Sample records for satellite image processing

  1. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee


    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.


    Directory of Open Access Journals (Sweden)

    A. H. Ahrari


    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.


    Directory of Open Access Journals (Sweden)

    T. Sree Sharmila


    Full Text Available Satellite images are corrupted by noise in its acquisition and transmission. The removal of noise from the image by attenuating the high frequency image components, removes some important details as well. In order to retain the useful information and improve the visual appearance, an effective denoising and resolution enhancement techniques are required. In this research, Hybrid Directional Lifting (HDL technique is proposed to retain the important details of the image and improve the visual appearance. The Discrete Wavelet Transform (DWT based interpolation technique is developed for enhancing the resolution of the denoised image. The performance of the proposed techniques are tested by Land Remote-Sensing Satellite (LANDSAT images, using the quantitative performance measure, Peak Signal to Noise Ratio (PSNR and computation time to show the significance of the proposed techniques. The PSNR of the HDL technique increases 1.02 dB compared to the standard denoising technique and the DWT based interpolation technique increases 3.94 dB. From the experimental results it reveals that newly developed image denoising and resolution enhancement techniques improve the image visual quality with rich textures.

  4. Image Processing Technique for Automatic Detection of Satellite Streaks (United States)


    satellites actifs et d’autres débris doivent être contrôlées. Dans ces cas, les paramètres orbitaux sont connus, mais après un certain temps cette...artéfacts de capteur (tel que des pixels morts, gradient de fond, bruit) et dégradation du signal (coulage, éblouissement, saturation, etc...Cette étude explique comment les artéfacts du capteur peuvent être corrigés, le fond de l’image enlevé et le bruit partiellement effacé. Puis, elle

  5. Digital image processing for the earth resources technology satellite data. (United States)

    Will, P. M.; Bakis, R.; Wesley, M. A.


    This paper discusses the problems of digital processing of the large volumes of multispectral image data that are expected to be received from the ERTS program. Correction of geometric and radiometric distortions are discussed and a byte oriented implementation is proposed. CPU timing estimates are given for a System/360 Model 67, and show that a processing throughput of 1000 image sets per week is feasible.

  6. Satellite Image Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare


    Full Text Available In this paper, urban growth of Bangalore region is analyzed and discussed by using multi-temporal and multi-spectral Landsat satellite images. Urban growth analysis helps in understanding the change detection of Bangalore region. The change detection is studied over a period of 39 years and the region of interest covers an area of 2182 km2. The main cause for urban growth is the increase in population. In India, rapid urbanization is witnessed due to an increase in the population, continuous development has affected the existence of natural resources. Therefore observing and monitoring the natural resources (land use plays an important role. To analyze changed detection, researcher’s use remote sensing data. Continuous use of remote sensing data helps researchers to analyze the change detection. The main objective of this study is to monitor land cover changes of Bangalore district which covers rural and urban regions using multi-temporal and multi-sensor Landsat - multi-spectral scanner (MSS, thematic mapper (TM, Enhanced Thematic mapper plus (ETM+ MSS, TM and ETM+ images captured in the years 1973, 1992, 1999, 2002, 2005, 2008 and 2011. Temporal changes were determined by using maximum likelihood classification method. The classification results contain four land cover classes namely, built-up, vegetation, water and barren land. The results indicate that the region is densely developed which has resulted in decrease of water and vegetation regions. The continuous transformation of barren land to built-up region has affected water and vegetation regions. Generally, from 1973 to 2011 the percentage of urban region has increased from 4.6% to 25.43%, mainly due to urbanization.

  7. Satellite Imagery Cadastral Features Extractions using Image Processing Algorithms: A Viable Option for Cadastral Science

    Directory of Open Access Journals (Sweden)

    Usman Babawuro


    Full Text Available Satellite images are used for feature extraction among other functions. They are used to extract linear features, like roads, etc. These linear features extractions are important operations in computer vision. Computer vision has varied applications in photogrammetric, hydrographic, cartographic and remote sensing tasks. The extraction of linear features or boundaries defining the extents of lands, land covers features are equally important in Cadastral Surveying. Cadastral Surveying is the cornerstone of any Cadastral System. A two dimensional cadastral plan is a model which represents both the cadastral and geometrical information of a two dimensional labeled Image. This paper aims at using and widening the concepts of high resolution Satellite imagery data for extracting representations of cadastral boundaries using image processing algorithms, hence minimizing the human interventions. The Satellite imagery is firstly rectified hence establishing the satellite imagery in the correct orientation and spatial location for further analysis. We, then employ the much available Satellite imagery to extract the relevant cadastral features using computer vision and image processing algorithms. We evaluate the potential of using high resolution Satellite imagery to achieve Cadastral goals of boundary detection and extraction of farmlands using image processing algorithms. This method proves effective as it minimizes the human demerits associated with the Cadastral surveying method, hence providing another perspective of achieving cadastral goals as emphasized by the UN cadastral vision. Finally, as Cadastral science continues to look to the future, this research aimed at the analysis and getting insights into the characteristics and potential role of computer vision algorithms using high resolution satellite imagery for better digital Cadastre that would provide improved socio economic development.

  8. Optimization of post-classification processing of high-resolution satellite image: A case study

    Institute of Scientific and Technical Information of China (English)

    DONG; Rencai; DONG; Jiajia; WU; Gang; DENG; Hongbing


    The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 rn resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of

  9. Pre-processing Algorithm for Rectification of Geometric Distortions in Satellite Images

    Directory of Open Access Journals (Sweden)

    Narayan Panigrahi


    Full Text Available A number of algorithms have been reported to process and remove geometric distortions in satellite images. Ortho-correction, geometric error correction, radiometric error removal, etc are a few important examples. These algorithm require supplementary meta-information of the satellite images such as ground control points and correspondence, sensor orientation details, elevation profile of the terrain, etc to establish corresponding transformations. In this paper, a pre-processing algorithm has been proposed which removes systematic distortions of a satellite image and thereby removes the blank portion of the image. It is an input-to-output mapping of image pixels, where the transformation computes the coordinate of each output pixel corresponding to the input pixel of an image. The transformation is established by the exact amount of scaling, rotation and translation needed for each pixel in the input image so that the distortion induced during the recording stage is corrected.Defence Science Journal, 2011, 61(2, pp.174-179, DOI:

  10. Quantitative analysis of geomorphic processes using satellite image data at different scales (United States)

    Williams, R. S., Jr.


    When aerial and satellite photographs and images are used in the quantitative analysis of geomorphic processes, either through direct observation of active processes or by analysis of landforms resulting from inferred active or dormant processes, a number of limitations in the use of such data must be considered. Active geomorphic processes work at different scales and rates. Therefore, the capability of imaging an active or dormant process depends primarily on the scale of the process and the spatial-resolution characteristic of the imaging system. Scale is an important factor in recording continuous and discontinuous active geomorphic processes, because what is not recorded will not be considered or even suspected in the analysis of orbital images. If the geomorphic process of landform change caused by the process is less than 200 m in x to y dimension, then it will not be recorded. Although the scale factor is critical, in the recording of discontinuous active geomorphic processes, the repeat interval of orbital-image acquisition of a planetary surface also is a consideration in order to capture a recurring short-lived geomorphic process or to record changes caused by either a continuous or a discontinuous geomorphic process.

  11. A novel super resolution scheme to acquire and process satellite images (United States)

    Yin, Dong-yu; Su, Xiao-feng; Lin, Jian-chun; Wang, Gan-quan; Kuang, Ding-bo


    Geosynchronous satellite has obvious limitations for the weight and the scale of payloads, and large aperture optical system is not permitted. The optical diffraction limit of small aperture optical system has an adverse impact on the resolution of the acquired images. Therefore, how to get high resolution images using super-resolution technique with the acquired low resolution images becomes a popular problem investigated by researchers. Here, we present a novel scheme to acquire low resolution images and process them to achieve a high resolution image. Firstly, to acquire low resolution images, we adopt a special arrangement pattern of four CCD staggered arrays on the focal plane in the remote sensing satellite framework .These four CCD linear arrays are parallelized with a 0.25√2 pixel shift along the CCD direction and a 1.25 pixel shift along the scanning direction. The rotation angle between the two directions is 45 degree. The tilting sampling mode and the special arrangement pattern allow the sensor to acquire images with a smaller sampling interval which can give the resolution a greater enhancement. Secondly, to reconstruct a high resolution image of pretty good quality with a magnification factor 4, we propose a novel algorithm based on the iterative-interpolation super resolution algorithm (IISR) and the new edge-directed interpolation algorithm (NEDI). The new algorithm makes a critical improvement to NEDI and introduces it into the multi-frame interpolation in IISR. The algorithm can preserve the edges well and requires a relatively small number of low-resolution images to achieve better reconstruction accuracy .In the last part of the paper, we carry out a simulation experiment, and use MSE as the quality measure. The results demonstrate that our new scheme substantially improves the image resolution with both better quantitative quality and visual quality compared with some previous normal methods.

  12. Image-processing techniques in precisely measuring positions of Saturn and its satellites

    Institute of Scientific and Technical Information of China (English)

    PENG; Qingyu; (彭青玉)


    After overcoming the deficiencies of previous image-processing techniques, a novel technique based on the edge-detection of Saturnian ring is developed to precisely measure Saturn's position. Furthermore, the scattering light (i.e. halo light) of Saturn and its ring is removed effectively based on its center symmetry. Therefore, we have much more opportunities to accurately measure the positions of Mimas and Enceladus-- two satellites very close to the Saturn. Experimental tests with 127 frames of CCD images obtained on the 1-meter telescope at the Yunnan Observatory over three nights show that the geometric center of the Saturnian ring and its 4 satellites (Tethys, Dione, Rhea and Titan) have the same positional precision, and the standard error for a single observation is less than ±0.05 arcsec. It is believed that these new techniques would have important impetus to the positional measurement of both Saturn by using a CCD meridian instrument and its faint satellites by using a long focal length telescope.

  13. Online self-service processing system of ZY-3 satellite: a prospective study of image cloud services (United States)

    Wang, Hongyan; Wang, Huabin; Shi, Shaoyu


    The strong demands for satellite images are increasing not only in professional fields, but also in the non-professionals. But the online map services with up-to-date satellite images can serve few demands. One challenge is how to provide online processing service, which need to handle real-time online data-intensive geospatial computation and visualization. Under the background of the development of cloud computing technology, the problem can be figured out partly. The other challenge is how to implement user-customized online processing without professional background and knowledge. An online self-service processing system of ZY-3 Satellite images is designed to implement an on-demand service mode in this paper. It will work with only some simple parameters being set up for the non-professionals without having to care about the specific processing steps. And the professionals can assemble the basic processing services to a service chain, which can work out a more complex processing and a better result. This intelligent self-service online system for satellite images processing, which is called the prototype of satellite image cloud service in this paper, is accelerated under the development of cloud computing technology and researches on data-intensive computing. To realize the goal, the service mode and framework of the online self-service processing system of ZY-3 Satellite images are figured out in this paper. The details of key technologies are also discussed, including user space virtualization management, algorithm-level parallel image processing, image service chain construction, etc. And the experimental system is built up as a prospective study of image cloud services.

  14. Analysis Of Usefulness Of Satellite Image Processing Methods For Investigations Of Cultural Heritage Resources (United States)

    Osińska-Skotak, Katarzyna; Zapłata, Rafał


    The paper presents the analysis of usefulness of WorldView-2 satellite image processing, which enhance information concerning the cultural heritage objects. WorldView-2 images are characterised by the very high spatial resolution and high spectral resolution; that is why they create new possibilities for many applications, including investigations of the cultural heritage. The vicinities of Iłża have been selected as the test site for presented investigations. The presented results of works are the effect of research works, which were performed in the frames of the scientific project "Utilisation of laser scanning and remote sensing in protection, investigations and inventory of the cultural heritage. Development of non-invasive, digital methods of documenting and recognising the architectural and archaeological heritage", as the part of "The National Programme for the Development of Humanities" of the Minister of Science and Higher Education in the period of 2012-2015.

  15. A learning tool for optical and microwave satellite image processing and analysis (United States)

    Dashondhi, Gaurav K.; Mohanty, Jyotirmoy; Eeti, Laxmi N.; Bhattacharya, Avik; De, Shaunak; Buddhiraju, Krishna M.


    This paper presents a self-learning tool, which contains a number of virtual experiments for processing and analysis of Optical/Infrared and Synthetic Aperture Radar (SAR) images. The tool is named Virtual Satellite Image Processing and Analysis Lab (v-SIPLAB) Experiments that are included in Learning Tool are related to: Optical/Infrared - Image and Edge enhancement, smoothing, PCT, vegetation indices, Mathematical Morphology, Accuracy Assessment, Supervised/Unsupervised classification etc.; Basic SAR - Parameter extraction and range spectrum estimation, Range compression, Doppler centroid estimation, Azimuth reference function generation and compression, Multilooking, image enhancement, texture analysis, edge and detection. etc.; SAR Interferometry - BaseLine Calculation, Extraction of single look SAR images, Registration, Resampling, and Interferogram generation; SAR Polarimetry - Conversion of AirSAR or Radarsat data to S2/C3/T3 matrix, Speckle Filtering, Power/Intensity image generation, Decomposition of S2/C3/T3, Classification of S2/C3/T3 using Wishart Classifier [3]. A professional quality polarimetric SAR software can be found at [8], a part of whose functionality can be found in our system. The learning tool also contains other modules, besides executable software experiments, such as aim, theory, procedure, interpretation, quizzes, link to additional reading material and user feedback. Students can have understanding of Optical and SAR remotely sensed images through discussion of basic principles and supported by structured procedure for running and interpreting the experiments. Quizzes for self-assessment and a provision for online feedback are also being provided to make this Learning tool self-contained. One can download results after performing experiments.

  16. Satellite Image Edge Detection for Population Distribution Pattern Identification using Levelset with Morphological Filtering Process (United States)

    Harsiti; Munandar, T. A.; Suhendar, A.; Abdullah, A. G.; Rohendi, D.


    Population distribution pattern is directly related with economic gap of a region. Analysis of population distribution pattern is usually performed by studying statistical data on population. This study aimed to analyze population distribution pattern using image analysis concept, i.e. using satellite images. Levelset and morphological image filtering methods were used to analyze images to see distribution pattern. The research result showed that Levelset and morphological image filtering could remove a lot of noises in analysis result images and form object edge contours very clearly. The detected object contours were used as references to recognize population distribution pattern based on satellite image analysis. The pattern made based on the research result didn’t show optimal result because Levelset performed image segmentation based on the contours of the analyzed objects. Other segmentation methods should be combined with it to produce clearer population distribution pattern.

  17. Shadow imaging of geosynchronous satellites (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. Image and Processing Models for Satellite Detection in Images Acquired by Space-based Surveillance-of-Space Sensors (United States)


    software. Résumé …..... Dans le cadre de la surveillance de l’espace, les objets spatiaux connus en orbite (OSO), i.e., satellites actifs ou débris...SAPPHIRE et NEOSSat. Ce document contient des modèles qui décrivent la formation des images et le processus d’acquisition de capteurs , basés au sol ou dans

  19. Geostationary Satellite (GOES) Images (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...

  20. Processing of Satellite Digital Images for Mapping Atmospheric Transmissivity in Bangladesh

    Directory of Open Access Journals (Sweden)

    Md Shahjahan Ali


    Full Text Available This study investigates the potential of determining atmospheric transmissivity (τ from NOAA-AVHRR satellite images using a simple methodology. Using this method, hourly transmissivity values over the land surface area of Bangladesh has been determined. The spatio-temporal distribution of τ has been studied by constructing monthly average maps for the whole country for one complete year (February 2005 to January 2006. Yearly average map has been prepared by integrating monthly average maps. Geographical distribution of τ exhibits patterns and trends. It is observed that the value of τ varies from 0.3 to 0.65 with the average maximum value in the month of April and minimum value in the month of November. It is also observed that for western parts of the country, which is the drought prone area, transmissivity values are little bit higher than that at the eastern parts. Relatively lower values of τ in the dry months (November to January may be due to the effect of particulate or chemical pollution in the atmosphere.

  1. Biogeography based Satellite Image Classification

    CERN Document Server

    Panchal, V K; Kaur, Navdeep; Kundra, Harish


    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  2. Satellite image processing for precision agriculture and agroindustry using convolutional neural network and genetic algorithm (United States)

    Firdaus; Arkeman, Y.; Buono, A.; Hermadi, I.


    Translating satellite imagery to a useful data for decision making during this time are usually done manually by human. In this research, we are going to translate satellite imagery by using artificial intelligence method specifically using convolutional neural network and genetic algorithm to become a useful data for decision making, especially for precision agriculture and agroindustry. In this research, we are focused on how to made a sustainable land use planning with 3 objectives. The first is maximizing economic factor. Second is minimizing CO2 emission and the last is minimizing land degradation. Results show that by using artificial intelligence method, can produced a good pareto optimum solutions in a short time.

  3. Study of time-lapse processing for dynamic hydrologic conditions. [electronic satellite image analysis console for Earth Resources Technology Satellites imagery (United States)

    Serebreny, S. M.; Evans, W. E.; Wiegman, E. J.


    The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies.

  4. Predictive estimation of upward pollutant migration during shale gas production using satellite image processing (United States)

    Lyalko, Vadim; Azimov, Oleksandr; Yakovlev, Yevgen


    The report considers the relevance of the application of modern remote aerospace and hydrogeological methods in the problems of the ecological safety for the hydrosphere during shale gas production in Ukraine. Case studies of pilot implementation of these methods are present for the Bilyaivska area adjacent to the Yuzivka licensed site within the Dnieper-Donets Depression. A number of the hydrogeological filtration parameters and the thematic processing for remote sensing data of the Earth enable to obtain the rough estimate of the temporal indices for the upward pollutant migration from the fracturing zone to the groundwater aquifers in the potential process of shale gas production (as an example the 400-Bilyaivska well). It is found that the possible variety of the active permeability in tectonic zone, which may be predicted by using remote sensing of the Earth image interpretation in vicinity of the well, is responsible for the passage time of pollution from the fracturing zone level to the groundwater aquifers one and this time interval spans 50˜5 years.

  5. Evaluation of Development and Changes in Land Use using Different Satellite Image Processing and Remote Sensing Techniques (Case Study: Kermanshah, Iran)



    Currently the largest city in the western Iran, Kermanshah enjoys fast growing trend because of its strategic location. Remote sensing and satellite imagery are well suited for assessing the changes in land use over different time periods. In this study, satellite images from Landsat TM sensor and ETM sensor have been prepared during 1987 and 2007 as geometric and radiometric corrections have been made to them. The process was followed by selecting the best combination of false color by using...

  6. Fuzzy rule-based model for optimum orientation of solar panels using satellite image processing (United States)

    Zaher, A.; N'goran, Y.; Thiery, F.; Grieu, S.; Traoré, A.


    In solar energy converting systems, a particular attention is paid to the orientation of solar collectors in order to optimize the overall system efficiency. In this context, the collectors can be fixed or oriented by a continuous solar tracking system. The proposed approach is based on METEOSAT images processing in order to detect the cloud coverage and its duration. These two parameters are treated by a fuzzy inference system deciding the optimal position of the solar panel. In fact, three weather cases can be considered: clear, partly covered or overcast sky. In the first case, the direct sunlight is more important than the diffuse radiation, thus the panel is always pointed towards the sun. In the overcast case, the solar beam is close to zero and the panel is placed horizontally to receive the diffuse radiation. Under partly covered conditions, the fuzzy inference system decides which of the previous positions is more efficient. The proposed approach is implemented using experimental prototype located in Perpignan (France). On a period of 17 months, the results are very satisfactory, with power gains of up to 23 % compared to the collectors oriented by a continuous solar tracking.

