geostationary optical satellite. A panchromatic and multispectral sensor (PMS is onboard the GF-4 satellite. Unfortunately, the GF-4 has no onboard calibration assembly, so on-orbit radiometric calibration is required. Like the charge-coupled device (CCD onboard HuanJing-1 (HJ or the wide field of view sensor (WFV onboard GaoFen-1 (GF-1, GF-4 also has a wide field of view, which provides challenges for cross-calibration with narrow field of view sensors, like the Landsat series. A new technique has been developed and used to calibrate HJ-1/CCD and GF-1/WFV, which is verified viable. The technique has three key steps: (1 calculate the surface using the bi-directional reflectance distribution function (BRDF characterization of a site, taking advantage of its uniform surface material and natural topographic variation using Landsat Enhanced Thematic Mapper Plus (ETM+/Operational Land Imager (OLI imagery and digital elevation model (DEM products; (2 calculate the radiance at the top-of-the atmosphere (TOA with the simulated surface reflectance using the atmosphere radiant transfer model; and (3 fit the calibration coefficients with the TOA radiance and corresponding Digital Number (DN values of the image. This study attempts to demonstrate the technique is also feasible to calibrate GF-4 multispectral bands. After fitting the calibration coefficients using the technique, extensive validation is conducted by cross-validation using the image pairs of GF-4/PMS and Landsat-8/OLI with similar transit times and close view zenith. The validation result indicates a higher accuracy and frequency than that given by the China Centre for Resources Satellite Data and Application (CRESDA using vicarious calibration. The study shows that the new technique is also quite feasible for GF-4 multispectral bands as a routine long-term procedure.

  14. Multichannel and Multispectral Image Restoration Employing Fuzzy Theory and Directional Techniques

    OpenAIRE

    Rosales, Alberto; Ponomaryov, Volodymyr

    2009-01-01

    It has designed a novel structure of robust framework to remove impulse noise and additive noise in images and multichannel video sequences. Unlike existed techniques, the designed approach employs fuzzy and directional techniques to estimate motion and noise in the past and present frames showing good results. The designed fuzzy rules characterize the presence of motion and noise between the pixels in two frames (past and present frames). It has been demonstrated that the combined use of gra...

  15. CLASSIFICATION BY USING MULTISPECTRAL POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    C. T. Liao

    2012-07-01

    Full Text Available Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

  16. Classification by Using Multispectral Point Cloud Data

    Science.gov (United States)

    Liao, C. T.; Huang, H. H.

    2012-07-01

    Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

  17. Image Fusion Applied to Satellite Imagery for the Improved Mapping and Monitoring of Coral Reefs: a Proposal

    Science.gov (United States)

    Gholoum, M.; Bruce, D.; Hazeam, S. Al

    2012-07-01

    A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine the quality of the

  18. IMAGE FUSION APPLIED TO SATELLITE IMAGERY FOR THE IMPROVED MAPPING AND MONITORING OF CORAL REEFS: A PROPOSAL

    Directory of Open Access Journals (Sweden)

    M. Gholoum

    2012-07-01

    Full Text Available A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine

  19. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus

    2017-03-01

    Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU

  20. Use of high-resolution satellite images for detection of geological structures related to Central Andes geothermal field, Chile.

    Science.gov (United States)

    Benavides-Rivas, C. L.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

    2014-12-01

    Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT 8 satellite have been used to delineate the geological structures related to the potential geothermal reservoirs located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique, using the ADALGEO software, developed by [Soto et al., 2013]. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields. A lineament is generally defined as a straight or slightly curved feature in the landscape visible satellite image as an aligned sequence of pixel intensity contrast compared to the background. The system features extracted from satellite images is not identical to the geological lineaments that are generally determined by ground surveys, however, generally reflects the structure of faults and fractures in the crust. A temporal sequence of eight Landsat multispectral images of Central Andes geothermal field, located in VI region de Chile, was used to study changes in the configuration of the lineaments during 2011. The presence of minerals with silicification, epidotization, and albitization, which are typical for geothrmal reservoirs, was also identified, using their spectral characteristics, and subsequently corroborated in the field. Both lineament analysis and spectral analysis gave similar location of the reservoir, which increases reliability of the results.

  1. ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    H. Kim

    2012-07-01

    Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.