  7. System refinement for content based satellite image retrieval

    Directory of Open Access Journals (Sweden)

    NourElDin Laban


    Full Text Available We are witnessing a large increase in satellite generated data especially in the form of images. Hence intelligent processing of the huge amount of data received by dozens of earth observing satellites, with specific satellite image oriented approaches, presents itself as a pressing need. Content based satellite image retrieval (CBSIR approaches have mainly been driven so far by approaches dealing with traditional images. In this paper we introduce a novel approach that refines image retrieval process using the unique properties to satellite images. Our approach uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tiling sizes. Accordingly the system uses these multilevel features within a multilevel retrieval system that refines the retrieval process. Our multilevel refinement approach has been experimentally validated against the conventional one yielding enhanced precision and recall rates.

  8. Image processing

    NARCIS (Netherlands)

    Heijden, van der F.; Spreeuwers, L.J.; Blanken, H.M.; Vries de, A.P.; Blok, H.E.; Feng, L


    The field of image processing addresses handling and analysis of images for many purposes using a large number of techniques and methods. The applications of image processing range from enhancement of the visibility of cer- tain organs in medical images to object recognition for handling by industri

  9. Smoothing of Fused Spectral Consistent Satellite Images

    DEFF Research Database (Denmark)

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


    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...

  10. Low-Cost Satellite Infrared Imager Study (United States)


    2,297.00 10 MATLAB , Simulink , Symbolic Math Toolbox (2 ea @ £894) £1,788.00 11 MATLAB Image Processing Toolbox (2 ea at £192) £384.00 12 MATLAB ...Figure 1: MWIR and TIR satellite imagery. On the left is a BIRD image of forest fires on the Portuguese/ Spanish border3 and the image on right MWIR and TIR imagers, instrument engineers are continually evaluating advances in the miniaturization of detector technology. One

  11. Satellite imager calibration and validation

    CSIR Research Space (South Africa)

    Vhengani, L


    Full Text Available The success or failure of any earth observation mission depends on the quality of its data. Data quality is assessed by determining the radiometric, spatial, spectral and geometric fidelity of the satellite sensor. The process is termed calval...

  12. A neuromorphic approach to satellite image understanding (United States)

    Partsinevelos, Panagiotis; Perakakis, Manolis


    Remote sensing satellite imagery provides high altitude, top viewing aspects of large geographic regions and as such the depicted features are not always easily recognizable. Nevertheless, geoscientists familiar to remote sensing data, gradually gain experience and enhance their satellite image interpretation skills. The aim of this study is to devise a novel computational neuro-centered classification approach for feature extraction and image understanding. Object recognition through image processing practices is related to a series of known image/feature based attributes including size, shape, association, texture, etc. The objective of the study is to weight these attribute values towards the enhancement of feature recognition. The key cognitive experimentation concern is to define the point when a user recognizes a feature as it varies in terms of the above mentioned attributes and relate it with their corresponding values. Towards this end, we have set up an experimentation methodology that utilizes cognitive data from brain signals (EEG) and eye gaze data (eye tracking) of subjects watching satellite images of varying attributes; this allows the collection of rich real-time data that will be used for designing the image classifier. Since the data are already labeled by users (using an input device) a first step is to compare the performance of various machine-learning algorithms on the collected data. On the long-run, the aim of this work would be to investigate the automatic classification of unlabeled images (unsupervised learning) based purely on image attributes. The outcome of this innovative process is twofold: First, in an abundance of remote sensing image datasets we may define the essential image specifications in order to collect the appropriate data for each application and improve processing and resource efficiency. E.g. for a fault extraction application in a given scale a medium resolution 4-band image, may be more effective than costly

  13. Image Processing (United States)


    Electronic Imagery, Inc.'s ImageScale Plus software, developed through a Small Business Innovation Research (SBIR) contract with Kennedy Space Flight Center for use on space shuttle Orbiter in 1991, enables astronauts to conduct image processing, prepare electronic still camera images in orbit, display them and downlink images to ground based scientists for evaluation. Electronic Imagery, Inc.'s ImageCount, a spin-off product of ImageScale Plus, is used to count trees in Florida orange groves. Other applications include x-ray and MRI imagery, textile designs and special effects for movies. As of 1/28/98, company could not be located, therefore contact/product information is no longer valid.

  14. Forecasting Hurricane by Satellite Image (United States)

    Liu, M. Y.

    Earth is an endanger planet. Severe weather, especially hurricanes, results in great disaster all the world. World Meteorology Organization and United Nations Environment Program established intergovernment Panel on Climate Change (IPCC) to offer warnings about the present and future disasters of the Earth. It is the mission for scientists to design warning system to predict the severe weather system and to reduce the damage of the Earth. Hurricanes invade all the world every year and made millions damage to all the people. Scientists in weather service applied satellite images and synoptic data to forecast the information for the next hours for warning purposes. Regularly, hurricane hits on Taiwan island directly will pass through her domain and neighbor within 10 hours. In this study, we are going to demonstrate a tricky hurricane NARI invaded Taiwan on September 16, 2000. She wandered in the neighborhood of the island more than 72 hours and brought heavy rainfall over the island. Her track is so tricky that scientists can not forecast her path using the regular method. Fortunately, all scientists in the Central Weather Bureau paid their best effort to fight against the tricky hurricane. Applying the new developed technique to analysis the satellite images with synoptic data and radar echo, scientists forecasted the track, intensity and rainfall excellently. Thus the damage of the severe weather reduced significantly.

  15. Embedded Implementation of VHR Satellite Image Segmentation. (United States)

    Li, Chao; Balla-Arabé, Souleymane; Ginhac, Dominique; Yang, Fan


    Processing and analysis of Very High Resolution (VHR) satellite images provide a mass of crucial information, which can be used for urban planning, security issues or environmental monitoring. However, they are computationally expensive and, thus, time consuming, while some of the applications, such as natural disaster monitoring and prevention, require high efficiency performance. Fortunately, parallel computing techniques and embedded systems have made great progress in recent years, and a series of massively parallel image processing devices, such as digital signal processors or Field Programmable Gate Arrays (FPGAs), have been made available to engineers at a very convenient price and demonstrate significant advantages in terms of running-cost, embeddability, power consumption flexibility, etc. In this work, we designed a texture region segmentation method for very high resolution satellite images by using the level set algorithm and the multi-kernel theory in a high-abstraction C environment and realize its register-transfer level implementation with the help of a new proposed high-level synthesis-based design flow. The evaluation experiments demonstrate that the proposed design can produce high quality image segmentation with a significant running-cost advantage.

  16. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    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...

  17. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang


    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...... on a seven-year ERS-1 and a four-year ERS-2 time series, the long term stability is found to be sufficient to allow a single calibration covering the entire mission period. A descending and an ascending orbit tandem pair of the ESA calibration site on Flevoland, suitable for calibration of ERS SAR processors...

  18. Haystack Ultrawideband Satellite Imaging Radar (United States)


    enable long-range imaging. In 2013, a major upgrade to the facility was completed, adding a millimeter - wave W-band radar capability to Haystack’s X...diameter antenna was completely rebuilt to provide a 100 μm root-mean-square (rms) surface accuracy to support operation at the 3 mm wave - length (W...electromagnetic wave propagation through the troposphere. − The signal processing system lev- eraged Lincoln Laboratory‘s Radar Open Systems

  19. Change detection in satellite images (United States)

    Thonnessen, U.; Hofele, G.; Middelmann, W.


    Change detection plays an important role in different military areas as strategic reconnaissance, verification of armament and disarmament control and damage assessment. It is the process of identifying differences in the state of an object or phenomenon by observing it at different times. The availability of spaceborne reconnaissance systems with high spatial resolution, multi spectral capabilities, and short revisit times offer new perspectives for change detection. Before performing any kind of change detection it is necessary to separate changes of interest from changes caused by differences in data acquisition parameters. In these cases it is necessary to perform a pre-processing to correct the data or to normalize it. Image registration and, corresponding to this task, the ortho-rectification of the image data is a further prerequisite for change detection. If feasible, a 1-to-1 geometric correspondence should be aspired for. Change detection on an iconic level with a succeeding interpretation of the changes by the observer is often proposed; nevertheless an automatic knowledge-based analysis delivering the interpretation of the changes on a semantic level should be the aim of the future. We present first results of change detection on a structural level concerning urban areas. After pre-processing, the images are segmented in areas of interest and structural analysis is applied to these regions to extract descriptions of urban infrastructure like buildings, roads and tanks of refineries. These descriptions are matched to detect changes and similarities.

  20. Spatial Cloud Detection and Retrieval System for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ayman Nasr


    Full Text Available In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection. Satellite images having a large percentage of cloud cannot be used in further analysis. While there are many approaches that deal with different semantic meaning, there are rarely approaches that deal specifically with cloud detection and retrieval. In this paper we introduce a novel approach that spatially detect and retrieve clouds in satellite images using their unique properties .Our approach is developed as spatial cloud detection and retrieval system (SCDRS that introduce a complete framework for specific semantic retrieval system. It uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tile sizes using spatial and textural properties of cloud regions. Second, we retrieve our tiles using a parametric statistical approach within a multilevel refinement process. Our approach has been experimentally validated against the conventional ones yielding enhanced precision and recall rates in the same time it gives more precise detection of cloud coverage regions.

  1. Structural High-resolution Satellite Image Indexing


    Xia, Gui-Song; YANG, WEN; Delon, Julie; Gousseau, Yann; Sun, Hong; Maître, Henri


    International audience; Satellite images with high spatial resolution raise many challenging issues in image understanding and pattern recognition. First, they allow measurement of small objects maybe up to 0.5 m, and both texture and geometrical structures emerge simultaneously. Second, objects in the same type of scenes might appear at different scales and orientations. Consequently, image indexing methods should combine the structure and texture information of images and comply with some i...

  2. Design and Implementation of a Real-time Processing System of Full Resolution Quick-look Image of HJ-1 Environmental Satellite C SAR Based on High Performance Cluster

    Directory of Open Access Journals (Sweden)

    Li Jing-shan


    Full Text Available This study is concerned with the design and implementation of a real-time processing system of full resolution quick-look image of HJ-1 environmental satellite C SAR based on high-performance clusters. The system processes the first quick-look SAR image on December 9, 2012. The results show that the design and implementation of the quick-look processing system satisfies the real-time SAR image processing performance requirements at full resolution. Moreover, this system is the first real-time business system of full-resolution quick-look spaceborne SAR images in China.


    Directory of Open Access Journals (Sweden)

    P. Kupidura


    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

  4. Automatic Approach to Vhr Satellite Image Classification (United States)

    Kupidura, P.; Osińska-Skotak, K.; Pluto-Kossakowska, J.


    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 preliminary step

  5. Evaluation of Development and Changes in Land Use using Different Satellite Image Processing and Remote Sensing Techniques (Case Study: Kermanshah, Iran

    Directory of Open Access Journals (Sweden)

    Mohammad Maleky


    Full Text Available Currently the largest city in the western Iran, Kermanshah enjoys fast growing trend because of its strategic location. Remote sensing and satellite imagery are well suited for assessing the changes in land use over different time periods. In this study, satellite images from Landsat TM sensor and ETM sensor have been prepared during 1987 and 2007 as geometric and radiometric corrections have been made to them. The process was followed by selecting the best combination of false color by using Optimal Index Factor (OIF in ILWIS software. Greenness, brightness and wetness indexes along with NDVI index of land cover were then derived in each period using Fuzzy Art map Supervised Classification, Principal Components Analysis and Tasseled-cap Transformation. The results indicated that Pca2 index can properly demonstrate increasing and decreasing changes among the main components as greenness index can display decreasing and no changes in land uses among tasseled-cap components, while the wetness index would reflect increasing changes in land use with high accuracy. Moreover, the precision and results of NDVI index is so close to that of greenness index. The overall results of the study suggest that the urban surface area is annually increased at a rate of 109.6 ha, which was a major decline in agricultural and range land use.

  6. Model-based satellite image fusion

    DEFF Research Database (Denmark)

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


    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...

  7. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

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


    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....

  8. Web Based Rapid Mapping of Disaster Areas using Satellite Images, Web Processing Service, Web Mapping Service, Frequency Based Change Detection Algorithm and J-iView (United States)

    Bandibas, J. C.; Takarada, S.


    Timely identification of areas affected by natural disasters is very important for a successful rescue and effective emergency relief efforts. This research focuses on the development of a cost effective and efficient system of identifying areas affected by natural disasters, and the efficient distribution of the information. The developed system is composed of 3 modules which are the Web Processing Service (WPS), Web Map Service (WMS) and the user interface provided by J-iView (fig. 1). WPS is an online system that provides computation, storage and data access services. In this study, the WPS module provides online access of the software implementing the developed frequency based change detection algorithm for the identification of areas affected by natural disasters. It also sends requests to WMS servers to get the remotely sensed data to be used in the computation. WMS is a standard protocol that provides a simple HTTP interface for requesting geo-registered map images from one or more geospatial databases. In this research, the WMS component provides remote access of the satellite images which are used as inputs for land cover change detection. The user interface in this system is provided by J-iView, which is an online mapping system developed at the Geological Survey of Japan (GSJ). The 3 modules are seamlessly integrated into a single package using J-iView, which could rapidly generate a map of disaster areas that is instantaneously viewable online. The developed system was tested using ASTER images covering the areas damaged by the March 11, 2011 tsunami in northeastern Japan. The developed system efficiently generated a map showing areas devastated by the tsunami. Based on the initial results of the study, the developed system proved to be a useful tool for emergency workers to quickly identify areas affected by natural disasters.

  9. Autonomous Planetary 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz


    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...

  10. Internal waves and vortices in satellite images

    CERN Document Server

    Sparavigna, Amelia Carolina


    Some recent papers proposed the use of the satellite images of Google Earth in teaching physics, in particular to see some behaviours of waves. Reflection, refraction, diffraction and interference are easy to be found in these satellite maps. Besides Google Earth, other sites exist, such as Earth Observatory or Earth Snapshot, suitable for illustrating the large-scale phenomena in atmosphere and oceans In this paper, we will see some examples for teaching surface and internal sea waves, and internal waves and the K\\'arm\\'an vortices in the atmosphere. Aim of this proposal is attracting the interest of students of engineering schools to the physics of waves.

  11. AO corrected satellite imaging from Mount Stromlo (United States)

    Bennet, F.; Rigaut, F.; Price, I.; Herrald, N.; Ritchie, I.; Smith, C.


    The Research School of Astronomy and Astrophysics have been developing adaptive optics systems for space situational awareness. As part of this program we have developed satellite imaging using compact adaptive optics systems for small (1-2 m) telescopes such as those operated by Electro Optic Systems (EOS) from the Mount Stromlo Observatory. We have focused on making compact, simple, and high performance AO systems using modern high stroke high speed deformable mirrors and EMCCD cameras. We are able to track satellites down to magnitude 10 with a Strehl in excess of 20% in median seeing.

  12. Comparison of Satellite Image Enhancement Techniques in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    K. Narasimhan


    Full Text Available In this study, a comparison of various existing satellite image resolution enhancement techniques in wavelet domain is done. Each method is analysed quantitatively and visually. There are various wavelet domain based methods such as Wavelet Zero Padding, Dual Tree-Complex Wavelet Transform, Discrete Wavelet Transform, Cycle Spinning and Undecimated Wavelet Transform. On the basis of analysis, the most efficient method is proposed. The algorithms take the low resolution image as the input image and then wavelet transformation using daubechies (db3 is used to decompose the input image into different sub band images containing high and low frequency component. Then these subband images along with the input image are interpolated followed by combining all these images to generate a new resolution enhanced image by an inverse process.

  13. Antarctica: measuring glacier velocity from satellite images. (United States)

    Lucchitta, B K; Ferguson, H M


    Many Landsat images of Antarctica show distinctive flow and crevasse features in the floating part of ice streams and outlet glaciers immediately below their grounding zones. Some of the features, which move with the glacier or ice stream, remain visible over many years and thus allow time-lapse measurements of ice velocities. Measurements taken from Landsat images of features on Byrd Glacier agree well with detailed ground and aerial observations. The satellite-image technique thus offers a rapid and cost-effective method of obtaining average velocities, to a first order of accuracy, of many ice streams and outlet glaciers near their termini.

  14. Imaging artificial satellites: An observational challenge (United States)

    Smith, D. A.; Hill, D. C.


    According to the Union of Concerned Scientists, as of the beginning of 2016 there are 1381 active satellites orbiting the Earth, and the United States' Space Surveillance Network tracks about 8000 manmade orbiting objects of baseball-size and larger. NASA estimates debris larger than 1 cm to number more than half a million. The largest ones can be seen by eye—unresolved dots of light that move across the sky in minutes. For most astrophotographers, satellites are annoying streaks that can ruin hours of work. However, capturing a resolved image of an artificial satellite can pose an interesting challenge for a student, and such a project can provide connections between objects in the sky and commercial and political activities here on Earth.

  15. Photogrammetric Processing Using ZY-3 Satellite Imagery (United States)

    Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.


    This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are

  16. Monitoring of wetlands Ecosystems using satellite images (United States)

    Dabrowska-Zielinska, K.; Gruszczynska, M.; Yesou, H.; Hoscilo, A.

    Wetlands are very sensitive ecosystems, functioning as habitat for many organisms. Protection and regeneration of wetlands has been the crucial importance in ecological research and in nature conservation. Knowledge on biophysical properties of wetlands vegetation retrieved from satellite images will enable us to improve monitoring of these unique areas, very often impenetrable. The study covers Biebrza wetland situated in the Northeast part of Poland and is considered as Ramsar Convention test site. The research aims at establishing of changes in biophysical parameters as the scrub encroachment, lowering of the water table, and changes of the farming activity caused ecological changes at these areas. Data from the optical and microwave satellite images collected for the area of Biebrza marshland ecosystem have been analysed and compared with the detailed soil-vegetation ground measurements conducted in conjunction with the overflights. Satellite data include Landsat ETM, ERS-2 ATSR and SAR, SPOT VEGETATION, ENVISAT MERIS and ASAR, and NOAA AVHRR. From the optical data various vegetation indices have been calculated, which characterize the vegetation surface roughness, its moisture conditions and stage of development. Landsat ETM image has been used for classification of wetlands vegetation. For each class of vegetation various moisture indices have been developed. Ground data collected include wet and dry biomass, LAI, vegetation height, and TDR soil moisture. The water cloud model has been applied for retrieval of soil vegetation parameters taking into account microwave satellite images acquired at VV, HV and HH polarisations at different viewing angles. The vegetation parameters have been used for to distinguish changes, which occurred at the area. For each of the vegetation class the soil moisture was calculated from microwave data using developed algorithms. Results of this study will help mapping and monitoring wetlands with the high spatial and temporal

  17. Satellite images analysis for shadow detection and building height estimation (United States)

    Liasis, Gregoris; Stavrou, Stavros


    Satellite images can provide valuable information about the presented urban landscape scenes to remote sensing and telecommunication applications. Obtaining information from satellite images is difficult since all the objects and their surroundings are presented with feature complexity. The shadows cast by buildings in urban scenes can be processed and used for estimating building heights. Thus, a robust and accurate building shadow detection process is important. Region-based active contour models can be used for satellite image segmentation. However, spectral heterogeneity that usually exists in satellite images and the feature similarity representing the shadow and several non-shadow regions makes building shadow detection challenging. In this work, a new automated method for delineating building shadows is proposed. Initially, spectral and spatial features of the satellite image are utilized for designing a custom filter to enhance shadows and reduce intensity heterogeneity. An effective iterative procedure using intensity differences is developed for tuning and subsequently selecting the most appropriate filter settings, able to highlight the building shadows. The response of the filter is then used for automatically estimating the radiometric property of the shadows. The customized filter and the radiometric feature are utilized to form an optimized active contour model where the contours are biased to delineate shadow regions. Post-processing morphological operations are also developed and applied for removing misleading artefacts. Finally, building heights are approximated using shadow length and the predefined or estimated solar elevation angle. Qualitative and quantitative measures are used for evaluating the performance of the proposed method for both shadow detection and building height estimation.

  18. Satellite Imaging with Adaptive Optics on a 1 M Telescope (United States)

    Bennet, F.; Price, I.; Rigaut, F.; Copeland, M.