  2. Satellites

    International Nuclear Information System (INIS)

    Burns, J.A.; Matthews, M.S.

    1986-01-01

    The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

  3. METEOROLOGICAL SATELLITE IMAGES IN GEOGRAPHY CLASSES: a didactic possibility

    Directory of Open Access Journals (Sweden)

    Diego Correia Maia

    2016-01-01

    Full Text Available ABSTRACT: The satellite images are still largely unexplored as didactic resource in geography classes, particularly about meteorology. This article aims to contribute to the development of new methodologies of interpretation and understanding, beyond the construction of pedagogical practices involving meteorological satellite images, concepts and issues related to climate issues. The aim of this paper is to present possibilities for the use of meteorological satellite images in the Teaching of Geography, aiming the promoting and the understanding of contents of air masses and fronts and climatic factors. RESUMO: As imagens de satélite ainda são pouco exploradas como recurso didático nas aulas de Geografia, principalmente aquelas relativas à meteorologia. Este artigo visa contribuir com o desenvolvimento de novas metodologias de interpretação e compreensão, além da construção de práticas pedagógicas envolvendo imagens de satélite meteorológico, conceitos e temas ligados às questões climáticas. Seu objetivo é apresentar possibilidades de utilização das imagens de satélite meteorológico no Ensino de Geografia, visando à promoção e ao entendimento dos conteúdos de massas de ar e frentes e de elementos climáticos. Palavras chave

  4. A Comparative Performance Analysis of Multispectral and RGB Imaging on HER2 Status Evaluation for the Prediction of Breast Cancer Prognosis.

    Science.gov (United States)

    Liu, Wenlou; Wang, Linwei; Liu, Jiuyang; Yuan, Jingping; Chen, Jiamei; Wu, Han; Xiang, Qingming; Yang, Guifang; Li, Yan

    2016-12-01

    Despite the extensive application of multispectral imaging (MSI) in biomedical multidisciplinary researches, there is a paucity of data available regarding the implication of MSI in tumor prognosis prediction. We compared the behaviors of multispectral (MS) and conventional red-green-blue (RGB) images on assessment of human epidermal growth factor receptor 2 (HER2) immunohistochemistry to explore their impact on outcome in patients with invasive breast cancer (BC). Tissue microarrays containing 240 BC patients were introduced to compare the performance of MS and RGB imaging methods on the quantitative assessment of HER2 status and the prognostic value of 5-year disease-free survival (5-DFS). Both the total and average signal optical density values of HER2 MS and RGB images were analyzed, and all patients were divided into two groups based on the different 5-DFS. The quantification of HER2 MS images was negatively correlated with 5-DFS in lymph node-negative and -positive patients (Panalysis indicated that the hazard ratio (HR) of HER2 MS was higher than that of HER2 RGB (HR=2.454; 95% confidence interval [CI], 1.636-3.681 vs HR=2.060; 95% CI, 1.361-3.119). Additionally, area under curve (AUC) by receiver operating characteristic analysis for HER2 MS was greater than that for HER2 RGB (AUC=0.649; 95% CI, 0.577-0.722 vs AUC=0.596; 95% CI, 0.522-0.670) in predicting the risk for recurrence. More importantly, the quantification of HER2 MS images has higher prediction accuracy than that of HER2 RGB images (69.6% vs 65.0%) on 5-DFS. Our study suggested that better information on BC prognosis could be obtained from the quantification of HER2 MS images and MS images might perform better in predicting BC prognosis than conventional RGB images. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  5. Recurrent Neural Networks to Correct Satellite Image Classification Maps

    Science.gov (United States)

    Maggiori, Emmanuel; Charpiat, Guillaume; Tarabalka, Yuliya; Alliez, Pierre

    2017-09-01

    While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.

  6. Reconstruction of quasimonochromatic images for multispectral x-ray imaging with a pinhole array and a flat Bragg mirror

    International Nuclear Information System (INIS)

    Izumi, N.; Barbee, T. W.; Koch, J. A.; Mancini, R. C.; Welser, L. A.