    The Research School of Astronomy and Astrophysics at the Mount Stromlo Observatory in Canberra, Australia, have been developing adaptive optic (AO) systems for space situational awareness applications. We report on the development and demonstration of an AO system for satellite imaging using a 1 m telescope. The system uses the orbiting object as a natural guide star to measure atmospheric turbulence, and a deformable mirror to provide an optical correction. The AO system utilised modern, high speed and low noise EMCCD technology on both the wavefront sensor and imaging camera to achieve high performance, achieving a Strehl ratio in excess of 30% at 870 nm. Images are post processed with lucky imaging algorithms to further improve the final image quality. We demonstrate the AO system on stellar targets and Iridium satellites, achieving a near diffraction limited full width at half maximum. A specialised realtime controller allows our system to achieve a bandwidth above 100 Hz, with the wavefront sensor and control loop running at 2 kHz. The AO systems we are developing show how ground-based optical sensors can be used to manage the space environment. AO imaging systems can be used for satellite surveillance, while laser ranging can be used to determine precise orbital data used in the critical conjunction analysis required to maintain a safe space environment. We have focused on making this system compact, expandable, and versatile. We are continuing to develop this platform for other space situational awareness applications such as geosynchronous satellite astrometry, space debris characterisation, satellite imaging, and ground-to-space laser communication.

  19. Image Dodging Algorithm for GF-1 Satellite WFV Imagery

    Directory of Open Access Journals (Sweden)

    HAN Jie


    Full Text Available Image dodging method is one of the important processes that determines whether the mosaicking image can be used for remote sensing quantitative application. GF-1 satellite is the first satellite in CHEOS (Chinese high-resolution earth observation system. WFV multispectral sensor is one of the instruments onboard GF-1 satellite which consist of four cameras to mosaic imaging. According to the characteristics of WFV sensor, this paper proposes an image dodging algorithm based on cross/inter-radiometric calibration method. First, the traditional cross calibration method is applied to obtain the calibration coefficients of one WFV camera. Then statistical analysis and simulation methods are adopted to build the correlation models of DN and TOA (top of atmosphere radiances between adjacent cameras. The proposed method can not only accomplish the radiation performance transfer, but also can fulfill the image dodging. The experimental results show the cross/inter-radiometric calibration coefficients in this paper can effectively eliminate the radiation inconsistency problem of the adjacent camera image which realizes the image dodging. So our proposed dodging method can provide an important reference for other similar sensor in future.

  20. Developing Geostationary Satellite Imaging at Lowell Observatory (United States)

    van Belle, G.


    Lowell Observatory operates the Navy Precision Optical Interferometer (NPOI), and owns & operates the Discovery Channel Telescope (DCT). This unique & necessary combination of facilities positions Lowell to develop a robust program of observing geostationary, GPS-plane, and other high-altitude (&1000mi) satellites. NPOI is a six-beam long-baseline optical interferometer, located in Flagstaff, Arizona; the facility is supported by a partnership between Lowell Observatory, the US Naval Observatory, and the Naval Research Laboratory. NPOI operates year-round in the visible with baselines between 8 and 100 meters (up to 432m is available), conducting programs of astronomical research and imaging technology development. NPOI is the only such facility as yet to directly observe geostationary satellites, enabling milliarcsecond resolution of these objects. To enhance this capability towards true imaging of geosats, an ongoing program of facility upgrades will be outlined. These upgrades include AO-assisted 1.0-m apertures feeding each beam line, and new near-infrared instrumentation on the back end. The large apertures will enable `at-will' observations of objects brighter than mK = 8:3 in the near-IR, corresponding to brighter than mV = 11:3 in the visible. At its core, the system is enabled by a `wavelength-baseline bootstrapping' approach discussed herein. A complementary pilot imaging study of visible speckle and aperture masked imaging at Lowell's 4.3-m DCT, for constraining the low-spatial frequency imaging information, is also outlined.

  1. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

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


    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......’s Master Environmental Library. At CLS the a priori wind direction is taken from the ECMWF (European Centre of Medium-range Weather Forecasting). It is also possible to use other sources of wind direction e.g. the satellite-based ASCAT wind directions as demonstrated by CLS. The wind direction has to known...


    Directory of Open Access Journals (Sweden)

    Catherine Mering


    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.

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

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

  5. Statistical image processing and multidimensional modeling

    CERN Document Server

    Fieguth, Paul


    Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something - an artery, a road, a DNA marker, an oil spill - from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over

  6. Polar-Orbiting Satellite (POES) Images (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...

  7. Identification of geostationary satellites using polarization data from unresolved images (United States)

    Speicher, Andy

    In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. Since resolved images of geosynchronous satellites are not technically feasible with current technology, another method of distinguishing space objects was explored that exploits the polarization signature from unresolved images. The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved images of geosynchronous satellites taken over various solar phase angles. Different collection geometries were used to evaluate the polarization contribution of solar arrays, thermal control materials, antennas, and the satellite bus as the solar phase angle changed. Since materials on space objects age due to the space environment, it was postulated that their polarization signature may change enough to allow discrimination of identical satellites launched at different times. The instrumentation used in this experiment was a United States Air Force Academy (USAFA) Department of Physics system that consists of a 20-inch Ritchey-Chretien telescope and a dual focal plane optical train fed with a polarizing beam splitter. A rigorous calibration of the system was performed that included corrections for pixel bias, dark current, and response. Additionally, the two channel polarimeter was calibrated by experimentally determining the Mueller matrix for the system and relating image intensity at the two cameras to Stokes parameters S0 and S1. After the system calibration, polarization data was collected during three nights on eight geosynchronous satellites built by various manufacturers and launched several years apart. Three pairs of the eight

  8. An entropy-based approach to automatic image segmentation of satellite images

    CERN Document Server

    Barbieri, A L; Rodrigues, F A; Bruno, O M; Costa, L da F


    An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.

  9. Realization of Processing Spot 5 Satellite Images by Block Adjustment Based on Erdas Image 9.2 LPS%基于Erdas Image 9.2 LPS区域网平差处理Spot5卫星影像实现方法

    Institute of Scientific and Technical Information of China (English)

    汲旭生; 张丽梅; 穆安才; 马治


    介绍基于LPS的正射影像处理流程,以图文的形式描述区域网平差处理Spot-5卫星影像的具体过程,最后得到正射纠正影像,用于1∶50 000DOM生产。%The paper describes the processing of Spot 5 satellite images based on the Erdas Image 9.2 LPS by block adjustment with words and pictures whereby orthophoto rectification images are obtained finally for producing 1∶ 50 000 digital orthophoto maps.


    Directory of Open Access Journals (Sweden)

    Preuss Ryszard


    Full Text Available This article discusses the current capabilities of automate processing of the image data on the example of using PhotoScan software by Agisoft . At present, image data obtained by various registration systems (metric and non - metric cameras placed on airplanes , satellites , or more often on UAVs is used to create photogrammetric products. Multiple registrations of object or land area (large groups of photos are captured are usually performed in order to eliminate obscured area as well as to raise the final accuracy of the photogrammetric product. Because of such a situation t he geometry of the resulting image blocks is far from the typical configuration of images . For fast images georeferencing automatic image matching algorithms are currently applied . They can create a model of a block in the local coordinate system or using initial exterior orientation and measured control points can provide image georeference in an external reference frame. In the case of non - metric image application, it is also possible to carry out self - calibration process at this stage . Image matching algorithm is also used in generation of dense point clouds reconstructing spatial shape of the object ( area. In subsequent processing steps it is possible to obtain typical photogrammetric products such as orthomosaic , DSM or DTM and a photorealistic solid model of an object . All aforementioned processing steps are implemented in a single program in contrary to standard commercial software dividing all steps into dedicated modules . I mage processing leading to final geo referenced products can be fully automated including sequential implementation of the processing steps at predetermined control parameters . The paper presents the practical results of the application fully automatic generation of othomosaic for both images obtained by a metric Vexell camera and a block of images acquired by a non - metric UAV system.

  11. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus


    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

  12. Panchromatic Satellite Image Classification for Flood Hazard Assessment

    Directory of Open Access Journals (Sweden)

    Ahmed Shaker


    Full Text Available The study aims to investigate the use of panchromatic (PAN satellite image data for flood hazard assessment with anaid of various digital image processing techniques. Two SPOT PAN satellite images covering part of the Nile River inEgypt were used to delineate the flood extent during the years 1997 and 1998 (before and after a high flood. Threeclassification techniques, including the contextual classifier, maximum likelihood classifier and minimum distanceclassifier, were applied to the following: 1 the original PAN image data, 2 the original PAN image data and grey-levelco-occurrence matrix texture created from the PAN data, and 3 the enhanced PAN image data using an edgesharpeningfilter. The classification results were assessed with reference to the results derived from manualdigitization and random checkpoints. Generally, the results showed improvement of the calculation of flood area whenan edge-sharpening filter was used. In addition, the maximum likelihood classifier yielded the best classificationaccuracy (up to 97% compared to the other two classifiers. The research demonstrates the benefits of using PANsatellite imagery as a potential data source for flood hazard assessment.

  13. Assessment of Satellite Images for Soil Salinity Studies

    Directory of Open Access Journals (Sweden)

    S.H. Sanaeinejad


    Full Text Available Soil salinity is one of the main environmental problems affecting extensive area in the world. There are some problems with traditional data collection methods for soil studies. Using the new methods and techniques such as remote sensing could overcome most of these problems. However using these data in areas with uncommon usages needed some researches to find the best calibration between the data and real situations in soil. This research was carried out using Landsat satellite images in Neyshabour area, North East of Iran. In order to prepare suitable learning samples for the image processing in this study, 300 locations were randomly selected in the area, among which 273 locations were finally selected as suitable surface soil samples. All samples were moved to laboratory and their electrical conductivity was measured. Six reflective bands of ETM+ satellite images taken from the study area in 2002 were used for the image processing analysis. Classification of different soil salinities was carried out using common algorithms of image classification based on the best composition bands and using statistical methods between soil salinity variables and digital numbers of the images to represent a suitable method. the research results showed that the reflective bands 7, 3, 4 and 1 are the best band composition for preparing the color composite images and for the classification of the salinity in this area. The highest coefficient of determination was R2=0.311 and R2=0.44 for saline and non-saline soil respectively using band 2 and 3 of the images at 5% significant level. Based on the results, it can be concluded that the potential of ETM+ images for delineation and identification of different soil salinity are limited.

  14. Detecting Anomaly Regions in Satellite Image Time Series Based on Sesaonal Autocorrelation Analysis (United States)

    Zhou, Z.-G.; Tang, P.; Zhou, M.


    Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1) it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2) it is flexible to meet some requirement (e.g., z-value or significance level) of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3) it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.


    Directory of Open Access Journals (Sweden)

    Z.-G. Zhou


    Full Text Available Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1 it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2 it is flexible to meet some requirement (e.g., z-value or significance level of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3 it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.

  16. Hyperspectral image processing methods (United States)

    Hyperspectral image processing refers to the use of computer algorithms to extract, store and manipulate both spatial and spectral information contained in hyperspectral images across the visible and near-infrared portion of the electromagnetic spectrum. A typical hyperspectral image processing work...

  17. Spatio-temporal multi-modality ontology for indexing and retrieving satellite images


    MESSOUDI, Wassim; FARAH, Imed Riadh; SAHEB ETTABAA, Karim; Ben Ghezala, Henda; SOLAIMAN, Basel


    International audience; This paper presents spatio-temporal multi-modality ontology for indexing and retrieving satellite images in the high level to improve the quality of the system retrieval and to perform semantic in the retrieval process.Our approach is based on three modules: (1) regions and features extraction, (2) ontological indexing and (3) semantic image retrieval. The first module allows extracting regions from the satellite image using the fuzzy c-means FCM) segmentation algorith...

  18. Processing Satellite Imagery To Detect Waste Tire Piles (United States)

    Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine


    A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed

  19. Object-based illumination normalization for multi-temporal satellite images in urban area (United States)

    Su, Nan; Zhang, Ye; Tian, Shu; Yan, Yiming


    Multi-temporal satellite images acquisition with different illumination conditions cause radiometric difference to have a huge effect on image quality during remote sensing image processing. In particular, image matching of satellite stereo images with great difference between acquisition dates is very difficult for the high-precision DSM generation in the field of satellite photogrammetry. Therefore, illumination normalization is one of the greatest application technology to eliminate radiometric difference for image matching and other image applications. In this paper, we proposed a novel method of object-based illumination normalization to improve image matching of different temporal satellite stereo images in urban area. Our proposed method include two main steps: 1) the object extraction 2) multi-level illumination normalization. Firstly, we proposed a object extraction method for the same objects extraction among the multi-temporal satellite images, which can keep the object structural attribute. Moreover, the multi-level illumination normalization is proposed by combining gradient domain method and singular value decomposition (SVD) according to characteristic information of relevant objects. Our proposed method has great improvement for the illumination of object area to be benefit for image matching in urban area with multiple objects. And the histogram similarity parameter and matching rate are used for illumination consistency quantitative evaluation. The experiments have been conducted on different satellite images with different acquisition dates in the same urban area to verify the effectiveness of our proposed method. The experimental results demonstrate a good performance by comparing other methods.

  20. Authentication Scheme Based on Principal Component Analysis for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ashraf. K. Helmy


    Full Text Available This paper presents a multi-band wavelet image content authentication scheme for satellite images by incorporating the principal component analysis (PCA. The proposed schemeachieves higher perceptual transparency and stronger robustness. Specifically, the developed watermarking scheme can successfully resist common signal processing such as JPEG compression and geometric distortions such as cropping. In addition, the proposed scheme can be parameterized, thus resulting in more security. That is, an attacker may not be able to extract the embedded watermark if the attacker does not know the parameter.In an order to meet these requirements, the host image is transformed to YIQ to decrease the correlation between different bands, Then Multi-band Wavelet transform (M-WT is applied to each channel separately obtaining one approximate sub band and fifteen detail sub bands. PCA is then applied to the coefficients corresponding to the same spatial location in all detail sub bands. The last principle component band represents an excellent domain forinserting the water mark since it represents lowest correlated features in high frequency area of host image.One of the most important aspects of satellite images is spectral signature, the behavior of different features in different spectral bands, the results of proposed algorithm shows that the spectral stamp for different features doesn't tainted after inserting the watermark.

  1. Moving Target Information Extraction Based on Single Satellite Image

    Directory of Open Access Journals (Sweden)

    ZHAO Shihu


    Full Text Available The spatial and time variant effects in high resolution satellite push broom imaging are analyzed. A spatial and time variant imaging model is established. A moving target information extraction method is proposed based on a single satellite remote sensing image. The experiment computes two airplanes' flying speed using ZY-3 multispectral image and proves the validity of spatial and time variant model and moving information extracting method.

  2. High Resolution Imaging of Satellites with Ground-Based 10-m Astronomical Telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Marois, C


    High resolution imaging of artificial satellites can play an important role in current and future space endeavors. One such use is acquiring detailed images that can be used to identify or confirm damage and aid repair plans. It is shown that a 10-m astronomical telescope equipped with an adaptive optics system (AO) to correct for atmospheric turbulence using a natural guide star can acquire high resolution images of satellites in low-orbits using a fast shutter and a near-infrared camera even if the telescope is not capable of tracking satellites. With the telescope pointing towards the satellite projected orbit and less than 30 arcsec away from a guide star, multiple images of the satellite are acquired on the detector using the fast shutter. Images can then be shifted and coadded by post processing to increase the satellite signal to noise ratio. Using the Keck telescope typical Strehl ratio and anisoplanatism angle as well as a simple diffusion/reflection model for a satellite 400 km away observed near Zenith at sunset or sunrise, it is expected that such system will produced > 10{sigma} K-band images at a resolution of 10 cm inside a 60 arcsec diameter field of view. If implemented, such camera could deliver the highest resolution satellite images ever acquired from the ground.

  3. High Resolution Imaging of Satellites with Ground-Based 10-m Astronomical Telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Marois, C


    High resolution imaging of artificial satellites can play an important role in current and future space endeavors. One such use is acquiring detailed images that can be used to identify or confirm damage and aid repair plans. It is shown that a 10-m astronomical telescope equipped with an adaptive optics system (AO) to correct for atmospheric turbulence using a natural guide star can acquire high resolution images of satellites in low-orbits using a fast shutter and a near-infrared camera even if the telescope is not capable of tracking satellites. With the telescope pointing towards the satellite projected orbit and less than 30 arcsec away from a guide star, multiple images of the satellite are acquired on the detector using the fast shutter. Images can then be shifted and coadded by post processing to increase the satellite signal to noise ratio. Using the Keck telescope typical Strehl ratio and anisoplanatism angle as well as a simple diffusion/reflection model for a satellite 400 km away observed near Zenith at sunset or sunrise, it is expected that such system will produced > 10{sigma} K-band images at a resolution of 10 cm inside a 60 arcsec diameter field of view. If implemented, such camera could deliver the highest resolution satellite images ever acquired from the ground.

  4. The cradle of pyramids in satellite images

    CERN Document Server

    Sparavigna, Amelia Carolina


    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.

  5. Image processing mini manual (United States)

    Matthews, Christine G.; Posenau, Mary-Anne; Leonard, Desiree M.; Avis, Elizabeth L.; Debure, Kelly R.; Stacy, Kathryn; Vonofenheim, Bill


    The intent is to provide an introduction to the image processing capabilities available at the Langley Research Center (LaRC) Central Scientific Computing Complex (CSCC). Various image processing software components are described. Information is given concerning the use of these components in the Data Visualization and Animation Laboratory at LaRC.

  6. Image Processing Software (United States)


    To convert raw data into environmental products, the National Weather Service and other organizations use the Global 9000 image processing system marketed by Global Imaging, Inc. The company's GAE software package is an enhanced version of the TAE, developed by Goddard Space Flight Center to support remote sensing and image processing applications. The system can be operated in three modes and is combined with HP Apollo workstation hardware.

  7. Region of Interest Detection Based on Histogram Segmentation for Satellite Image (United States)

    Kiadtikornthaweeyot, Warinthorn; Tatnall, Adrian R. L.


    High resolution satellite imaging is considered as the outstanding applicant to extract the Earth's surface information. Extraction of a feature of an image is very difficult due to having to find the appropriate image segmentation techniques and combine different methods to detect the Region of Interest (ROI) most effectively. This paper proposes techniques to classify objects in the satellite image by using image processing methods on high-resolution satellite images. The systems to identify the ROI focus on forests, urban and agriculture areas. The proposed system is based on histograms of the image to classify objects using thresholding. The thresholding is performed by considering the behaviour of the histogram mapping to a particular region in the satellite image. The proposed model is based on histogram segmentation and morphology techniques. There are five main steps supporting each other; Histogram classification, Histogram segmentation, Morphological dilation, Morphological fill image area and holes and ROI management. The methods to detect the ROI of the satellite images based on histogram classification have been studied, implemented and tested. The algorithm is be able to detect the area of forests, urban and agriculture separately. The image segmentation methods can detect the ROI and reduce the size of the original image by discarding the unnecessary parts.

  8. Classification of Pansharpened Urban Satellite Images

    DEFF Research Database (Denmark)

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


    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...

  9. Satellite image eavesdropping: a multidisciplinary science education project

    Energy Technology Data Exchange (ETDEWEB)

    Friedt, Jean-Michel [Association Projet Aurore, UFR-ST La Bouloie, 16, route de Gray, 25030 Besancon Cedex (France)


    Amateur reception of satellite images gathers a wide number of concepts and technologies which makes it attractive as an educational tool. We here introduce the reception of images emitted from NOAA series low-altitude Earth-orbiting satellites. We tackle various issues including the identification and prediction of the pass time of visible satellites, the building of the radio-frequency receiver and antenna after modelling their radiation pattern, and then the demodulation of the resulting audio signal for finally displaying an image of the Earth as seen from space.

  10. Accuracy assessment of topographic mapping using UAV image integrated with satellite images (United States)

    Azmi, S. M.; Ahmad, Baharin; Ahmad, Anuar


    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.