    2006-01-01

    We have developed a software package for reconstruction of quasimonochromatic images from a multiple monochromatic x-ray imager for inertial confinement fusion implosions. The instrument consists of a pinhole array, a multilayer Bragg mirror, and an image detector. The pinhole array projects hundreds of images onto the detector after reflection off the multilayer Bragg mirror, which introduces spectral dispersion along the reflection axis. The quasimonochromatic images of line emissions and continuum emissions can be used for measurement of temperature and density maps of implosion plasmas. In this article, we describe a computer-aided processing technique for systematic reconstruction of quasimonochromatic images from raw data. This technique provides flexible spectral bandwidth selection and allows systematic subtraction of continuum emission from line emission images

  7. Prospects of application of survey satellite image for meteorology

    Science.gov (United States)

    Kapochkina, A. B.; Kapochkin, B. B.; Kucherenko, N. V.

    The maximal interest is represented with the information from geostationary satellites. These satellites repeat shootings the chosen territories, allowing to study dynamics of images. Most interesting shootings in IR a range. Studying of survey image is applied to studying linear elements of clouds (LEC). It is established, that "LEC " arise only above breaks of an earth's crust. In research results of the complex analysis of the satellite data, hydrometeorological supervision, seismicity, supervision over deformations of a surface of the Earth are used. It is established that before formation "LEC " in a ground layer arise anomalies of temperature and humidity. The situation above Europe 16 May, 2001 is considered. "LEC " in Europe block carry of air weights from the west to the east. Synoptic conditions above the Great Britain July, 7-10, 2000 is considered. Moving "LEC" trace distribution of deformation waves to an earth's crust. Satellite shootings Europe before earthquake in Greece 14.08.2003 are considered. These days ground supervision were conducted and the data of the geostationary satellite were analyzed. During moving "LEC " occur failures (destruction houses & of gas mains), earthquake. The situation above Iberian peninsula 12-16.11.2001 is considered. "LEC" arose before flooding in Europe. The situation before flooding in Germany June, 6-8, 2002 and flooding on the river Kuban June, 16-23, 2002 is considered. In case of occurrence of tectonic compression of an earth's crust there are "LEC ", tracer intensive movements of air upwards and downwards above negative and positive anomalies of the form of a terrestrial surface, accordingly. Such meteorological situations are dangerous to flights of aircraft, the fast gravitational anomalies influencing into orbits of movement of satellites trace. The situation above equatorial Atlantic 26.03.2003 years is considered. At tectonic compression of continental scale overcast covers the whole continents for more

  8. New and Emerging Satellite Imaging Capabilities in Support of Safeguards

    International Nuclear Information System (INIS)

    Johnson, M.; Paquette, J.P.; Spyropoulos, N.; Rainville, L.; Schichor, P.; Hong, M.

    2015-01-01

    This abstract is focused on new and emerging commercial satellite imagery (CSI) capabilities. For more than a decade, experienced imagery analysts have been exploiting and analyzing CSI in support of the Department of Safeguards. As the remote sensing industry continues to evolve, additional CSI imagery types are becoming available that could enhance our ability to evaluate and verify States' declarations and to investigate the possible presence of undeclared activities. A newly available and promising CSI capability that may have a Safeguards application is Full Motion Video (FMV) imagery collection from satellites. For quite some time, FMV imagery has been collected from airborne platforms, but now FMV sensors are being deployed into space. Like its airborne counterpart, satellite FMV imagery could provide analysts with a great deal of information, including insight into the operational status of facilities and patterns of activity. From a Safeguards perspective, FMV imagery could help the Agency in the evaluation and verification of States' declared facilities and activities. There are advantages of FMV imaging capabilities that cannot be duplicated with other CSI capabilities, including the ability to loiter over areas of interest and the potential to revisit sites multiple times per day. Additional sensor capabilities applicable to the Safeguards mission include, but are not limited to, the following sensors: · Thermal Infrared imaging sensors will be launched in late 2014 to monitor operational status, e.g., heat from a transformer. · High resolution ShortWave Infrared sensors able to characterize materials that could support verification of Additional Protocol declarations under Article 2.a(v). · Unmanned Aerial Vehicles with individual sensors or specific sensor combinations. The Safeguards Symposium provides a forum to showcase and demonstrate safeguards applications for these emerging satellite imaging capabilities. (author)

  9. The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science

    Science.gov (United States)

    Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.

    2017-12-01

    The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.

  10. Ice Sheet Change Detection by Satellite Image Differencing

    Science.gov (United States)

    Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

    2010-01-01

    Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

  11. Estimation of urban surface water at subpixel level from neighborhood pixels using multispectral remote sensing image (Conference Presentation)

    Science.gov (United States)

    Xie, Huan; Luo, Xin; Xu, Xiong; Wang, Chen; Pan, Haiyan; Tong, Xiaohua; Liu, Shijie

    2016-10-01

    Water body is a fundamental element in urban ecosystems and water mapping is critical for urban and landscape planning and management. As remote sensing has increasingly been used for water mapping in rural areas, this spatially explicit approach applied in urban area is also a challenging work due to the water bodies mainly distributed in a small size and the spectral confusion widely exists between water and complex features in the urban environment. Water index is the most common method for water extraction at pixel level, and spectral mixture analysis (SMA) has been widely employed in analyzing urban environment at subpixel level recently. In this paper, we introduce an automatic subpixel water mapping method in urban areas using multispectral remote sensing data. The objectives of this research consist of: (1) developing an automatic land-water mixed pixels extraction technique by water index; (2) deriving the most representative endmembers of water and land by utilizing neighboring water pixels and adaptive iterative optimal neighboring land pixel for respectively; (3) applying a linear unmixing model for subpixel water fraction estimation. Specifically, to automatically extract land-water pixels, the locally weighted scatter plot smoothing is firstly used to the original histogram curve of WI image . And then the Ostu threshold is derived as the start point to select land-water pixels based on histogram of the WI image with the land threshold and water threshold determination through the slopes of histogram curve . Based on the previous process at pixel level, the image is divided into three parts: water pixels, land pixels, and mixed land-water pixels. Then the spectral mixture analysis (SMA) is applied to land-water mixed pixels for water fraction estimation at subpixel level. With the assumption that the endmember signature of a target pixel should be more similar to adjacent pixels due to spatial dependence, the endmember of water and land are determined

  12. Multispectral data compression through transform coding and block quantization

    Science.gov (United States)

    Ready, P. J.; Wintz, P. A.

    1972-01-01

    Transform coding and block quantization techniques are applied to multispectral aircraft scanner data, and digitized satellite imagery. The multispectral source is defined and an appropriate mathematical model proposed. The Karhunen-Loeve, Fourier, and Hadamard encoders are considered and are compared to the rate distortion function for the equivalent Gaussian source and to the performance of the single sample PCM encoder.

  13. DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. A. Azzaoui

    2016-06-01

    Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

  14. Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

    Science.gov (United States)

    Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

    2016-03-01

    The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care

  15. Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels

    Directory of Open Access Journals (Sweden)

    Mailys Lopes

    2017-07-01

    Full Text Available This paper deals with the classification of grasslands using high resolution satellite image time series. Grasslands considered in this work are semi-natural elements in fragmented landscapes, i.e., they are heterogeneous and small elements. The first contribution of this study is to account for grassland heterogeneity while working at the object level by modeling its pixels distributions by a Gaussian distribution. To measure the similarity between two grasslands, a new kernel is proposed as a second contribution: the α -Gaussian mean kernel. It allows one to weight the influence of the covariance matrix when comparing two Gaussian distributions. This kernel is introduced in support vector machines for the supervised classification of grasslands from southwest France. A dense intra-annual multispectral time series of the Formosat-2 satellite is used for the classification of grasslands’ management practices, while an inter-annual NDVI time series of Formosat-2 is used for old and young grasslands’ discrimination. Results are compared to other existing pixel- and object-based approaches in terms of classification accuracy and processing time. The proposed method is shown to be a good compromise between processing speed and classification accuracy. It can adapt to the classification constraints, and it encompasses several similarity measures known in the literature. It is appropriate for the classification of small and heterogeneous objects such as grasslands.