  11. NNIC—neural network image compressor for satellite positioning system (United States)

    Danchenko, Pavel; Lifshits, Feodor; Orion, Itzhak; Koren, Sion; Solomon, Alan D.; Mark, Shlomo


    We have developed an algorithm, based on novel techniques of data compression and neural networks for the optimal positioning of a satellite. The algorithm is described in detail, and examples of its application are given. The heart of this algorithm is the program NNIC—neural network image compressor. This program was developed for compression color and grayscale images with artificial neural networks (ANNs). NNIC applies three different methods for compression. Two of them are based on neural networks architectures—multilayer perceptron and kohonen network. The third is based on a widely used method of discrete cosine transform, the basis for the JPEG standard. The program also serves as a tool for determining numerical and visual quality parameters of compression and comparison between different methods. A number of advantages and disadvantages of the compression using ANNs were discovered in the course of the present research, some of them presented in this report. The thrust of the report is the discussion of ANNs implementation problems for modern platforms, such as a satellite positioning system that include intensive image flowing and processing.

  12. Image Processing Software (United States)

    Bosio, M. A.


    ABSTRACT: A brief description of astronomical image software is presented. This software was developed in a Digital Micro Vax II Computer System. : St presenta una somera descripci6n del software para procesamiento de imagenes. Este software fue desarrollado en un equipo Digital Micro Vax II. : DATA ANALYSIS - IMAGE PROCESSING

  13. 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


    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.

  14. Satellite image collection modeling for large area hazard emergency response (United States)

    Liu, Shufan; Hodgson, Michael E.


    Timely collection of critical hazard information is the key to intelligent and effective hazard emergency response decisions. Satellite remote sensing imagery provides an effective way to collect critical information. Natural hazards, however, often have large impact areas - larger than a single satellite scene. Additionally, the hazard impact area may be discontinuous, particularly in flooding or tornado hazard events. In this paper, a spatial optimization model is proposed to solve the large area satellite image acquisition planning problem in the context of hazard emergency response. In the model, a large hazard impact area is represented as multiple polygons and image collection priorities for different portion of impact area are addressed. The optimization problem is solved with an exact algorithm. Application results demonstrate that the proposed method can address the satellite image acquisition planning problem. A spatial decision support system supporting the optimization model was developed. Several examples of image acquisition problems are used to demonstrate the complexity of the problem and derive optimized solutions.

  15. Landsat TM and ETM+ Kansas Satellite Image Database (KSID) (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...

  16. Kansas Satellite Image Database (KSID) 2004-2005 (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)...

  17. gProcess and ESIP Platforms for Satellite Imagery Processing over the Grid (United States)

    Bacu, Victor; Gorgan, Dorian; Rodila, Denisa; Pop, Florin; Neagu, Gabriel; Petcu, Dana


    The Environment oriented Satellite Data Processing Platform (ESIP) is developed through the SEE-GRID-SCI (SEE-GRID eInfrastructure for regional eScience) co-funded by the European Commission through FP7 [1]. The gProcess Platform [2] is a set of tools and services supporting the development and the execution over the Grid of the workflow based processing, and particularly the satelite imagery processing. The ESIP [3], [4] is build on top of the gProcess platform by adding a set of satellite image processing software modules and meteorological algorithms. The satellite images can reveal and supply important information on earth surface parameters, climate data, pollution level, weather conditions that can be used in different research areas. Generally, the processing algorithms of the satellite images can be decomposed in a set of modules that forms a graph representation of the processing workflow. Two types of workflows can be defined in the gProcess platform: abstract workflow (PDG - Process Description Graph), in which the user defines conceptually the algorithm, and instantiated workflow (iPDG - instantiated PDG), which is the mapping of the PDG pattern on particular satellite image and meteorological data [5]. The gProcess platform allows the definition of complex workflows by combining data resources, operators, services and sub-graphs. The gProcess platform is developed for the gLite middleware that is available in EGEE and SEE-GRID infrastructures [6]. gProcess exposes the specific functionality through web services [7]. The Editor Web Service retrieves information on available resources that are used to develop complex workflows (available operators, sub-graphs, services, supported resources, etc.). The Manager Web Service deals with resources management (uploading new resources such as workflows, operators, services, data, etc.) and in addition retrieves information on workflows. The Executor Web Service manages the execution of the instantiated workflows

  18. Medical image processing

    CERN Document Server

    Dougherty, Geoff


    This book is designed for end users in the field of digital imaging, who wish to update their skills and understanding with the latest techniques in image analysis. This book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It uses applications in a variety of fields to demonstrate and consolidate both specific and general concepts, and to build intuition, insight and understanding. Although the chapters are essentially self-contained they reference other chapters to form an integrated whole. Each chapter employs a pedagogical approach to e

  19. Biomedical Image Processing

    CERN Document Server

    Deserno, Thomas Martin


    In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.

  20. Methods in Astronomical Image Processing (United States)

    Jörsäter, S.

    A Brief Introductory Note History of Astronomical Imaging Astronomical Image Data Images in Various Formats Digitized Image Data Digital Image Data Philosophy of Astronomical Image Processing Properties of Digital Astronomical Images Human Image Processing Astronomical vs. Computer Science Image Processing Basic Tools of Astronomical Image Processing Display Applications Calibration of Intensity Scales Calibration of Length Scales Image Re-shaping Feature Enhancement Noise Suppression Noise and Error Analysis Image Processing Packages: Design of AIPS and MIDAS AIPS MIDAS Reduction of CCD Data Bias Subtraction Clipping Preflash Subtraction Dark Subtraction Flat Fielding Sky Subtraction Extinction Correction Deconvolution Methods Rebinning/Combining Summary and Prospects for the Future

  1. Airport runway detection in satellite images by Adaboost learning (United States)

    Zongur, Ugur; Halici, Ugur; Aytekin, Orsan; Ulusoy, Ilkay


    Advances in hardware and pattern recognition techniques, along with the widespread utilization of remote sensing satellites, have urged the development of automatic target detection systems in satellite images. Automatic detection of airports is particularly essential, due to the strategic importance of these targets. In this paper, a runway detection method using a segmentation process based on textural properties is proposed for the detection of airport runways, which is the most distinguishing element of an airport. Several local textural features are extracted including not only low level features such as mean, standard deviation of image intensity and gradient, but also Zernike Moments, Circular-Mellin Features, Haralick Features, as well as features involving Gabor Filters, Wavelets and Fourier Power Spectrum Analysis. Since the subset of the mentioned features, which have a role in the discrimination of airport runways from other structures and landforms, cannot be predicted trivially, Adaboost learning algorithm is employed for both classification and determining the feature subset, due to its feature selector nature. By means of the features chosen in this way, a coarse representation of possible runway locations is obtained. Promising experimental results are achieved and given.

  2. Satellite image blind restoration based on surface fitting and multivariate model

    Institute of Scientific and Technical Information of China (English)

    CHEN Xin-bing; YANG Shi-zhi; WANG Xian-hua; QIAO Yan-li


    Owing to the blurring effect from atmosphere and camera system in the satellite imaging a blind image restoration algo-rithm is proposed which includes the modulation transfer function (MTF) estimation and the image restoration. In the MTF estimation stage, based on every degradation process of satellite imaging-chain, a combined parametric model of MTF is given and used to fit the surface of normalized logarithmic amplitude spectrum of degraded image. In the image restoration stage, a maximum a posteriori (MAP) based edge-preserving image restoration method is presented which introduces multivariate Laplacian model to characterize the prior distribution of wavelet coefficients of original image. During the image restoration, in order to avoid solving high nonlinear equations, optimization transfer algorithm is adopted to decom-pose the image restoration procedure into two simple steps: Landweber iteration and wavelet thresholding denoising. In the numerical experiment, the satellite image restoration results from SPOT-5 and high resolution camera (HR) of China & Brazil earth resource satellite (CBERS-02B) ane compared, and the proposed algorithm is superior in the image edge preservation and noise inhibition.

  3. An Image-Based Sensor System for Autonomous Rendez-Vous with Uncooperative Satellites

    CERN Document Server

    Miravet, Carlos; Krouch, Eloise; del Cura, Juan Manuel


    In this paper are described the image processing algorithms developed by SENER, Ingenieria y Sistemas to cope with the problem of image-based, autonomous rendez-vous (RV) with an orbiting satellite. The methods developed have a direct application in the OLEV (Orbital Life Extension Extension Vehicle) mission. OLEV is a commercial mission under development by a consortium formed by Swedish Space Corporation, Kayser-Threde and SENER, aimed to extend the operational life of geostationary telecommunication satellites by supplying them control, navigation and guidance services. OLEV is planned to use a set of cameras to determine the angular position and distance to the client satellite during the complete phases of rendez-vous and docking, thus enabling the operation with satellites not equipped with any specific navigational aid to provide support during the approach. The ability to operate with un-equipped client satellites significantly expands the range of applicability of the system under development, compar...

  4. The image processing handbook

    CERN Document Server

    Russ, John C


    Now in its fifth edition, John C. Russ's monumental image processing reference is an even more complete, modern, and hands-on tool than ever before. The Image Processing Handbook, Fifth Edition is fully updated and expanded to reflect the latest developments in the field. Written by an expert with unequalled experience and authority, it offers clear guidance on how to create, select, and use the most appropriate algorithms for a specific application. What's new in the Fifth Edition? ·       A new chapter on the human visual process that explains which visual cues elicit a response from the vie

  5. Higher resolution satellite remote sensing and the impact on image mapping (United States)

    Watkins, Allen H.; Thormodsgard, June M.


    Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented. 

  6. Higher resolution satellite remote sensing and the impact on image mapping (United States)

    Watkins, Allen H.; Thormodsgard, June M.

    Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

  7. Use of satellite images for the monitoring of water systems (United States)

    Hillebrand, Gudrun; Winterscheid, Axel; Baschek, Björn; Wolf, Thomas


    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 - 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

  8. Image processing occupancy sensor (United States)

    Brackney, Larry J.


    A system and method of detecting occupants in a building automation system environment using image based occupancy detection and position determinations. In one example, the system includes an image processing occupancy sensor that detects the number and position of occupants within a space that has controllable building elements such as lighting and ventilation diffusers. Based on the position and location of the occupants, the system can finely control the elements to optimize conditions for the occupants, optimize energy usage, among other advantages.

  9. Digital signal processing techniques for on-board processing satellites (United States)

    Kwan, Ching Chung


    In on-board processing satellite systems in which frequency division multiple access (FDMA)/signal channel per carrier (SCPC) access schemes are employed, transmultiplexers are required for the frequency demultiplexing of the SCPC signals. Digital techniques for the implementation of the transmultiplexer for such application were examined. The signal processing in the transmultiplexer operations involved many parameters which could be optimized in order to reduce the hardware complexity while satisfying the level of performance required of the system. An approach for the assessment of the relationship between the various parameters and the system performance was devised, which allowed hardware requirement of practical system specifications to be estimated. For systems involving signals of different bandwidths, a more flexible implementation of the transmultiplexer is required and two computationally efficient methods, the DFT convolution and analysis/synthesis filter bank, were investigated. These methods gave greater flexibility to the input frequency plan of the transmultiplexer, at the expense of increased computational requirements. Filters were then designed to exploit specific properties of the flexible transmultiplexer methods, resulting in considerable improvement in their efficiencies. Hardware implementation of the flexible transmultiplexer was considered and an efficient multiprocesser architecture in combination with parallel processing software algorithms for the signal processing operations were designed. Finally, an experimental model of the payload for a land-mobile satellite system proposal, T-SAT, was constructed using general-purpose digital signal processors and the merits of the on-board processing architecture were demonstrated.

  10. Quantum image processing? (United States)

    Mastriani, Mario


    This paper presents a number of problems concerning the practical (real) implementation of the techniques known as quantum image processing. The most serious problem is the recovery of the outcomes after the quantum measurement, which will be demonstrated in this work that is equivalent to a noise measurement, and it is not considered in the literature on the subject. It is noteworthy that this is due to several factors: (1) a classical algorithm that uses Dirac's notation and then it is coded in MATLAB does not constitute a quantum algorithm, (2) the literature emphasizes the internal representation of the image but says nothing about the classical-to-quantum and quantum-to-classical interfaces and how these are affected by decoherence, (3) the literature does not mention how to implement in a practical way (at the laboratory) these proposals internal representations, (4) given that quantum image processing works with generic qubits, this requires measurements in all axes of the Bloch sphere, logically, and (5) among others. In return, the technique known as quantum Boolean image processing is mentioned, which works with computational basis states (CBS), exclusively. This methodology allows us to avoid the problem of quantum measurement, which alters the results of the measured except in the case of CBS. Said so far is extended to quantum algorithms outside image processing too.

  11. 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...

  12. Image processing of 2D crystal images. (United States)

    Arheit, Marcel; Castaño-Díez, Daniel; Thierry, Raphaël; Gipson, Bryant R; Zeng, Xiangyan; Stahlberg, Henning


    Electron crystallography of membrane proteins uses cryo-transmission electron microscopy to image frozen-hydrated 2D crystals. The processing of recorded images exploits the periodic arrangement of the structures in the images to extract the amplitudes and phases of diffraction spots in Fourier space. However, image imperfections require a crystal unbending procedure to be applied to the image before evaluation in Fourier space. We here describe the process of 2D crystal image unbending, using the 2dx software system.

  13. Analysis of tectonic-controlled fluvial morphology and sedimentary processes of the western Amazon Basin: an approach using satellite images and digital elevation model

    Directory of Open Access Journals (Sweden)

    Clauzionor L. Silva


    Full Text Available An investigation of the tectonic controls of the fluvial morphology and sedimentary processes of an area located southwest of Manaus in the Amazon Basin was conducted using orbital remote sensing data. In this region, low topographic gradients represent a major obstacle for morphotectonic analysis using conventional methods. The use of remote sensing data can contribute significantly to overcome this limitation. In this instance, remote sensing data comprised digital elevation model (DEM acquired by the Shuttle Radar Topographic Mission (SRTM and Landsat Thematic Mapper images. Advanced image processing techniques were employed for enhancing the topographic textures and providing a three-dimensional visualization, hence allowing interpretation of the morphotectonic elements. This led to the recognition of main tectonic compartments and several morphostructural features and landforms related to the neotectonic evolution of this portion of the Amazon Basin. Features such as fault scarps, anomalous drainage patterns, aligned ridges, spurs and valleys, are expressed in the enhanced images as conspicuous lineaments along NE-SW, NW-SE, E-W and N-S directions. These features are associated to the geometry of alternated horst and graben structures, the latter filled by recent sedimentary units. Morphotectonic interpretation using this approach has proven to be efficient and permitted to recognize new tectonic features that were named Asymmetric Ariaú Graben, Rombohedral Manacapuru Basin and Castanho-Mamori Graben.Uma investigação do controle tectônico da morfologia fluvial e dos processos sedimentares de uma área localizada a sudoeste da cidade de Manaus, na Bacia do Amazonas, foi conduzida a partir do uso de dados de sensores remotos orbitais. Nessa região, o baixo gradiente topográfico representa o principal obstáculo para a análise morfotectônica usando métodos convencionais. O uso de dados de sensores remotos pode contribuir

  14. Galileo's first images of Jupiter and the Galilean satellites (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.


    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.

  15. Geospatial Visualization of Global Satellite Images with Vis-EROS

    Energy Technology Data Exchange (ETDEWEB)

    Standart, G. D.; Stulken, K. R.; Zhang, Xuesong; Zong, Ziliang


    The Earth Resources Observation and Science (EROS) Center of U.S. Geological Survey is currently managing and maintaining the world largest satellite images distribution system, which provides 24/7 free download service for researchers all over the globe in many areas such as Geology, Hydrology, Climate Modeling, and Earth Sciences. A large amount of geospatial data contained in satellite images maintained by EROS is generated every day. However, this data is not well utilized due to the lack of efficient data visualization tools. This software implements a method for visualizing various characteristics of the global satellite image download requests. More specifically, Keyhole Markup Language (KML) files are generated which can be loaded into an earth browser such as Google Earth. Colored rectangles associated with stored satellite scenes are painted onto the earth browser; and the color and opacity of each rectangle is varied as a function of the popularity of the corresponding satellite image. An analysis of the geospatial information obtained relative to specified time constraints provides an ability to relate image download requests to environmental, political, and social events.

  16. Image Processing for Teaching. (United States)

    Greenberg, R.; And Others


    The Image Processing for Teaching project provides a powerful medium to excite students about science and mathematics, especially children from minority groups and others whose needs have not been met by traditional teaching. Using professional-quality software on microcomputers, students explore a variety of scientific data sets, including…

  17. Image-Processing Program (United States)

    Roth, D. J.; Hull, D. R.


    IMAGEP manipulates digital image data to effect various processing, analysis, and enhancement functions. It is keyboard-driven program organized into nine subroutines. Within subroutines are sub-subroutines also selected via keyboard. Algorithm has possible scientific, industrial, and biomedical applications in study of flows in materials, analysis of steels and ores, and pathology, respectively.

  18. Multi-Mode GF-3 Satellite Image Geometric Accuracy Verification Using the RPC Model. (United States)

    Wang, Taoyang; Zhang, Guo; Yu, Lei; Zhao, Ruishan; Deng, Mingjun; Xu, Kai


    The GaoFen-3 (GF-3) satellite is the first C-band multi-polarization synthetic aperture radar (SAR) imaging satellite with a resolution up to 1 m in China. It is also the only SAR satellite of the High-Resolution Earth Observation System designed for civilian use. There are 12 different imaging models to meet the needs of different industry users. However, to use SAR satellite images for related applications, they must possess high geometric accuracy. In order to verify the geometric accuracy achieved by the different modes of GF-3 images, we analyze the SAR geometric error source and perform geometric correction tests based on the RPC model with and without ground control points (GCPs) for five imaging modes. These include the spotlight (SL), ultra-fine strip (UFS), Fine Strip I (FSI), Full polarized Strip I (QPSI), and standard strip (SS) modes. Experimental results show that the check point residuals are large and consistent without GCPs, but the root mean square error of the independent checkpoints for the case of four corner control points is better than 1.5 pixels, achieving a similar level of geometric positioning accuracy to that of international satellites. We conclude that the GF-3 satellite can be used for high-accuracy geometric processing and related industry applications.

  19. Estimate Landslide Volume with Genetic Algorithms and Image Similarity Method from Single Satellite Image (United States)

    Yu, Ting-To


    It is important to acquire the volume of landslide in short period of time. For hazard mitigation and also emergency response purpose, the traditional method takes much longer time than expected. Due to the weather limit, traffic accessibility and many regulations of law, it take months to handle these process before the actual carry out of filed work. Remote sensing imagery can get the data as long as the visibility allowed, which happened only few day after the event. While traditional photometry requires a stereo pairs images to produce the post event DEM for calculating the change of volume. Usually have to wait weeks or even months for gathering such data, LiDAR or ground GPS measurement might take even longer period of time with much higher cost. In this study we use one post event satellite image and pre-event DTM to compare the similarity between these by alter the DTM with genetic algorithms. The outcome of smartest guess from GAs shall remove or add exact values of height at each location, which been converted into shadow relief viewgraph to compare with satellite image. Once the similarity threshold been make then the guessing work stop. It takes only few hours to finish the entire task, the computed accuracy is around 70% by comparing to the high resolution LiDAR survey at a landslide, southern Taiwan. With extra GCPs, the estimate accuracy can improve to 85% and also within few hours after the receiving of satellite image. Data of this demonstration case is a 5 m DTM at 2005, 2M resolution FormoSat optical image at 2009 and 5M LiDAR at 2010. The GAs and image similarity code is developed on Matlab at windows PC.

  20. Hyperspectral image processing

    CERN Document Server

    Wang, Liguo


    Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping, and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.

  1. Dsm Based Orientation of Large Stereo Satellite Image Blocks (United States)

    d'Angelo, P.; Reinartz, P.


    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.

  2. The best printing methods to print satellite images

    Directory of Open Access Journals (Sweden)

    G.A. Yousif


    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.