  16. Chagas disease study using satellite image processing: A Bolivian case

    Science.gov (United States)

    Vargas-Cuentas, Natalia I.; Roman-Gonzalez, Avid; Mantari, Alicia Alva; Muñoz, Luis AnthonyAucapuma

    2018-03-01

    Remote sensing is the technology that has enabled us to obtain information about the Earth's surface without directly contacting it. For this reason, currently, the Bolivian state has considered a list of interesting applications of remote sensing in the country, including the following: biodiversity and environment monitoring, mining and geology, epidemiology, agriculture, water resources and land use planning. The use of satellite images has become a great tool for epidemiology because with this technological advance we can determine the environment in which transmission occurs, the distribution of the disease and its evolution over time. In that context, one of the important diseases related to public health in Bolivia is Chagas disease, also known as South American Trypanosomiasis. Chagas is caused by a blood-sucking bug or Vinchuca, which causes serious intestinal and heart long term problems and affects 33.4% of the Bolivian population. This disease affects mostly humble people, so the Bolivian state invests millions of dollars to acquire medicine and distribute it for free. Due to the above reasons, the present research aims to analyze some areas of Bolivia using satellite images for developing an epidemiology study. The primary objective is to understand the environment in which the transmission of the disease happens, and the climatic conditions under which occurs, observe the behavior of the blood-sucking bug, identify in which months occur higher outbreaks, in which months the bug leaves its eggs, and under which weather conditions this happens. All this information would be contrasted with information extracted from the satellite images and data from the Ministry of Health, and the Institute of Meteorology in Bolivia. All this data will allow us to have a more integrated understanding of this disease and promote new possibilities to prevent and control it.

  17. Quantification of amyloid deposits and oxygen extraction fraction in the brain with multispectral optoacoustic imaging in arcAβ mouse model of Alzheimer's disease

    Science.gov (United States)

    Ni, Ruiqing; Vaas, Markus; Rudin, Markus; Klohs, Jan

    2018-02-01

    Beta-amyloid (Aβ) deposition and vascular dysfunction are important contributors to the pathogenesis in Alzheimer's disease (AD). However, the spatio-temporal relationship between an altered oxygen metabolism and Aβ deposition in the brain remains elusive. Here we provide novel in-vivo estimates of brain Aβ load with Aβ-binding probe CRANAD-2 and measures of brain oxygen saturation by using multi-spectral optoacoustic imaging (MSOT) and perfusion imaging with magnetic resonance imaging (MRI) in arcAβ mouse models of AD. We demonstrated a decreased cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) in the cortical region of the arcAβ mice compared to wildtype littermates at 24 months. In addition, we showed proof-of-concept for the detection of cerebral Aβ deposits in brain from arcAβ mice compared to wild-type littermates.

  18. Multispectral Palmprint Recognition Using a Quaternion Matrix

    Directory of Open Access Journals (Sweden)

    Yafeng Li

    2012-04-01

    Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

  19. Global Solar Radiation in Spain from Satellite Images

    International Nuclear Information System (INIS)

    Ramirez, L.; Mora, L.; Sidrach de Cardona, M.; Navarro, A. A.; Varela, M.; Cruz, M. de la

    2003-01-01

    In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been reevaluated to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar, impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyrano metric measures in a concrete locality, but it provides a very valid indicator in places in which it is not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs

  20. Discovering significant evolution patterns from satellite image time series.

    Science.gov (United States)

    Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

    2011-12-01

    Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

  1. Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  2. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA from 2003-08-26 to 2012-05-03 (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  3. Ship-Iceberg Discrimination in Sentinel-2 Multispectral Imagery by Supervised Classification

    Directory of Open Access Journals (Sweden)

    Peder Heiselberg

    2017-11-01

    Full Text Available The European Space Agency Sentinel-2 satellites provide multispectral images with pixel sizes down to 10 m. This high resolution allows for fast and frequent detection, classification and discrimination of various objects in the sea, which is relevant in general and specifically for the vast Arctic environment. We analyze several sets of multispectral image data from Denmark and Greenland fall and winter, and describe a supervised search and classification algorithm based on physical parameters that successfully finds and classifies all objects in the sea with reflectance above a threshold. It discriminates between objects like ships, islands, wakes, and icebergs, ice floes, and clouds with accuracy better than 90%. Pan-sharpening the infrared bands leads to classification and discrimination of ice floes and clouds better than 95%. For complex images with abundant ice floes or clouds, however, the false alarm rate dominates for small non-sailing boats.

  4. Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

    Science.gov (United States)

    Su, X.

    2017-12-01

    A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

  5. An interdisciplinary analysis of multispectral satellite data for selected cover types in the Colorado Mountains, using automatic data processing techniques. [geological lineaments and mineral exploration

    Science.gov (United States)

    Hoffer, R. M. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. One capability which has been recognized by many geologists working with space photography is the ability to see linear features and alinements which were previously not apparent. To the exploration geologist, major lineaments seen on satellite images are of particular interest. A portion of ERTS-1 frame 1407-17193 (3 Sept. 1973) was used for mapping lineaments and producing an iso-lineament intersection map. Skylab photography over the area of prime area was not useable due to snow cover. Once the lineaments were mapped, a grid with 2.5 km spacing was overlayed on the map and the lineament intersections occurring within each grid square were counted and the number plotted in the center of the grid square. These numbers were then contoured producing a contour map of equal lineament intersection. It is believed that the areas of high intersection concentration would be the most favorable area for ore mineralization if favorable host rocks are also present. These highly fractured areas would act as conduits for carrying the ore forming solutions to the site of deposition in a favorable host rock. Two of the six areas of high intersection concentration are over areas of present or past mining camps and small claims are known to exist near the others. These would be prime target areas for future mineral exploration.

  6. Use of satellite images for the monitoring of water systems

    Science.gov (United States)

    Hillebrand, Gudrun; Winterscheid, Axel; Baschek, Björn; Wolf, Thomas

    2015-04-01

    Satellite images are a proven source of information for monitoring ecological indicators in coastal waters and inland river systems. This potential of remote sensing products was demonstrated by recent research projects (e.g. EU-funded project Freshmon - www.freshmon.eu) and other activities by national institutions. Among indicators for water quality, a particular focus was set on the temporal and spatial dynamics of suspended particulate matter (SPM) and Chlorophyll-a (Chl-a). The German Federal Institute of Hydrology (BfG) was using the Weser and Elbe estuaries as test cases to compare in-situ measurements with results obtained from a temporal series of automatically generated maps of SPM distributions based on remote sensing data. Maps of SPM and Chl-a distributions in European inland rivers and alpine lakes were generated by the Freshmon Project. Earth observation based products are a valuable source for additional data that can well supplement in-situ monitoring. For 2015, the BfG and the Institute for Lake Research of the State Institute for the Environment, Measurements and Nature Conservation of Baden-Wuerttemberg, Germany (LUBW) are in the process to start implementing an operational service for monitoring SPM and Chl-a based on satellite images (Landsat 7 & 8, Sentinel 2, and if required other systems with higher spatial resolution, e.g. Rapid Eye). In this 2-years project, which is part of the European Copernicus Programme, the operational service will be set up for - the inland rivers of Rhine and Elbe - the North Sea estuaries of Elbe, Weser and Ems. Furthermore - Lake Constance and other lakes located within the Federal State of Baden-Wuerttemberg. In future, the service can be implemented for other rivers and lakes as well. Key feature of the project is a data base that holds the stock of geo-referenced maps of SPM and Chl-a distributions. Via web-based portals (e.g. GGInA - geo-portal of the BfG; UIS - environmental information system of the

  7. Laser Guidestar Satellite for Ground-based Adaptive Optics Imaging of Geosynchronous Satellites and Astronomical Targets

    Science.gov (United States)

    Marlow, W. A.; Cahoy, K.; Males, J.; Carlton, A.; Yoon, H.

    2015-12-01

    Real-time observation and monitoring of geostationary (GEO) satellites with ground-based imaging systems would be an attractive alternative to fielding high cost, long lead, space-based imagers, but ground-based observations are inherently limited by atmospheric turbulence. Adaptive optics (AO) systems are used to help ground telescopes achieve diffraction-limited seeing. AO systems have historically relied on the use of bright natural guide stars or laser guide stars projected on a layer of the upper atmosphere by ground laser systems. There are several challenges with this approach such as the sidereal motion of GEO objects relative to natural guide stars and limitations of ground-based laser guide stars; they cannot be used to correct tip-tilt, they are not point sources, and have finite angular sizes when detected at the receiver. There is a difference between the wavefront error measured using the guide star compared with the target due to cone effect, which also makes it difficult to use a distributed aperture system with a larger baseline to improve resolution. Inspired by previous concepts proposed by A.H. Greenaway, we present using a space-based laser guide starprojected from a satellite orbiting the Earth. We show that a nanosatellite-based guide star system meets the needs for imaging GEO objects using a low power laser even from 36,000 km altitude. Satellite guide star (SGS) systemswould be well above atmospheric turbulence and could provide a small angular size reference source. CubeSatsoffer inexpensive, frequent access to space at a fraction of the cost of traditional systems, and are now being deployed to geostationary orbits and on interplanetary trajectories. The fundamental CubeSat bus unit of 10 cm cubed can be combined in multiple units and offers a common form factor allowing for easy integration as secondary payloads on traditional launches and rapid testing of new technologies on-orbit. We describe a 6U CubeSat SGS measuring 10 cm x 20 cm x