  3. Vehicle Detection and Classification from High Resolution Satellite Images (United States)

    Abraham, L.; Sasikumar, M.


    In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.

  4. Image processing techniques for acoustic images (United States)

    Murphy, Brian P.


    The primary goal of this research is to test the effectiveness of various image processing techniques applied to acoustic images generated in MATLAB. The simulated acoustic images have the same characteristics as those generated by a computer model of a high resolution imaging sonar. Edge detection and segmentation are the two image processing techniques discussed in this study. The two methods tested are a modified version of the Kalman filtering and median filtering.

  5. Retinomorphic image processing. (United States)

    Ghosh, Kuntal; Bhaumik, Kamales; Sarkar, Sandip


    The present work is aimed at understanding and explaining some of the aspects of visual signal processing at the retinal level while exploiting the same towards the development of some simple techniques in the domain of digital image processing. Classical studies on retinal physiology revealed the nature of contrast sensitivity of the receptive field of bipolar or ganglion cells, which lie in the outer and inner plexiform layers of the retina. To explain these observations, a difference of Gaussian (DOG) filter was suggested, which was subsequently modified to a Laplacian of Gaussian (LOG) filter for computational ease in handling two-dimensional retinal inputs. Till date almost all image processing algorithms, used in various branches of science and engineering had followed LOG or one of its variants. Recent observations in retinal physiology however, indicate that the retinal ganglion cells receive input from a larger area than the classical receptive fields. We have proposed an isotropic model for the non-classical receptive field of the retinal ganglion cells, corroborated from these recent observations, by introducing higher order derivatives of Gaussian expressed as linear combination of Gaussians only. In digital image processing, this provides a new mechanism of edge detection on one hand and image half-toning on the other. It has also been found that living systems may sometimes prefer to "perceive" the external scenario by adding noise to the received signals in the pre-processing level for arriving at better information on light and shade in the edge map. The proposed model also provides explanation to many brightness-contrast illusions hitherto unexplained not only by the classical isotropic model but also by some other Gestalt and Constructivist models or by non-isotropic multi-scale models. The proposed model is easy to implement both in the analog and digital domain. A scheme for implementation in the analog domain generates a new silicon retina

  6. Near Real Time Processing Chain for Suomi NPP Satellite Data (United States)

    Monsorno, Roberto; Cuozzo, Giovanni; Costa, Armin; Mateescu, Gabriel; Ventura, Bartolomeo; Zebisch, Marc


    Since 2009, the EURAC satellite receiving station, located at Corno del Renon, in a free obstacle site at 2260 m a.s.l., has been acquiring data from Aqua and Terra NASA satellites equipped with Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The experience gained with this local ground segmenthas given the opportunity of adapting and modifying the processing chain for MODIS data to the Suomi NPP, the natural successor to Terra and Aqua satellites. The processing chain, initially implemented by mean of a proprietary system supplied by Seaspace and Advanced Computer System, was further developed by EURAC's Institute for Applied Remote Sensing engineers. Several algorithms have been developed using MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) data to produce Snow Cover, Particulate Matter estimation and Meteo maps. These products are implemented on a common processor structure based on the use of configuration files and a generic processor. Data and products have then automatically delivered to the customers such as the Autonomous Province of Bolzano-Civil Protection office. For the processing phase we defined two goals: i) the adaptation and implementation of the products already available for MODIS (and possibly new ones) to VIIRS, that is one of the sensors onboard Suomi NPP; ii) the use of an open source processing chain in order to process NPP data in Near Real Time, exploiting the knowledge we acquired on parallel computing. In order to achieve the second goal, the S-NPP data received and ingested are sent as input to RT-STPS (Real-time Software Telemetry Processing System) software developed by the NASA Direct Readout Laboratory 1 (DRL) that gives as output RDR files (Raw Data Record) for VIIRS, ATMS (Advanced Technology Micorwave Sounder) and CrIS (Cross-track Infrared Sounder)sensors. RDR are then transferred to a server equipped with CSPP2 (Community Satellite Processing Package) software developed by the University of



    Arjun Nelikanti


    Principle objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a multitude of choices for improving the visual quality of images. Appropriate choice of such techniques is greatly influenced by the imaging modality, task at hand and viewing conditions. This paper will provide a combination of two concepts, image fusion by DWT and digital image processing techniques. The e...

  8. Simultaneous Fusion and Denoising of Panchromatic and Multispectral Satellite Images (United States)

    Ragheb, Amr M.; Osman, Heba; Abbas, Alaa M.; Elkaffas, Saleh M.; El-Tobely, Tarek A.; Khamis, S.; Elhalawany, Mohamed E.; Nasr, Mohamed E.; Dessouky, Moawad I.; Al-Nuaimy, Waleed; Abd El-Samie, Fathi E.


    To identify objects in satellite images, multispectral (MS) images with high spectral resolution and low spatial resolution, and panchromatic (Pan) images with high spatial resolution and low spectral resolution need to be fused. Several fusion methods such as the intensity-hue-saturation (IHS), the discrete wavelet transform, the discrete wavelet frame transform (DWFT), and the principal component analysis have been proposed in recent years to obtain images with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for satellite images comprising both the IHS transform and the DWFT is proposed. This method tries to achieve the highest possible spectral and spatial resolutions with as small distortion in the fused image as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan images from Landsat-5, Spot, Landsat-7, and IKONOS satellites are used in this comparison. The effect of noise on the proposed hybrid fusion method as well as the traditional fusion methods is studied. Experimental results show the superiority of the proposed hybrid method to the traditional methods. The results show also that a wavelet denoising step is required when fusion is performed at low signal-to-noise ratios.

  9. Mapping soil heterogeneity using RapidEye satellite images (United States)

    Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane


    In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

  10. Detecting aircrafts from satellite images using saliency and conical pyramid based template representation

    Indian Academy of Sciences (India)



    Automatic target localization in satellite images still remains as a challenging problem in the field of computer vision. The issues involved in locating targets in satellite images are viewpoint, spectral (intensity) and scale variations. Diversity in background texture and target clutter also adds up to the complexity of the problem of localizing aircrafts in satellite images. Failure of modern feature extraction and object detection methods highlight the complexity of the problem. In the proposed work, pre-processing techniques, viz.denoising and contrast enhancement, are first used to improve the quality of the images. Then, the concept of unsupervised saliency is used to detect the potential regions of interest, which reduces the search space. Parts from the salient regions are further processed using clustering and morphological processing to get the probable regions of isolated aircraft targets. Finally, a novel conical pyramid based framework for template representation of the target samples is proposed for matching. Experimental results shown on a few satellite images exhibit the superior performance of the proposed methods.

  11. Analytical models integrated with satellite images for optimized pest management (United States)

    The global field protection (GFP) was developed to protect and optimize pest management resources integrating satellite images for precise field demarcation with physical models of controlled release devices of pesticides to protect large fields. The GFP was implemented using a graphical user interf...

  12. scikit-image: image processing in Python. (United States)

    van der Walt, Stéfan; Schönberger, Johannes L; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D; Yager, Neil; Gouillart, Emmanuelle; Yu, Tony


    scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage,

  13. scikit-image: image processing in Python

    Directory of Open Access Journals (Sweden)

    Stéfan van der Walt


    Full Text Available scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage,

  14. Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations (United States)


    and the extent to which they cover the necessary portions of the UV plane . Once the photon counting noise becomes smaller than the UV coverage noise, ad...satellites,” in Proc. SPIE 4091, Imaging Technology and Telescopes, J. W. Bilbro, J. B. Breckinridge, R. A. Carreras , S. R. Czyzak, M. J. Eckart, R. D...SPIE 4091, Imaging Technology and Telescopes, J. W. Bilbro, J. B. Breckinridge, R. A. Carreras , S. R. Czyzak, M. J. Eckart, R. D. Fiete, and P. S

  15. 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz


    The aim of this project has been to implement a software system, that is able to create a 3-D reconstruction from two or more 2-D photographic images made from different positions. The height is determined from the disparity difference of the images. The general purpose of the system is mapping o......, where various methods have been tested in order to optimize the performance. The match results are used in the reconstruction part to establish a 3-D digital representation and finally, different presentation forms are discussed....

  16. An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiao Ling


    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. Shadow imaging of geosynchronous satellites: simulation, image reconstruction, and shadow prediction (United States)

    Douglas, Dennis M.; Hunt, Bobby R.; Sheppard, David G.


    Shadow imaging is a technique to obtain highly resolved silhouettes of resident space objects (RSOs) which would otherwise be unattainable using conventional terrestrial based imaging approaches. This is done by post processing the measured irradiance pattern (shadow) cast onto the Earth as the RSO occults a star. The research presented here focuses on shadow imaging of geosynchronous (GEO) satellites with near stationary orbits approximately 36,000 km from the Earth. Shadows pertaining to a set of diverse observing scenarios are simulated and used as inputs to a Fresnel based phase retrieval algorithm. Spatial resolution limits are evaluated and correlated to signal to noise (SNR) metrics. Resolvable feature sizes of less than 1 m are shown to be readily achievable using foreseeable observing scenarios. Initial output from a shadow prediction tool indicates that there are, on average, over 1000 shadows on the Earth on any given time from a single GEO satellite for stars brighter than mv=10. Shadow ground track uncertainties are correlated to stellar astrometric errors. Global and localized shadow track maps are presented demonstrating a high feasibility for future shadow collections.

  18. Using Satellite Images for Wireless Network Planing in Baku City (United States)

    Gojamanov, M.; Ismayilov, J.


    It is a well known fact that the Information-Telecommunication and Space research technologies are the fields getting much more benefits from the achievements of the scientific and technical progress. In many cases, these areas supporting each other have improved the conditions for their further development. For instance, the intensive development in the field of the mobile communication has caused the rapid progress of the Space research technologies and vice versa.Today it is impossible to solve one of the most important tasks of the mobile communication as Radio Frecance planning without the 2D and 3D digital maps. The compiling of such maps is much more efficient by means of the space images. Because the quality of the space images has been improved and developed, especially at the both spectral and spatial resolution points. It has been possible to to use 8 Band images with the spatial resolution of 50 sm. At present, in relation to the function 3G of mobile communications one of the main issues facing mobile operator companies is a high-precision 3D digital maps. It should be noted that the number of mobile phone users in the Republic of Azerbaijan went forward other Community of Independent States Countries. Of course, using of aerial images for 3D mapping would be optimal. However, depending on a number of technical and administrative problems aerial photography cannot be used. Therefore, the experience of many countries shows that it will be more effective to use the space images with the higher resolution for these issues. Concerning the fact that the mobile communication within the city of Baku has included 3G function there were ordered stereo images wih the spatial resolution of 50 cm for the 150 territory occupying the central part of the city in order to compile 3D digital maps. The images collected from the WorldView-2 satellite are 4-Band Bundle(Pan+MS1) stereo images. Such kind of imagery enable to automatically classificate some required



    Pilař, Martin


    This thesis is focused primarily on digital image processing and modern imaging modalities algorithms. An algorithm means a method for solving a problem or an instruction. In image processing an algorithm presents the process from data acquisition to the resulting image displayed on the monitor. Therefore, in the first part of the thesis a brief overview of principles of imaging modalities used in radiodiagnostics is given. Collected data have to be analyzed and modelled in a certain way. The...

  20. Smart Image Enhancement Process (United States)

    Jobson, Daniel J. (Inventor); Rahman, Zia-ur (Inventor); Woodell, Glenn A. (Inventor)


    Contrast and lightness measures are used to first classify the image as being one of non-turbid and turbid. If turbid, the original image is enhanced to generate a first enhanced image. If non-turbid, the original image is classified in terms of a merged contrast/lightness score based on the contrast and lightness measures. The non-turbid image is enhanced to generate a second enhanced image when a poor contrast/lightness score is associated therewith. When the second enhanced image has a poor contrast/lightness score associated therewith, this image is enhanced to generate a third enhanced image. A sharpness measure is computed for one image that is selected from (i) the non-turbid image, (ii) the first enhanced image, (iii) the second enhanced image when a good contrast/lightness score is associated therewith, and (iv) the third enhanced image. If the selected image is not-sharp, it is sharpened to generate a sharpened image. The final image is selected from the selected image and the sharpened image.

  1. Image processing and recognition for biological images. (United States)

    Uchida, Seiichi


    This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target.

  2. Parallel algorithms of relative radiometric correction for images of TH-1 satellite (United States)

    Wang, Xiang; Zhang, Tingtao; Cheng, Jiasheng; Yang, Tao


    The first generation of transitive stereo-metric satellites in China, TH-1 Satellite, is able to gain stereo images of three-line-array with resolution of 5 meters, multispectral images of 10 meters, and panchromatic high resolution images of 2 meters. The procedure between level 0 and level 1A of high resolution images is so called relative radiometric correction (RRC for short). The processing algorithm of high resolution images, with large volumes of data, is complicated and time consuming. In order to bring up the processing speed, people in industry commonly apply parallel processing techniques based on CPU or GPU. This article firstly introduces the whole process and each step of the algorithm - that is in application - of RRC for high resolution images in level 0; secondly, the theory and characteristics of MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) parallel programming techniques is briefly described, as well as the superiority for parallel technique in image processing field; thirdly, aiming at each step of the algorithm in application and based on MPI+OpenMP hybrid paradigm, the parallelizability and the strategies of parallelism for three processing steps: Radiometric Correction, Splicing Pieces of TDICCD (Time Delay Integration Charge-Coupled Device) and Gray Level Adjustment among pieces of TDICCD are deeply discussed, and furthermore, deducts the theoretical acceleration rates of each step and the one of whole procedure, according to the processing styles and independence of calculation; for the step Splicing Pieces of TDICCD, two different strategies of parallelism are proposed, which are to be chosen with consideration of hardware capabilities; finally, series of experiments are carried out to verify the parallel algorithms by applying 2-meter panchromatic high resolution images of TH-1 Satellite, and the experimental results are analyzed. Strictly on the basis of former parallel algorithms, the programs in the experiments

  3. Image processing with ImageJ

    CERN Document Server

    Pascau, Javier


    The book will help readers discover the various facilities of ImageJ through a tutorial-based approach.This book is targeted at scientists, engineers, technicians, and managers, and anyone who wishes to master ImageJ for image viewing, processing, and analysis. If you are a developer, you will be able to code your own routines after you have finished reading this book. No prior knowledge of ImageJ is expected.

  4. Improving multispectral satellite image compression using onboard subpixel registration (United States)

    Albinet, Mathieu; Camarero, Roberto; Isnard, Maxime; Poulet, Christophe; Perret, Jokin


    Future CNES earth observation missions will have to deal with an ever increasing telemetry data rate due to improvements in resolution and addition of spectral bands. Current CNES image compressors implement a discrete wavelet transform (DWT) followed by a bit plane encoding (BPE) but only on a mono spectral basis and do not profit from the multispectral redundancy of the observed scenes. Recent CNES studies have proven a substantial gain on the achievable compression ratio, +20% to +40% on selected scenarios, by implementing a multispectral compression scheme based on a Karhunen Loeve transform (KLT) followed by the classical DWT+BPE. But such results can be achieved only on perfectly registered bands; a default of registration as low as 0.5 pixel ruins all the benefits of multispectral compression. In this work, we first study the possibility to implement a multi-bands subpixel onboard registration based on registration grids generated on-the-fly by the satellite attitude control system and simplified resampling and interpolation techniques. Indeed bands registration is usually performed on ground using sophisticated techniques too computationally intensive for onboard use. This fully quantized algorithm is tuned to meet acceptable registration performances within stringent image quality criteria, with the objective of onboard real-time processing. In a second part, we describe a FPGA implementation developed to evaluate the design complexity and, by extrapolation, the data rate achievable on a spacequalified ASIC. Finally, we present the impact of this approach on the processing chain not only onboard but also on ground and the impacts on the design of the instrument.

  5. Image Processing and its Military Applications

    Directory of Open Access Journals (Sweden)

    V. V.D. Shah


    Full Text Available One of the important breakthroughs, image processing is the stand alone, non-human image understanding system (IUS. The task of understanding images becomes monumental as one tries to define what understanding really is. Both pattern recognition and artificial intelligence are used in addition to traditional signal processing. Scene analysis procedures using edge and texture segmentation can be considered as the early stages of image understanding process. Symbolic representation and relationship grammers come at subsequent stages. Thus it is not reasonable to put a man into a loop of signal processing at certain sensors such as remotely piloted vehicles, satellites and spacecrafts. Consequently smart sensors and semi-automatic processes are being developed. Land remote sensing has been another important application of the image processing. With the introduction of programmes like Star Wars this particular application has gained a special importance from the Military's point of view. This paper provides an overview of digital image processing and explores the scope of the technology of remote sensing and IUSs from the Military's point of view. An example of the autonomous vehicle project now under progress in the US is described in detail to elucidate the impact of IUSs.

  6. Convolutional neural network features based change detection in satellite images (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong


    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.

  7. The digital mapping of satellite images under no ground control and the distribution of landform, blue ice and meteorites in the Grove Mountains, Antarctica

    Institute of Scientific and Technical Information of China (English)

    孙家抦; 霍东民; 周军其; 孙朝辉


    The colorful satellite image maps with the scale of 1∶100 000 were made by processing the parameters-on-satellite under the condition of no data of field surveying. The purpose is to ensure the smooth performance of the choice of expedition route, navigation and research task before the Chinese National Antarctic Research Expedition (CHINARE) first made researches on the Grove Mountains. Moreover, on the basis of the visual interpretation of the satellite image, we preliminarily analyze and discuss the relief and landform, blue ice and meteorite distribution characteristics in the Grove Mountains. Key words Grove Mountains, parameters-on-satellite, satellite image, digital mapping, blue ice, meteorites distribution.

  8. High-Resolution Imaging of Asteroids/Satellites with AO (United States)

    Merline, William


    We propose to make high-resolution observations of asteroids using AO, to measure size, shape, and pole position (spin vectors), and/or to search for satellites. We have demonstrated that AO imaging allows determination of the pole/dimensions in 1 or 2 nights on a single target, rather than the years of observations with lightcurve inversion techniques that only yield poles and axial ratios, not true dimensions. Our new technique (KOALA) combines AO imaging with lightcurve and occultation data for optimum size/shape determinations. We request that LGS be available for faint targets, but using NGS AO, we will measure several large and intermediate asteroids that are favorably placed in spring/summer of 2012 for size/shape/pole. Accurately determining the volume from the often-irregular shape allows us to derive densities to much greater precision in cases where the mass is known, e.g., from the presence of a satellite. We will search several d! ozen asteroids for the presence of satellites, particularly in under-studied populations, particularly NEOs (we have recently achieved the first-ever optical image of an NEO binary [Merline et al. 2008b, IAUC 8977]). Satellites provide a real-life lab for testing collisional models. We will search for satellites around special objects at the request of lightcurve observers, and we will make a search for debris in the vicinity of Pluto, in support of the New Horizons mission. Our shape/size work requires observations over most of a full rotation period (typically several hours).

  9. High resolution Doppler imager on the Upper Atmosphere Research Satellite

    Energy Technology Data Exchange (ETDEWEB)

    Skinner, W.R.; Hays, P.B.; Grassl, H.J.; Gell, D.A.; Burrage, M.D.; Marshall, A.R.; Ortland, D.A. [Univ. of Michigan, Ann Arbor, MI (United States)


    The High Resolution Doppler Imager (HRDI) on the Upper Atmosphere Research Satellite has been providing measurements of the wind field in the stratosphere, mesosphere and lower thermosphere since November 1991. Examination of various calibration data indicates the instrument has remained remarkably stable since launch. The instrument has a thermal drift of about 30 m/s/{degree}C (slightly dependent on wavelength) and a long-term temporal drift that has amounted to about 80 m/s since launch. These effects are removed in the data processing leaving an uncertainty in the instrument stability of {minus}2 nVs. The temperature control of the instrument has improved significantly since launch as a new method was implemented. The initial temperature control held the instrument temperature at about {+-}1{degree}C. The improved method, which holds constant the temperature of the optical bench instead of the radiator, keeps the instrument temperature at about 0.2{degree}C. The calibrations indicate very little change in the sensitivity of the instrument. The detector response has shown no degradation and the optics have not changed their transmittance.

  10. Fundamentals of electronic image processing

    CERN Document Server

    Weeks, Arthur R


    This book is directed to practicing engineers and scientists who need to understand the fundamentals of image processing theory and algorithms to perform their technical tasks. It is intended to fill the gap between existing high-level texts dedicated to specialists in the field and the need for a more practical, fundamental text on image processing. A variety of example images are used to enhance reader understanding of how particular image processing algorithms work.


    Directory of Open Access Journals (Sweden)

    H. Kim


    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.

  12. Spacecraft design project: High temperature superconducting infrared imaging satellite (United States)


    The High Temperature Superconductor Infrared Imaging Satellite (HTSCIRIS) is designed to perform the space based infrared imaging and surveillance mission. The design of the satellite follows the black box approach. The payload is a stand alone unit, with the spacecraft bus designed to meet the requirements of the payload as listed in the statement of work. Specifications influencing the design of the spacecraft bus were originated by the Naval Research Lab. A description of the following systems is included: spacecraft configuration, orbital dynamics, radio frequency communication subsystem, electrical power system, propulsion, attitude control system, thermal control, and structural design. The issues of testing and cost analysis are also addressed. This design project was part of the course Advanced Spacecraft Design taught at the Naval Postgraduate School.

  13. Multiangle Bistatic SAR Imaging and Fusion Based on BeiDou-2 Navigation Satellite System

    Directory of Open Access Journals (Sweden)

    Zeng Tao


    Full Text Available Bistatic Synthetic Aperture Radar (BSAR based on the Global Navigation Service System (GNSSBSAR uses navigation satellites as radar transmitters, which are low in cost. However, GNSS-BSAR images have poor resolution and low Signal-to-Noise Ratios (SNR. In this paper, a multiangle observation and data processing strategy are presented based on BeiDou-2 navigation satellite imagery, from which twenty-six BSAR images in different configurations are obtained. A region-based fusion algorithm using region of interest segmentation is proposed, and a high-quality fusion image is obtained. The results reveal that the multiangle imaging method can extend the applications of GNSS-BSAR.

  14. Optimal design of the satellite constellation arrangement reconfiguration process (United States)

    Fakoor, Mahdi; Bakhtiari, Majid; Soleymani, Mahshid


    In this article, a novel approach is introduced for the satellite constellation reconfiguration based on Lambert's theorem. Some critical problems are raised in reconfiguration phase, such as overall fuel cost minimization, collision avoidance between the satellites on the final orbital pattern, and necessary maneuvers for the satellites in order to be deployed in the desired position on the target constellation. To implement the reconfiguration phase of the satellite constellation arrangement at minimal cost, the hybrid Invasive Weed Optimization/Particle Swarm Optimization (IWO/PSO) algorithm is used to design sub-optimal transfer orbits for the satellites existing in the constellation. Also, the dynamic model of the problem will be modeled in such a way that, optimal assignment of the satellites to the initial and target orbits and optimal orbital transfer are combined in one step. Finally, we claim that our presented idea i.e. coupled non-simultaneous flight of satellites from the initial orbital pattern will lead to minimal cost. The obtained results show that by employing the presented method, the cost of reconfiguration process is reduced obviously.


    Directory of Open Access Journals (Sweden)

    Diego Correia Maia


    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

  16. Building high-performance system for processing a daily large volume of Chinese satellites imagery (United States)

    Deng, Huawu; Huang, Shicun; Wang, Qi; Pan, Zhiqiang; Xin, Yubin


    The number of Earth observation satellites from China increases dramatically recently and those satellites are acquiring a large volume of imagery daily. As the main portal of image processing and distribution from those Chinese satellites, the China Centre for Resources Satellite Data and Application (CRESDA) has been working with PCI Geomatics during the last three years to solve two issues in this regard: processing the large volume of data (about 1,500 scenes or 1 TB per day) in a timely manner and generating geometrically accurate orthorectified products. After three-year research and development, a high performance system has been built and successfully delivered. The high performance system has a service oriented architecture and can be deployed to a cluster of computers that may be configured with high end computing power. The high performance is gained through, first, making image processing algorithms into parallel computing by using high performance graphic processing unit (GPU) cards and multiple cores from multiple CPUs, and, second, distributing processing tasks to a cluster of computing nodes. While achieving up to thirty (and even more) times faster in performance compared with the traditional practice, a particular methodology was developed to improve the geometric accuracy of images acquired from Chinese satellites (including HJ-1 A/B, ZY-1-02C, ZY-3, GF-1, etc.). The methodology consists of fully automatic collection of dense ground control points (GCP) from various resources and then application of those points to improve the photogrammetric model of the images. The delivered system is up running at CRESDA for pre-operational production and has been and is generating good return on investment by eliminating a great amount of manual labor and increasing more than ten times of data throughput daily with fewer operators. Future work, such as development of more performance-optimized algorithms, robust image matching methods and application

  17. Models for Photogrammetric Processing of Information from Resource-P Satellites (United States)

    Poshekhonov, V.; Eremeev, V.; Kuznetcov, A.; Kochergin, A.


    The present paper provides information about imagery and navigation systems of the Russian high resolution satellites "Resource- P". Models of image geolocation used for photogrammetric processing of information from all types of imagery systems are designed. Design of these models is based on two task solutions: correct processing of the measurement information and geometric calibration of the imagery systems. It is shown that for high-precision interior orientation parameters adjustment of the high-resolution "Geoton" instrument the method of self-calibration should be used. The technology of calibration activities is considered. Distinctive features of calibration of the hyperspectral and wide-swath imagery systems are noted. It is represented in the paper that after calibration the root mean square error (RMSE) of measured geodetic coordinates of objects on images do not exceed 10 m. Examples of the obtained models practical application for photogrammetric processing of images from "Resource-P" satellites are shown.

  18. Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series (United States)

    Champion, Nicolas


    Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

  19. Eye Redness Image Processing Techniques (United States)

    Adnan, M. R. H. Mohd; Zain, Azlan Mohd; Haron, Habibollah; Alwee, Razana; Zulfaezal Che Azemin, Mohd; Osman Ibrahim, Ashraf


    The use of photographs for the assessment of ocular conditions has been suggested to further standardize clinical procedures. The selection of the photographs to be used as scale reference images was subjective. Numerous methods have been proposed to assign eye redness scores by computational methods. Image analysis techniques have been investigated over the last 20 years in an attempt to forgo subjective grading scales. Image segmentation is one of the most important and challenging problems in image processing. This paper briefly outlines the comprehensive of image processing and the implementation of image segmentation in eye redness.

  20. Collection of road traffic information from satellite images and digital map (United States)

    Shinmura, Fumito; Saji, Hitoshi


    There have been many reports on the analysis of the Earth's surface by remote sensing. The purpose of this study is to analyze traffic information, and we have been studying methods of collecting traffic information by remote sensing. To collect traffic information, sensors installed on the roadside are frequently used. However, methods using sensors only collect information around the positions of the sensors. In this study, we attempt to solve this problem by using satellite images, which have recently become increasingly available. We propose a method of collecting traffic information over a large area using satellite images as well as three-dimensional digital maps. We assess traffic conditions by computing the number of edges of vehicles per road section as follows. First, the edges of vehicles are detected in satellite images. During this processing, three-dimensional digital maps are used to increase the accuracy of vehicle edge detection. The number of vehicles per road section, which is computed from the number of edges of vehicles, is computed and referred to as the vehicle density. Traffic conditions can be assessed from the vehicle density and are considered useful for collecting information on traffic congestion. In this study, we experimentally confirm that congested roads can be extracted from satellite images by our method.

  1. The precision-processing subsystem for the Earth Resources Technology Satellite. (United States)

    Chapelle, W. E.; Bybee, J. E.; Bedross, G. M.


    Description of the precision processor, a subsystem in the image-processing system for the Earth Resources Technology Satellite (ERTS). This processor is a special-purpose image-measurement and printing system, designed to process user-selected bulk images to produce 1:1,000,000-scale film outputs and digital image data, presented in a Universal-Transverse-Mercator (UTM) projection. The system will remove geometric and radiometric errors introduced by the ERTS multispectral sensors and by the bulk-processor electron-beam recorder. The geometric transformations required for each input scene are determined by resection computations based on reseau measurements and image comparisons with a special ground-control base contained within the system; the images are then printed and digitized by electronic image-transfer techniques.

  2. Fast segmentation of satellite images using SLIC, WebGL and Google Earth Engine (United States)

    Donchyts, Gennadii; Baart, Fedor; Gorelick, Noel; Eisemann, Elmar; van de Giesen, Nick


    Google Earth Engine (GEE) is a parallel geospatial processing platform, which harmonizes access to petabytes of freely available satellite images. It provides a very rich API, allowing development of dedicated algorithms to extract useful geospatial information from these images. At the same time, modern GPUs provide thousands of computing cores, which are mostly not utilized in this context. In the last years, WebGL became a popular and well-supported API, allowing fast image processing directly in web browsers. In this work, we will evaluate the applicability of WebGL to enable fast segmentation of satellite images. A new implementation of a Simple Linear Iterative Clustering (SLIC) algorithm using GPU shaders will be presented. SLIC is a simple and efficient method to decompose an image in visually homogeneous regions. It adapts a k-means clustering approach to generate superpixels efficiently. While this approach will be hard to scale, due to a significant amount of data to be transferred to the client, it should significantly improve exploratory possibilities and simplify development of dedicated algorithms for geoscience applications. Our prototype implementation will be used to improve surface water detection of the reservoirs using multispectral satellite imagery.

  3. Magnetic resonance imaging research in sub-Saharan Africa: challenges and satellite-based networking implementation. (United States)

    Latourette, Matthew T; Siebert, James E; Barto, Robert J; Marable, Kenneth L; Muyepa, Anthony; Hammond, Colleen A; Potchen, Michael J; Kampondeni, Samuel D; Taylor, Terrie E


    As part of an NIH-funded study of malaria pathogenesis, a magnetic resonance (MR) imaging research facility was established in Blantyre, Malaŵi to enhance the clinical characterization of pediatric patients with cerebral malaria through application of neurological MR methods. The research program requires daily transmission of MR studies to Michigan State University (MSU) for clinical research interpretation and quantitative post-processing. An intercontinental satellite-based network was implemented for transmission of MR image data in Digital Imaging and Communications in Medicine (DICOM) format, research data collection, project communications, and remote systems administration. Satellite Internet service costs limited the bandwidth to symmetrical 384 kbit/s. DICOM routers deployed at both the Malaŵi MRI facility and MSU manage the end-to-end encrypted compressed data transmission. Network performance between DICOM routers was measured while transmitting both mixed clinical MR studies and synthetic studies. Effective network latency averaged 715 ms. Within a mix of clinical MR studies, the average transmission time for a 256 × 256 image was ~2.25 and ~6.25 s for a 512 × 512 image. Using synthetic studies of 1,000 duplicate images, the interquartile range for 256 × 256 images was [2.30, 2.36] s and [5.94, 6.05] s for 512 × 512 images. Transmission of clinical MRI studies between the DICOM routers averaged 9.35 images per minute, representing an effective channel utilization of ~137% of the 384-kbit/s satellite service as computed using uncompressed image file sizes (including the effects of image compression, protocol overhead, channel latency, etc.). Power unreliability was the primary cause of interrupted operations in the first year, including an outage exceeding 10 days.

  4. Analysis of Galileo Style Geostationary Satellite Imaging: Image Reconstruction (United States)


    obtained using only baselines longer than 8 m does not sample the short spacial frequencies, and the image reconstruction is not able to recover the...the long spacial frequencies sampled in a shorter baseline overlap the short spacial frequencies sampled in a longer baseline. This technique will

  5. Image Processing Research (United States)


    linear. c). The prediction is to be based on a selected small number of past estimates. This will impose a desired limited memory requirement for the...otservational ericra can lead to oscillatory estimates. Since c is generally quite smooth, it is reasonable to impose some suopthing constraints on... figura 4 continuous Gaussian noise was added to an image. Median filtering resmltinq in a slight visual improvement. For image enhancement applications

  6. Automatic cloud detection for high resolution satellite stereo images and its application in terrain extraction (United States)

    Wu, Teng; Hu, Xiangyun; Zhang, Yong; Zhang, Lulin; Tao, Pengjie; Lu, Luping


    The automatic extraction of terrain from high-resolution satellite optical images is very difficult under cloudy conditions. Therefore, accurate cloud detection is necessary to fully use the cloud-free parts of images for terrain extraction. This paper addresses automated cloud detection by introducing an image matching based method under a stereo vision framework, and the optimization usage of non-cloudy areas in stereo matching and the generation of digital surface models (DSMs). Given that clouds are often separated from the terrain surface, cloudy areas are extracted by integrating dense matching DSM, worldwide digital elevation model (DEM) (i.e., shuttle radar topography mission (SRTM)) and gray information from the images. This process consists of the following steps: an image based DSM is firstly generated through a multiple primitive multi-image matcher. Once it is aligned with the reference DEM based on common features, places with significant height differences between the DSM and the DEM will suggest the potential cloud covers. Detecting cloud at these places in the images then enables precise cloud delineation. In the final step, elevations of the reference DEM within the cloud covers are assigned to the corresponding region of the DSM to generate a cloud-free DEM. The proposed approach is evaluated with the panchromatic images of the Tianhui satellite and has been successfully used in its daily operation. The cloud detection accuracy for images without snow is as high as 95%. Experimental results demonstrate that the proposed method can significantly improve the usage of the cloudy panchromatic satellite images for terrain extraction.

  7. Optical and digital image processing

    CERN Document Server

    Cristobal, Gabriel; Thienpont, Hugo


    In recent years, Moore's law has fostered the steady growth of the field of digital image processing, though the computational complexity remains a problem for most of the digital image processing applications. In parallel, the research domain of optical image processing has matured, potentially bypassing the problems digital approaches were suffering and bringing new applications. The advancement of technology calls for applications and knowledge at the intersection of both areas but there is a clear knowledge gap between the digital signal processing and the optical processing communities. T

  8. Industrial Applications of Image Processing (United States)

    Ciora, Radu Adrian; Simion, Carmen Mihaela


    The recent advances in sensors quality and processing power provide us with excellent tools for designing more complex image processing and pattern recognition tasks. In this paper we review the existing applications of image processing and pattern recognition in industrial engineering. First we define the role of vision in an industrial. Then a dissemination of some image processing techniques, feature extraction, object recognition and industrial robotic guidance is presented. Moreover, examples of implementations of such techniques in industry are presented. Such implementations include automated visual inspection, process control, part identification, robots control. Finally, we present some conclusions regarding the investigated topics and directions for future investigation

  9. Persistent scatterers detection on synthetic aperture radar images acquired by Sentinel-1 satellite (United States)

    Dǎnişor, Cosmin; Popescu, Anca; Datcu, Mihai


    Persistent Scatterers Interferometry (PS-InSAR) has become a popular method in remote sensing because of its capability to measure terrain deformations with very high accuracy. It relies on multiple Synthetic Aperture Radar (SAR) acquisitions, to monitor points with stable proprieties over time, called Persistent Scatterers (PS)[1]. These points are unaffected by temporal decorrelation, therefore by analyzing their interferometric phase variation we can estimate the scene's deformation rates within a given time interval. In this work, we apply two incoherent detection algorithms to identify Persistent Scatterers candidates in the city of Focșani, Romania. The first method studies the variation of targets' intensities along the SAR acquisitions and the second method analyzes the spectral proprieties of the scatterers. The algorithms were implemented on a dataset containing 11 complex images of the region covering Buzău, Brăila and Focșani cities. Images were acquired by Sentinel-1 satellite in a time span of 5 months, from October 2014 to February 2015. The processing chain follows the requirements imposed by the new C-band SAR images delivered by the Sentinel-1 satellite (launched in April 2014) imaging in Interferometric Wide (IW) mode. Considering the particularities of the TOPS (Terrain Observation with Progressive Scans in Azimuth) imaging mode[2], special requirements had to be considered for pre-processing steps. The PS detection algorithms were implemented in Gamma RS program, a software which contains various function packages dedicated to SAR images focalization, analysis and processing.

  10. ESA's Gaia Satellite and data processing status

    CERN Document Server

    CERN. Geneva


    Gaia, ESA's astrometric surveyor, was launched on Dec 19th 2013 from Kourou. This exciting mission intends to probe the formation history of our galaxy among other things. We will briefly describe the mission and its goals. An overview of Gaia Data Processing Analysis Consortium and the status of the on ground processing will be provided as this is intimately linked to mission performance and goals. The commissioning phase ended in July 2015, this was longer than planned due to in-flight issues. Now we are well into nominal operations and learning to deal with the Gaia we have (it is a great piece of hardware). We will share the current status of Gaia at L2 and the current end of mission performance estimates. About the speaker Since April 2014 William O'Mullane is head of the Operations Development Division in the Science and Robotic Exploration (SRE) directorate of the the European Space Agency. Based in Madrid, he was Gaia Science Operations Development manager from 2005 to launc...

  11. Path planning on satellite images for unmanned surface vehicles

    Directory of Open Access Journals (Sweden)

    Joe-Ming Yang


    Full Text Available In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A * algorithm (FAA *, an advanced A * algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV

  12. Statistical Image Processing. (United States)


    spectral analysist texture image analysis and classification, __ image software package, automatic spatial clustering.ITWA domenit hi ba apa for...ICOLOR(256),IBW(256) 1502 FORMATO (30( CNO(N): fF12.1)) 1503 FORMAT(o *FMINo DMRGE:0f2E20.8) 1504 FORMAT(/o IMRGE:or15) 1505 FOR14ATV FIRST SUBIMAGE:v...1506 FORMATO ’ JOIN CLUSTER NL:0) 1507 FORMAT( NEW CLUSTER:O) 1508 FORMAT( LLBS.GE.600) 1532 FORMAT(15XoTHETA ,7X, SIGMA-SQUAREr3Xe MERGING-DISTANCE

  13. Trends In Microcomputer Image Processing (United States)

    Strum, William E.


    We have seen, in the last four years, the microcomputer become the platform of choice for many image processing applications. By 1991, Frost and Sullivan forecasts that 75% of all image processing will be carried out on microcomputers. Many factors have contributed to this trend and will be discussed in the following paper.

  14. Very High Resolution Satellite Image Classification Using Fuzzy Rule-Based Systems

    Directory of Open Access Journals (Sweden)

    Yun Zhang


    Full Text Available The aim of this research is to present a detailed step-by-step method for classification of very high resolution urban satellite images (VHRSI into specific classes such as road, building, vegetation, etc., using fuzzy logic. In this study, object-based image analysis is used for image classification. The main problems in high resolution image classification are the uncertainties in the position of object borders in satellite images and also multiplex resemblance of the segments to different classes. In order to solve this problem, fuzzy logic is used for image classification, since it provides the possibility of image analysis using multiple parameters without requiring inclusion of certain thresholds in the class assignment process. In this study, an inclusive semi-automatic method for image classification is offered, which presents the configuration of the related fuzzy functions as well as fuzzy rules. The produced results are compared to the results of a normal classification using the same parameters, but with crisp rules. The overall accuracies and kappa coefficients of the presented method stand higher than the check projects.

  15. SWNT Imaging Using Multispectral Image Processing (United States)

    Blades, Michael; Pirbhai, Massooma; Rotkin, Slava V.


    A flexible optical system was developed to image carbon single-wall nanotube (SWNT) photoluminescence using the multispectral capabilities of a typical CCD camcorder. The built in Bayer filter of the CCD camera was utilized, using OpenCV C++ libraries for image processing, to decompose the image generated in a high magnification epifluorescence microscope setup into three pseudo-color channels. By carefully calibrating the filter beforehand, it was possible to extract spectral data from these channels, and effectively isolate the SWNT signals from the background.