  8. Satellite image time series simulation for environmental monitoring

    Science.gov (United States)

    Guo, Tao

    2014-11-01

    The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

  9. CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

    Directory of Open Access Journals (Sweden)

    K.-Y. Lee

    2016-06-01

    Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate

  10. Cloud Detection of Optical Satellite Images Using Support Vector Machine

    Science.gov (United States)

    Lee, Kuan-Yi; Lin, Chao-Hung

    2016-06-01

    Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

  11. Analysis of optical proprieties of the water reservoir Rodolfo Costa e Silva – Itaara, RS, Brazil, with field spectral data and orbital multispectral images

    Directory of Open Access Journals (Sweden)

    Waterloo Pereira Filho

    2007-08-01

    Full Text Available An evaluation of the discrimination of water classes using continuum removal technique applied over spectral data obtained in field and multispectral images classification is presented. The study area was the Rodolfo Costa e Silva water reservoir, located in central region of Rio Grande do Sul (RS State, in Southern region of Brazil. The methodology was based on in situ data collection of: total suspended solids, chlorophyll (a, b and c, water transparency, and bidirectional spectral reflectance. These data were collected in 21 point (samples in May 16, 2006. The continuum removal technique was applied on the spectral data over 4 absorption bands: 400-550nm, 610-640nm, 650-680nm e 580-700nm. The continuum removal parameters analyzed for each absorption band were: depth, area and width. The multispectral images used were CBERS-2/CCD and Landsat 5/TM. The images were acquired in a date nearest to field work and with appropriate weather conditions. These images were corrected by removing atmospheric effects and then classified. According to the results obtained from the continuum removal technique, it was verified that band depth, area and width did not present a good potential to separate different water classes. Digital classification results did not show significant correlations with the limnological parameters collected in field and, therefore, could not be used to characterize spectrally different water classes or compartments. The main problem of establishing relationships between spectral reflectance and water quality parameters was due to the low variability of optical components in the water of Rodolfo Costa e Silva Reservoir. In this case the spectral analyses (considering both techniques were not sensitive to the relative small variations observed in field data.

  12. Spatial Co-Registration of Ultra-High Resolution Visible, Multispectral and Thermal Images Acquired with a Micro-UAV over Antarctic Moss Beds

    Directory of Open Access Journals (Sweden)

    Darren Turner

    2014-05-01

    Full Text Available In recent times, the use of Unmanned Aerial Vehicles (UAVs as tools for environmental remote sensing has become more commonplace. Compared to traditional airborne remote sensing, UAVs can provide finer spatial resolution data (up to 1 cm/pixel and higher temporal resolution data. For the purposes of vegetation monitoring, the use of multiple sensors such as near infrared and thermal infrared cameras are of benefit. Collecting data with multiple sensors, however, requires an accurate spatial co-registration of the various UAV image datasets. In this study, we used an Oktokopter UAV to investigate the physiological state of Antarctic moss ecosystems using three sensors: (i a visible camera (1 cm/pixel, (ii a 6 band multispectral camera (3 cm/pixel, and (iii a thermal infrared camera (10 cm/pixel. Imagery from each sensor was geo-referenced and mosaicked with a combination of commercially available software and our own algorithms based on the Scale Invariant Feature Transform (SIFT. The validation of the mosaic’s spatial co-registration revealed a mean root mean squared error (RMSE of 1.78 pixels. A thematic map of moss health, derived from the multispectral mosaic using a Modified Triangular Vegetation Index (MTVI2, and an indicative map of moss surface temperature were then combined to demonstrate sufficient accuracy of our co-registration methodology for UAV-based monitoring of Antarctic moss beds.