  16. Image processing system performance prediction and product quality evaluation (United States)

    Stein, E. K.; Hammill, H. B. (Principal Investigator)


    The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

  17. Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID) (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...

  18. Triple Linear-array Imaging Geometry Model of ZiYuan-3 Surveying Satellite and its Validation

    Directory of Open Access Journals (Sweden)

    TANG Xinming


    Full Text Available The ZiYuan-3 (ZY-3 surveying satellite is the first civilian high-resolution stereo mapping satellite of China. Its objective is oriented to plot the 1:50,000 and 1:25,000 topographic maps. Comparing with foreign commercial mapping satellite imagery, the establishment of our own imaging geometry model is the core technical problem for different products and various applications of ZY-3 surveying satellite. This paper analyses the key problem on precision geometry processing based on the overall design, and proposes the ZY-3 Surveying satellite imaging geometry model with the technology of virtual CCD line-array imaging. In addition, this paper utilizes the first orbit imagery of ZY-3 satellite with coverage of the region of Dalian, and produces forward, backward and nadir cameras calibration products. Different ground control points are selected for the block adjustment experiment, and the Digital Surface Model (DSM, Digital Ortho Map (DOM are generated. The accuracy is validated by check points. It can be seen from the experiment that the planar and vertical accuracy are better than 3 meters and 2 meters, respectively. The experiment demonstrates the effectiveness of ZY-3 surveying satellite imaging geometry model

  19. Onboard Image Processing System for Hyperspectral Sensor

    Directory of Open Access Journals (Sweden)

    Hiroki Hihara


    Full Text Available Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS, which is a hierarchical predictive coding method with resolution scaling. To improve FELICS’s performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost.

  20. Onboard Image Processing System for Hyperspectral Sensor. (United States)

    Hihara, Hiroki; Moritani, Kotaro; Inoue, Masao; Hoshi, Yoshihiro; Iwasaki, Akira; Takada, Jun; Inada, Hitomi; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Tanii, Jun


    Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost.

  1. A low cost thermal infrared hyperspectral imager for small satellites (United States)

    Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.


    The traditional model for space-based earth observations involves long mission times, high cost, and long development time. Because of the significant time and monetary investment required, riskier instrument development missions or those with very specific scientific goals are unlikely to successfully obtain funding. However, a niche for earth observations exploiting new technologies in focused, short lifetime missions is opening with the growth of the small satellite market and launch opportunities for these satellites. These low-cost, short-lived missions provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off the shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCOR), to demonstrate the ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable the use of COTS electronics, and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230-meter pixels with 20 wavenumber spectral resolution from a 400-km orbit.

  2. A low cost thermal infrared hyperspectral imager for small satellites (United States)

    Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.; Wood, M.


    The growth of the small satellite market and launch opportunities for these satellites is creating a new niche for earth observations that contrasts with the long mission durations, high costs, and long development times associated with traditional space-based earth observations. Low-cost, short-lived missions made possible by this new approach provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off-the-shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCoR), to demonstrate ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power-efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable use of COTS electronics and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230 meter pixels with 20 wavenumber spectral resolution from a 400 km orbit. We are currently in the laboratory and airborne testing stage in order to demonstrate the spectro-radiometric quality of data that the instrument provides.

  3. Modeling of solar irradiance using satellite images and direct terrestrial measurements with PV modules (United States)

    Tyukhov, Igor; Schakhramanyan, Michael; Strebkov, Dmitry; Tikhonov, Anton; Vignola, Frank


    A simple, affordable and efficient multifaceted system with technical software programs, "Kosmos 3M", was developed for taking images of the Earth from NOAA satellites and for handling this images and analyzing many geographical and meteorological parameters. Technical software programs have been developed that utilize the "Kosmos 3M" Receiver system. Basic capabilities of the multifaceted "Kosmos 3M" system include: receiving signal from NOAA satellites; digital processing of space images with geographical fixing, superposition of maps of cities and coordinate grid; finding of geographical coordinates at any point of space image; finding of temperature of underlying surface at given points; finding of albedo (reflection coefficient) at any point of space image; finding of upper boundary of clouds (cloudiness); forecasting of dangerous weather phenomena; defining wind fields in cyclones; precipitations forecast; measuring distances between given points; measuring surfaces (areas); and forming of electronic library of images of the Earth. Work is underway to use the "Kosmos 3M" cloudiness images to estimate the incident solar radiation values for evaluating terrestrial solar energy performance in real time. Such kind of system would have a wide variety of uses from the classroom to the field.

  4. Satellite image based methods for fuels maps updating (United States)

    Alonso-Benito, Alfonso; Hernandez-Leal, Pedro A.; Arbelo, Manuel; Gonzalez-Calvo, Alejandro; Moreno-Ruiz, Jose A.; Garcia-Lazaro, Jose R.


    Regular updating of fuels maps is important for forest fire management. Nevertheless complex and time consuming field work is usually necessary for this purpose, which prevents a more frequent update. That is why the assessment of the usefulness of satellite data and the development of remote sensing techniques that enable the automatic updating of these maps, is of vital interest. In this work, we have tested the use of the spectral bands of OLI (Operational Land Imager) sensor on board Landsat 8 satellite, for updating the fuels map of El Hierro Island (Spain). From previously digitized map, a set of 200 reference plots for different fuel types was created. A 50% of the plots were randomly used as a training set and the rest were considered for validation. Six supervised and 2 unsupervised classification methods were applied, considering two levels of detail. A first level with only 5 classes (Meadow, Brushwood, Undergrowth canopy cover >50%, Undergrowth canopy cover <15%, and Xeric formations), and the second one containing 19 fuel types. The level 1 classification methods yielded an overall accuracy ranging from 44% for Parellelepided to an 84% for Maximun Likelihood. Meanwhile, level 2 results showed at best, an unacceptable overall accuracy of 34%, which prevents the use of this data for such a detailed characterization. Anyway it has been demonstrated that in some conditions, images of medium spatial resolution, like Landsat 8-OLI, could be a valid tool for an automatic upgrade of fuels maps, minimizing costs and complementing traditional methodologies.

  5. Application of Geostatistical Simulation to Enhance Satellite Image Products (United States)

    Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David


    With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

  6. Image processing to optimize wave energy converters (United States)

    Bailey, Kyle Marc-Anthony

    The world is turning to renewable energies as a means of ensuring the planet's future and well-being. There have been a few attempts in the past to utilize wave power as a means of generating electricity through the use of Wave Energy Converters (WEC), but only recently are they becoming a focal point in the renewable energy field. Over the past few years there has been a global drive to advance the efficiency of WEC. Placing a mechanical device either onshore or offshore that captures the energy within ocean surface waves to drive a mechanical device is how wave power is produced. This paper seeks to provide a novel and innovative way to estimate ocean wave frequency through the use of image processing. This will be achieved by applying a complex modulated lapped orthogonal transform filter bank to satellite images of ocean waves. The complex modulated lapped orthogonal transform filterbank provides an equal subband decomposition of the Nyquist bounded discrete time Fourier Transform spectrum. The maximum energy of the 2D complex modulated lapped transform subband is used to determine the horizontal and vertical frequency, which subsequently can be used to determine the wave frequency in the direction of the WEC by a simple trigonometric scaling. The robustness of the proposed method is provided by the applications to simulated and real satellite images where the frequency is known.

  7. Micro-satellite constellations for monitoring cryospheric processes and related natural hazards (United States)

    Kaeaeb, A.; Altena, B.; Mascaro, J.


    Currently, several micro-satellite constellations for earth-observation are planned or under build-up. Here, we assess the potential of the well-advanced Planet satellite constellation for investigating cryospheric processes. In its final stage, the Planet constellation will consist of 150 free-flying micro-satellites in near-polar and ISS orbits. The instruments carry RGB+NIR frame cameras that image the Earth surface in nadir direction with resolutions of 3-5 m, covering 20 x 13 km per image. In its final set-up, the constellation will be able to image the (almost) entire land surface at least once per day, under the limitation of cloud cover. Here, we explore new possibilities for insight into cryospheric processes that this very high repeat cycle combined with high image resolution offer. Based on repeat Planet imagery we derive repeat glacier velocity fields for example glaciers in the northern and southern hemispheres. We find it especially useful to monitor the ice velocities near calving fronts and simultaneously detect changes of the front, pointing to calving events. We also explore deformation fields over creeping mountain permafrost, so-called rockglaciers. As a second, very promising cryospheric application we suggest monitoring of glacier and permafrost related natural hazards. In cases such as temporary lakes, lake outbursts, landslides, rock avalanches, visual information over remote areas and at high frequencies are crucial for hazard assessment, early warning or disaster management. Based on several examples, we demonstrate that massive micro-satellite constellations such Planet's are exactly able to provide this type of information. As a third promising example, we show how such high-repeat optical satellite data are useful to monitor river ice and related jams and flooding. At certain latitudes, the repeat frequency of the data is even high enough to track river ice floes and thus water velocities.

  8. Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming (United States)

    Benzouai, Siham; Smara, Youcef


    The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.

  9. Biomedical signal and image processing

    CERN Document Server

    Najarian, Kayvan


    INTRODUCTION TO DIGITAL SIGNAL AND IMAGE PROCESSINGSignals and Biomedical Signal ProcessingIntroduction and OverviewWhat is a ""Signal""?Analog, Discrete, and Digital SignalsProcessing and Transformation of SignalsSignal Processing for Feature ExtractionSome Characteristics of Digital ImagesSummaryProblemsFourier TransformIntroduction and OverviewOne-Dimensional Continuous Fourier TransformSampling and NYQUIST RateOne-Dimensional Discrete Fourier TransformTwo-Dimensional Discrete Fourier TransformFilter DesignSummaryProblemsImage Filtering, Enhancement, and RestorationIntroduction and Overview

  10. Digital geometry in image processing

    CERN Document Server

    Mukhopadhyay, Jayanta


    Exploring theories and applications developed during the last 30 years, Digital Geometry in Image Processing presents a mathematical treatment of the properties of digital metric spaces and their relevance in analyzing shapes in two and three dimensions. Unlike similar books, this one connects the two areas of image processing and digital geometry, highlighting important results of digital geometry that are currently used in image analysis and processing. The book discusses different digital geometries in multi-dimensional integral coordinate spaces. It also describes interesting properties of

  11. Image processing for optical mapping. (United States)

    Ravindran, Prabu; Gupta, Aditya


    Optical Mapping is an established single-molecule, whole-genome analysis system, which has been used to gain a comprehensive understanding of genomic structure and to study structural variation of complex genomes. A critical component of Optical Mapping system is the image processing module, which extracts single molecule restriction maps from image datasets of immobilized, restriction digested and fluorescently stained large DNA molecules. In this review, we describe robust and efficient image processing techniques to process these massive datasets and extract accurate restriction maps in the presence of noise, ambiguity and confounding artifacts. We also highlight a few applications of the Optical Mapping system.

  12. Digital elevation model and satellite images an assessment of soil erosion potential in the Pcinja catchment

    Directory of Open Access Journals (Sweden)

    Milevski Ivica


    Full Text Available Pcinja is large left tributary of Vardar River (135 km long, 2877,3 km2 catchment’s area, which drainages surface waters from northeastern Macedonia, and small part of southeastern Serbia. Because of suitable physical-geographic factors (geology, terrain morphology, climate, hydrology, vegetation coverage, soil composition, and high human impact, some parts of the catchment’s suffer significant erosion process. For this reason, it is necessary to research properly spatial distribution of erosion, then influence of physical and anthropogenic factors for the intensity of soil erosion, related erosion landforms (with morphology, genesis, evolution, soil erosion protection etc.. Earlier researches in the area have been performed generally with combination of cartographic and classic field analysis. But in last decades, there are new possibilities available like satellite images and digital elevation models. In this work has been presented the methodology of utilization of satellite images and DEM for erosion research, with analysis and comparisons of outcome data.

  13. A Bayesian approach for solar resource potential assessment using satellite images (United States)

    Linguet, L.; Atif, J.


    The need for a more sustainable and more protective development opens new possibilities for renewable energy. Among the different renewable energy sources, the direct conversion of sunlight into electricity by solar photovoltaic (PV) technology seems to be the most promising and represents a technically viable solution to energy demands. But implantation and deployment of PV energy need solar resource data for utility planning, accommodating grid capacity, and formulating future adaptive policies. Currently, the best approach to determine the solar resource at a given site is based on the use of satellite images. However, the computation of solar resource (non-linear process) from satellite images is unfortunately not straightforward. From a signal processing point of view, it falls within non-stationary, non-linear/non-Gaussian dynamical inverse problems. In this paper, we propose a Bayesian approach combining satellite images and in situ data. We propose original observation and transition functions taking advantages of the characteristics of both the involved type of data. A simulation study of solar irradiance is carried along with this method and a French Guiana solar resource potential map for year 2010 is given.

  14. Production process for advanced space satellite system cables/interconnects.

    Energy Technology Data Exchange (ETDEWEB)

    Mendoza, Luis A.


    This production process was generated for the satellite system program cables/interconnects group, which in essences had no well defined production process. The driver for the development of a formalized process was based on the set backs, problem areas, challenges, and need improvements faced from within the program at Sandia National Laboratories. In addition, the formal production process was developed from the Master's program of Engineering Management for New Mexico Institute of Mining and Technology in Socorro New Mexico and submitted as a thesis to meet the institute's graduating requirements.

  15. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation (United States)

    Song, Huihui

    Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

  16. Acoustic image-processing software (United States)

    Several algorithims that display, enhance and analyze side-scan sonar images of the seafloor, have been developed by the University of Washington, Seattle, as part of an Office of Naval Research funded program in acoustic image analysis. One of these programs, PORTAL, is a small (less than 100K) image display and enhancement program that can run on MS-DOS computers with VGA boards. This program is now available in the public domain for general use in acoustic image processing.PORTAL is designed to display side-scan sonar data that is stored in most standard formats, including SeaMARC I, II, 150 and GLORIA data. (See image.) In addition to the “standard” formats, PORTAL has a module “front end” that allows the user to modify the program to accept other image formats. In addition to side-scan sonar data, the program can also display digital optical images from scanners and “framegrabbers,” gridded bathymetry data from Sea Beam and other sources, and potential field (magnetics/gravity) data. While limited in image analysis capability, the program allows image enhancement by histogram manipulation, and basic filtering operations, including multistage filtering. PORTAL can print reasonably high-quality images on Postscript laser printers and lower-quality images on non-Postscript printers with HP Laserjet emulation. Images suitable only for index sheets are also possible on dot matrix printers.


    Directory of Open Access Journals (Sweden)

    K.-Y. Lee


    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

  18. Cloud Detection of Optical Satellite Images Using Support Vector Machine (United States)

    Lee, Kuan-Yi; Lin, Chao-Hung


    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

  19. Satellite image time series simulation for environmental monitoring (United States)

    Guo, Tao


    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

  20. Detection of Burn Area and Severity with MODIS Satellite Images and Spatial Autocorrelation Techniques (United States)

    Kaya, S.; Kavzoglu, T.; Tonbul, H.


    Effects of forest fires and implications are one of the most important natural disasters all over the world. Statistical data observed that forest fires had a variable structure in the last century in Turkey, but correspondingly the population growth amount of forest fires and burn area increase widely in recent years. Depending on this, erosion, landslides, desertification and mass loss come into existence. In addition; after forest fires, renewal of forests and vegetation are very important for land management. Classic methods used for detection of burn area and severity requires a long and challenging process due to time and cost factors. Thanks to advanced techniques used in the field of Remote Sensing, burn area and severity can be determined with high detail and precision. The purpose of this study based on blending MODIS (Moderate Resolution Imaging Spectradiometer) satellite images and spatial autocorrelation techniques together, thus detect burn area and severity absolutely. In this context, spatial autocorrelation statistics like Moran's I and Get is-Ord Local Gi indexes were used to measure and analyze to burned area characteristics. Prefire and postfire satellite images were used to determine fire severity depending on spectral indexes corresponding to biomass loss and carbon emissivity intensities. Satellite images have used for identification of fire damages and risks in terms of fire management for a long time. This study was performed using prefire and postfire satellite images and spatial autocorrelation techniques to determining and analyzing forest fires in Antalya, Turkey region which serious fires occurred. In this context, this approach enables the characterization of distinctive texture of burned area and helps forecasting more precisely. Finally, it is observed that mapping of burned area and severity could be performed from local scale to national scale. Key Words: Spatial autocorrelation, MODIS, Fire, Burn Severity

  1. Foodstuff Survey Around a Major Nuclear Facility with Test of Satellite Image Application

    Energy Technology Data Exchange (ETDEWEB)

    Fledderman, P.D.


    'A foodstuff survey was performed around the Savannah River Site, Aiken SC. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of SRS center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined in two ways: by the usual process of assuming uniform crop distribution in each county on the basis of agricultural statistics reported by state agencies, and by analysis of two LANDSAT TM images obtained in May and September. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the Site and by 16-km distance intervals from 16 km to 80 km. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption. For four food crops, the amounts per section based on county agricultural statistics prorated by area were compared with the amounts per section based on satellite image analysis. The median ratios of the former to the latter were 0.6 - 0.7, suggesting that the two approaches are comparable but that satellite image analysis gave consistently higher amounts. Use of satellite image analysis is recommended on the basis of these findings to obtain site-specific, as compared to area-averaged, information on crop locations in conjunction with radionuclide pathway modelling. Some improvements in technique are suggested for satellite image application to characterize additional crops.'

  2. Building damage scale proposal from VHR satellite image (United States)

    Sandu, Constantin; Giulio Tonolo, Fabio; Cotrufo, Silvana; Boccardo, Piero


    Natural hazards have a huge impact in terms of economic losses, affected and killed people. Current exploitation of remote sensed images play a fundamental role in the delineation of damages generated by catastrophic events. Institutions like the United Nations and the European Commission designed services that provide information about the impact of disasters rapidly. One of the approach currently used to carry out the damage assessment is based on very high resolution remote sensing imagery (including both aerial and satellite platforms). One of the main focus of the responders, especially in case of events like earthquakes, is on buildings and infrastructures. As far as the buildings are concerned, to date international standard guidelines that provide essential information on how to assess building damages using VHR images still does not exist. The aim of this study is to develop a building damage scale tailored for analyses based on VHR vertical imagery and to propose a standard for the related interpretation guidelines. The task is carried out by comparing the current scales used for damage assessment by the main satellite based emergency mapping services. The study will analyze the datasets produced after the Ecuador (April 2016) and Central Italy(August and October 2016) earthquakes. The results suggest that by using VHR remotely sensed images it is not possible to directly use damage classification scales addressing structural damages (e.g the 5 grades proposed by EMS-98). A fine-tuning of existing damage classes is therefore required and the adoption of an internationally agreed standard should be encouraged, to streamline the use of SEM products generated by different services.

  3. Accelerating Satellite Image Based Large-Scale Settlement Detection with GPU

    Energy Technology Data Exchange (ETDEWEB)

    Patlolla, Dilip Reddy [ORNL; Cheriyadat, Anil M [ORNL; Weaver, Jeanette E [ORNL; Bright, Eddie A [ORNL


    Computer vision algorithms for image analysis are often computationally demanding. Application of such algorithms on large image databases\\---- such as the high-resolution satellite imagery covering the entire land surface, can easily saturate the computational capabilities of conventional CPUs. There is a great demand for vision algorithms running on high performance computing (HPC) architecture capable of processing petascale image data. We exploit the parallel processing capability of GPUs to present a GPU-friendly algorithm for robust and efficient detection of settlements from large-scale high-resolution satellite imagery. Feature descriptor generation is an expensive, but a key step in automated scene analysis. To address this challenge, we present GPU implementations for three different feature descriptors\\-- multiscale Historgram of Oriented Gradients (HOG), Gray Level Co-Occurrence Matrix (GLCM) Contrast and local pixel intensity statistics. We perform extensive experimental evaluations of our implementation using diverse and large image datasets. Our GPU implementation of the feature descriptor algorithms results in speedups of 220 times compared to the CPU version. We present an highly efficient settlement detection system running on a multiGPU architecture capable of extracting human settlement regions from a city-scale sub-meter spatial resolution aerial imagery spanning roughly 1200 sq. kilometers in just 56 seconds with detection accuracy close to 90\\%. This remarkable speedup gained by our vision algorithm maintaining high detection accuracy clearly demonstrates that such computational advancements clearly hold the solution for petascale image analysis challenges.