  13. A Direct and Fast Methodology for Ship Recognition in Sentinel-2 Multispectral Imagery

    Directory of Open Access Journals (Sweden)

    Henning Heiselberg

    2016-12-01

    Full Text Available The European Space Agency satellite Sentinel-2 provides multispectral images with pixel sizes down to 10 m. This high resolution allows for ship detection and recognition by determining a number of important ship parameters. We are able to show how a ship position, its heading, length and breadth can be determined down to a subpixel resolution. If the ship is moving, its velocity can also be determined from its Kelvin waves. The 13 spectrally different visual and infrared images taken using multispectral imagery (MSI are “fingerprints” that allow for the recognition and identification of ships. Furthermore, the multispectral image profiles along the ship allow for discrimination between the ship, its turbulent wakes, and the Kelvin waves, such that the ship’s length and breadth can be determined more accurately even when sailing. The ship’s parameters are determined by using satellite imagery taken from several ships, which are then compared to known values from the automatic identification system. The agreement is on the order of the pixel resolution or better.

  14. Accuracy assessment of topographic mapping using UAV image integrated with satellite images

    International Nuclear Information System (INIS)

    Azmi, S M; Ahmad, Baharin; Ahmad, Anuar

    2014-01-01

    Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps

  15. Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

    Directory of Open Access Journals (Sweden)

    Maocai Wang

    2014-01-01

    Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

  16. Galileo's first images of Jupiter and the Galilean satellites

    Science.gov (United States)

    Belton, M.J.S.; Head, J. W.; Ingersoll, A.P.; Greeley, R.; McEwen, A.S.; Klaasen, K.P.; Senske, D.; Pappalardo, R.; Collins, G.; Vasavada, A.R.; Sullivan, R.; Simonelli, D.; Geissler, P.; Carr, M.H.; Davies, M.E.; Veverka, J.; Gierasch, P.J.; Banfield, D.; Bell, M.; Chapman, C.R.; Anger, C.; Greenberg, R.; Neukum, G.; Pilcher, C.B.; Beebe, R.F.; Burns, J.A.; Fanale, F.; Ip, W.; Johnson, T.V.; Morrison, D.; Moore, J.; Orton, G.S.; Thomas, P.; West, R.A.

    1996-01-01

    The first images of Jupiter, Io, Europa, and Ganymede from the Galileo spacecraft reveal new information about Jupiter's Great Red Spot (GRS) and the surfaces of the Galilean satellites. Features similar to clusters of thunderstorms were found in the GRS. Nearby wave structures suggest that the GRS may be a shallow atmospheric feature. Changes in surface color and plume distribution indicate differences in resurfacing processes near hot spots on lo. Patchy emissions were seen while Io was in eclipse by Jupiter. The outer margins of prominent linear markings (triple bands) on Europa are diffuse, suggesting that material has been vented from fractures. Numerous small circular craters indicate localized areas of relatively old surface. Pervasive brittle deformation of an ice layer appears to have formed grooves on Ganymede. Dark terrain unexpectedly shows distinctive albedo variations to the limit of resolution.

  17. Dsm Based Orientation of Large Stereo Satellite Image Blocks

    Science.gov (United States)

    d'Angelo, P.; Reinartz, P.

    2012-07-01

    High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.

  18. Images of war: using satellite images for human rights monitoring in Turkish Kurdistan.

    Science.gov (United States)

    de Vos, Hugo; Jongerden, Joost; van Etten, Jacob

    2008-09-01

    In areas of war and armed conflict it is difficult to get trustworthy and coherent information. Civil society and human rights groups often face problems of dealing with fragmented witness reports, disinformation of war propaganda, and difficult direct access to these areas. Turkish Kurdistan was used as a case study of armed conflict to evaluate the potential use of satellite images for verification of witness reports collected by human rights groups. The Turkish army was reported to be burning forests, fields and villages as a strategy in the conflict against guerrilla uprising. This paper concludes that satellite images are useful to validate witness reports of forest fires. Even though the use of this technology for human rights groups will depend on some feasibility factors such as prices, access and expertise, the images proved to be key for analysis of spatial aspects of conflict and valuable for reconstructing a more trustworthy picture.

  19. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  20. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  1. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  2. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  3. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  4. Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  5. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...