  4. GPU Accelerated Automated Feature Extraction From Satellite Images

    Directory of Open Access Journals (Sweden)

    K. Phani Tejaswi


    Full Text Available The availability of large volumes of remote sensing data insists on higher degree of automation in featureextraction, making it a need of thehour. Fusingdata from multiple sources, such as panchromatic,hyperspectraland LiDAR sensors, enhances the probability of identifying and extracting features such asbuildings, vegetation or bodies of water by using a combination of spectral and elevation characteristics.Utilizing theaforementioned featuresin remote sensing is impracticable in the absence ofautomation.Whileefforts are underway to reduce human intervention in data processing, this attempt alone may notsuffice. Thehuge quantum of data that needs to be processed entailsaccelerated processing to be enabled.GPUs, which were originally designed to provide efficient visualization,arebeing massively employed forcomputation intensive parallel processing environments. Image processing in general and hence automatedfeatureextraction, is highly computation intensive, where performance improvements have a direct impacton societal needs. In this context, an algorithm has been formulated for automated feature extraction froma panchromatic or multispectral image based on image processing techniques.Two Laplacian of Guassian(LoGmasks were applied on the image individually followed by detection of zero crossing points andextracting the pixels based on their standard deviationwiththe surrounding pixels. The two extractedimages with different LoG masks were combined together which resulted in an image withthe extractedfeatures and edges.Finally the user is at liberty to apply the image smoothing step depending on the noisecontent in the extracted image.The image ispassed through a hybrid median filter toremove the salt andpepper noise from the image.This paper discusses theaforesaidalgorithmforautomated featureextraction, necessity of deployment of GPUs for thesame;system-level challenges and quantifies thebenefits of integrating GPUs in such environment. The

  5. Onboard Image Processing System for Hyperspectral Sensor

    National Research Council Canada - National Science Library

    Hihara, Hiroki; Moritani, Kotaro; Inoue, Masao; Hoshi, Yoshihiro; Iwasaki, Akira; Takada, Jun; Inada, Hitomi; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Tanii, Jun


    .... Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size...

  6. A data mining based approach to predict spatiotemporal changes in satellite images (United States)

    Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben


    The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

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

    Directory of Open Access Journals (Sweden)

    Irene Erlyn Wina Rachmawan


    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.

  8. Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

    Directory of Open Access Journals (Sweden)

    Maocai Wang


    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.

  9. Urban Land Use Change Detection Using Multisensor Satellite Images

    Institute of Scientific and Technical Information of China (English)

    DENG Jin-Song; WANG Ke; LI Jun; DENG Yan-Hua


    Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multiseusor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 muttispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into bnilt-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.

  10. Images of war: using satellite images for human rights monitoring in Turkish Kurdistan. (United States)

    de Vos, Hugo; Jongerden, Joost; van Etten, Jacob


    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.

  11. Multifractal analysis of satellite images. (Polish Title: Multifraktalna analiza zobrazowan satelitarnych) (United States)

    Wawrzaszek, A.; Krupiński, M.; Drzewiecki, W.; Aleksandrowicz, S.


    Research presented in this paper is focused on the efficiency assessment of multifractal description as a tool for Image Information Mining. Large datasets of very high spatial resolution satellite images (WorldView-2 and EROS-A) have been analysed. The results have confirmed the superiority of multifractals as global image descriptors in comparison to monofractals. Moreover, their usefulness in image classification by using decision trees classifiers was confirmed, also in comparison with textural features. Filtration process preceding fractal and multifractal features estimations was also proved to improve classification results. Additionally, airborne hyperspectral data have been initially analysed. Fractal dimension shows high potential for the description of hyperspectral data. To summarise all conducted tests indicate the usefulness of multifractal formalism in various aspects of remote sensing. Prepared methodology can be further developed and used for more specific tasks, for example in change detection or in the description of hyperspectal data complexity.

  12. TIRCIS: thermal infrared compact imaging spectrometer for small satellite applications (United States)

    Wright, Robert; Lucey, Paul; Crites, Sarah; Garbeil, Harold; Wood, Mark; Pilger, Eric; Gabrieli, Andrea; Honniball, Casey


    Measurements of reflectance or emittance in tens of narrow, contiguous wavebands, allow for the derivation of laboratory quality spectra remotely, from which the chemical composition and physical properties of targets can be determined. Although spaceborne (e.g. EO-1 Hyperion) hyperspectral data in the 0.4-2.5 micron (VSWIR) region are available, the provision of equivalent data in the log-wave infrared has lagged behind, there being no currently operational high spatial resolution LWIR imaging spectrometer on orbit. TIRCIS (Thermal Infra-Red Compact Imaging Spectrometer), uses a Fabry-Perot interferometer, an uncooled microbolometer array, and push-broom scanning to acquire hyperspectral image data. Radiometric calibration is provided by blackbody targets while spectral calibration is achieved using monochromatic light sources. The instrument has a mass of <15 kg and dimensions of 53 cm × 25 cm ♢ 22 cm, and has been designed to be compatible with integration into a micro-satellite platform. (A precursor to this instrument was launched onboard a 55 kg microsatellite in October 2015). The optical design yields a 120 m ground sample size given an orbit of 500 km. Over the wavelength interval of 7.5 to 14 microns up to 50 spectral samples are possible. Measured signal-to-noise ratios range from peak values of 500:1 to 1500:1, for source temperature of 10 to 100°C.

  13. A System to Detect Residential Area in Multispectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Seyfallah Bouraoui


    Full Text Available In this paper, we propose a new solution to extract complex structures from High-Resolution (HR remote-sensing images. We propose to represent shapes and there relations by using region adjacency graphs. They are generated automatically from the segmented images. Thus, the nodes of the graph represent shape like houses, streets or trees, while arcs describe the adjacency relation between them. In order to be invariant to transformations such as rotation and scaling, the extraction of objects of interest is done by combining two techniques: one based on roof color to detect the bounding boxes of houses, and one based on mathematical morphology notions to detect streets. To recognize residential areas, a model described by a regular language is built. The detection is achieved by looking for a path in the region adjacency graph, which can be recognized as a word belonging to the description language. Our algorithm was tested with success on images from the French satellite SPOT 5 representing the urban area of Strasbourg (France at different spatial resolution.

  14. Identifying potential solar power generation sites using satellite apt images (United States)

    Fawz-Ul-Haq, K. R.; Siddiqui, Z. R.


    In this paper, satellite APT images have been used to study cloud-cover over Pakistan, so as to determine those areas which have the least frequency of cloudiness. Such areas are likely to receive maximum insolation, and have been shown on a contour map of Pakistan. It is observed that more than half of Pakistan is highly sunny, and has many promising areas for establishing large scale solar electric power generation stations. It is further observed that, some of the productive mineral-rich areas in remote parts, such as Chagai, are highly cloud-free, therefore, it may be possible to meet their mining needs through solar energy. Thus Pakistan, on the threshold of industrialization, has high prospects of obtaining `clean' energy, free of greenhouse gases.

  15. Satellite Image Security Improvement by Combining DWT-DCT Watermarking and AES Encryption

    Directory of Open Access Journals (Sweden)



    Full Text Available With the large-scale research in space sciences and technologies, there is a great demand of satellite image security system for providing secure storage and transmission of satellite images. As the demand to protect the sensitive and valuable data from satellites has increased and hence proposed a new method for satellite image security by combining DWT-DCT watermarking and AES encryption. Watermarking techniques developed for multimedia data cannot be directly applied to the satellite images because here the analytic integrity of the data, rather than perceptual quality, is of primary importance. To improve performance, combine discrete wavelet transform (DWT with another equally powerful transform; the discrete cosine transform (DCT. The combined DWT-DCT watermarking algorithm’s imperceptibility was better than the performance of the DWT approach. Modified decision based unsymmetrical trimmed median filter (MDBUTMF algorithm is proposed for the restoration of satellite images that are highly corrupted by salt and pepper noise. Satellite images desire not only the watermarking for copyright protection but also encryption during storage and transmission for preventing information leakage. Hence this paper investigates the security and performance level of joint DWT-DCT watermarking and Advanced Encryption Standard (AES for satellite imagery. Theoretical analysis can be done by calculating PSNR and MSE. The experimental results demonstrate the efficiency of the proposed scheme, which fulfils the strict requirements concerning alterations of satellite images.

  16. Satellite image analysis for surveillance, vegetation and climate change

    Energy Technology Data Exchange (ETDEWEB)

    Cai, D Michael [Los Alamos National Laboratory


    Recently, many studies have provided abundant evidence to show the trend of tree mortality is increasing in many regions, and the cause of tree mortality is associated with drought, insect outbreak, or fire. Unfortunately, there is no current capability available to monitor vegetation changes, and correlate and predict tree mortality with CO{sub 2} change, and climate change on the global scale. Different survey platforms (methods) have been used for forest management. Typical ground-based forest surveys measure tree stem diameter, species, and alive or dead. The measurements are low-tech and time consuming, but the sample sizes are large, running into millions of trees, covering large areas, and spanning many years. These field surveys provide powerful ground validation for other survey methods such as photo survey, helicopter GPS survey, and aerial overview survey. The satellite imagery has much larger coverage. It is easier to tile the different images together, and more important, the spatial resolution has been improved such that close to or even higher than aerial survey platforms. Today, the remote sensing satellite data have reached sub-meter spatial resolution for panchromatic channels (IKONOS 2: 1 m; Quickbird-2: 0.61 m; Worldview-2: 0.5 m) and meter spatial resolution for multi-spectral channels (IKONOS 2: 4 meter; Quickbird-2: 2.44 m; Worldview-2: 2 m). Therefore, high resolution satellite imagery can allow foresters to discern individual trees. This vital information should allow us to quantify physiological states of trees, e.g. healthy or dead, shape and size of tree crowns, as well as species and functional compositions of trees. This is a powerful data resource, however, due to the vast amount of the data collected daily, it is impossible for human analysts to review the imagery in detail to identify the vital biodiversity information. Thus, in this talk, we will discuss the opportunities and challenges to use high resolution satellite imagery and

  17. Fuzzy image processing in sun sensor (United States)

    Mobasser, S.; Liebe, C. C.; Howard, A.


    This paper will describe how the fuzzy image processing is implemented in the instrument. Comparison of the Fuzzy image processing and a more conventional image processing algorithm is provided and shows that the Fuzzy image processing yields better accuracy then conventional image processing.

  18. Recognization of Satellite Images of Large Scale Data Based on Map- Reduce Framework

    Directory of Open Access Journals (Sweden)

    Vidya Jadhav,


    Full Text Available Today in the world of cloud and grid computing integration of data from heterogeneous databases is inevitable.This will become complex when size of the database is very large. M-R is a new framework specifically designed for processing huge datasets on distributed sources. Apache’s Hadoop is an implementation of M-R.Currently Hadoop has been applied successfully for file based datasets. This project proposes to utilize the parallel and distributed processing capability of Hadoop M-R for handling Images on large datasets.The presented methodology of land-cover recognition provides a scalable solution for automatic satellite imagery analysis, especially when GIS data is not readily available, or surface change may occur due to catastrophic events such as flooding, hurricane, and snow storm, etc.Here,we are using algorithms such as Image Differentiation,Image Duplication,Zoom-In,Gray-Scale.

  19. Topics in medical image processing and computational vision

    CERN Document Server

    Jorge, Renato


      The sixteen chapters included in this book were written by invited experts of international recognition and address important issues in Medical Image Processing and Computational Vision, including: Object Recognition, Object Detection, Object Tracking, Pose Estimation, Facial Expression Recognition, Image Retrieval, Data Mining, Automatic Video Understanding and Management, Edges Detection, Image Segmentation, Modelling and Simulation, Medical thermography, Database Systems, Synthetic Aperture Radar and Satellite Imagery.   Different applications are addressed and described throughout the book, comprising: Object Recognition and Tracking, Facial Expression Recognition, Image Database, Plant Disease Classification, Video Understanding and Management, Image Processing, Image Segmentation, Bio-structure Modelling and Simulation, Medical Imaging, Image Classification, Medical Diagnosis, Urban Areas Classification, Land Map Generation.   The book brings together the current state-of-the-art in the various mul...

  20. Image processing using reconfigurable FPGAs (United States)

    Ferguson, Lee


    The use of reconfigurable field-programmable gate arrays (FPGAs) for imaging applications show considerable promise to fill the gap that often occurs when digital signal processor chips fail to meet performance specifications. Single chip DSPs do not have the overall performance to meet the needs of many imaging applications, particularly in real-time designs. Using multiple DSPs to boost performance often presents major design challenges in maintaining data alignment and process synchronization. These challenges can impose serious cost, power consumption and board space penalties. Image processing requires manipulating massive amounts of data at high-speed. Although DSP chips can process data at high-speeds, their architectures can inhibit overall system performance in real-time imaging. The rate of operations can be increased when they are performed in dedicated hardware, such as special-purpose imaging devices and FPGAs, which provides the horsepower necessary to implement real-time image processing products successfully and cost-effectively. For many fixed applications, non-SRAM- based (antifuse or flash-based) FPGAs provide the raw speed to accomplish standard high-speed functions. However, in applications where algorithms are continuously changing and compute operations must be modified, only SRAM-based FPGAs give enough flexibility. The addition of reconfigurable FPGAs as a flexible hardware facility enables DSP chips to perform optimally. The benefits primarily stem from optimizing the hardware for the algorithms or the use of reconfigurable hardware to enhance the product architecture. And with SRAM-based FPGAs that are capable of partial dynamic reconfiguration, such as the Cache-Logic FPGAs from Atmel, continuous modification of data and logic is not only possible, it is practical as well. First we review the particular demands of image processing. Then we present various applications and discuss strategies for exploiting the capabilities of

  1. Potential application of Kanade-Lucas-Tomasi tracker on satellite images for automatic change detection (United States)

    Ahmed, Tasneem; Singh, Dharmendra; Raman, Balasubramanian


    Monitoring agricultural areas is still a very challenging task. Various models and methodologies have been developed for monitoring the agricultural areas with satellite images, but their practical applicability is limited due to the complexity in processing and dependence on a priori information. Therefore, in this paper, an attempt has been made to investigate the utility of the Kanade-Lucas-Tomasi (KLT) tracker, which is generally useful for tracking objects in video images, for monitoring agricultural areas. The KLT tracker was proposed to deal with the problem of image registration, but the use of the KLT tracker in satellite images for land cover monitoring is rarely reported. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) data has been used to identify and track the agricultural areas. The tracked pixels were compared with the agriculture pixels obtained from a decision tree algorithm and both results are closely matched. An image differencing change detection technique has been applied after KLT tracker implementation to observe the "change" and "no change" pixels in agricultural areas. It is observed that two kinds of changes are being detected. The areas where agriculture was not there earlier, but now is present, the changes are called positive changes. In the areas where agriculture was present earlier, but now is not present, those changes are referred to as negative changes. Unchanged areas retrieved from both the images are labeled as "no change" pixels. The novelty of the proposed algorithm is that it uses a simplified version of the KLT tracker to efficiently select and track the agriculture features on the basis of their spatial information and does not require a priori information every time.

  2. Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

    DEFF Research Database (Denmark)

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


    Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...... based 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. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method....


    National Research Council Canada - National Science Library

    Kupidura Przemysław; Skulimowska Monika


    ...: the morphological profile, and granulometric maps in detecting buildings on satellite images. It briefly explains the theoretical basis for granulometric analysis of image and compares two methods used in research...

  4. Post launch calibration and testing of the Advanced Baseline Imager on the GOES-R satellite (United States)

    Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.


    The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

  5. Differential morphology and image processing. (United States)

    Maragos, P


    Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

  6. Computational Intelligence in Image Processing

    CERN Document Server

    Siarry, Patrick


    Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the atten­tion of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research prob­lems and in real-world problems. Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can ...

  7. Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    Nina Merkle


    Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

  8. Determination of quasi-static microaccelerations onboard a satellite using video images of moving objects (United States)

    Levtov, V. L.; Romanov, V. V.; Boguslavsky, A. A.; Sazonov, V. V.; Sokolov, S. M.; Glotov, Yu. N.


    A space experiment aimed at determination of quasi-static microaccelerations onboard an artificial satellite of the Earth using video images of the objects executing free motion is considered. The experiment was carried out onboard the Foton M-3 satellite. Several pellets moved in a cubic box fixed on the satellite’s mainframe and having two transparent adjacent walls. Their motion was photographed by a digital video camera. The camera was installed facing one of the transparent walls; a mirror was placed at an angle to another transparent wall. Such an optical system allowed us to have in a single frame two images of the pellets from differing viewpoints. The motion of the pellets was photographed on time intervals lasting 96 s. Pauses between these intervals were also equal to 96 s. A special processing of a separate image allowed us to determine coordinates of the pellet centers in the camera’s coordinate system. The sequence of frames belonging to a continuous interval of photography was processed in the following way. The time dependence of each coordinate of every pellet was approximated by a second degree polynomial using the least squares method. The coefficient of squared time is equal to a half of the corresponding microacceleration component. As has been shown by processing made, the described method of determination of quasi-static microaccelerations turned out to be sufficiently sensitive and accurate.

  9. Image processing of galaxy photographs (United States)

    Arp, H.; Lorre, J.


    New computer techniques for analyzing and processing photographic images of galaxies are presented, with interesting scientific findings gleaned from the processed photographic data. Discovery and enhancement of very faint and low-contrast nebulous features, improved resolution of near-limit detail in nebulous and stellar images, and relative colors of a group of nebulosities in the field are attained by the methods. Digital algorithms, nonlinear pattern-recognition filters, linear convolution filters, plate averaging and contrast enhancement techniques, and an atmospheric deconvolution technique are described. New detail is revealed in images of NGC 7331, Stephan's Quintet, Seyfert's Sextet, and the jet in M87, via processes of addition of plates, star removal, contrast enhancement, standard deviation filtering, and computer ratioing to bring out qualitative color differences.

  10. Satellite Image Time Series Decomposition Based on EEMD

    Directory of Open Access Journals (Sweden)

    Yun-long Kong


    Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.

  11. The Advanced X-ray Imaging Satellite (AXIS) (United States)

    Reynolds, Christopher S.; Mushotzky, Richard


    The Advanced X-ray Imaging Satellite (AXIS) will follow in the footsteps of the spectacularly successful Chandra X-ray Observatory with similar or higher angular resolution and an order of magnitude more collecting area in the 0.3-10keV band. These capabilities will enable major advances in many of the most active areas of astrophysics, including (i) mapping event horizon scale structure in AGN accretion disks and the determination of supermassive black hole (SMBH) spins through monitoring of gravitationally-microlensed quasars; (ii) dramatically deepening our understanding of AGN feedback in galaxies and galaxy clusters out to high-z through the direct imaging of AGN winds and the interaction of jets with the hot interstellar/intracluster medium; (iii) understanding the fueling of AGN by probing hot flows inside of the SMBH sphere of influence; (iv) obtaining geometric distance measurements using dust scattering halos. With a nominal 2028 launch, AXIS will be enormously synergistic with LSST, ALMA, WFIRST and ATHENA, and will be a valuable precursor to Lynx. AXIS is enabled by breakthroughs in the construction of light-weight X-ray optics from mono-crystalline silicon blocks, building on recent developments in the semiconductor industry. Here, we describe the straw-man concept for AXIS, some of the high profile science that this observatory will address, and how you can become involved.

  12. Image processing system for digital chest X-ray images

    Energy Technology Data Exchange (ETDEWEB)

    Cocklin, M.; Gourlay, A.; Jackson, P.; Kaye, G.; Miessler, M. (I.B.M. U.K. Scientific Centre, Winchester (UK)); Kerr, I.; Lams, P. (Radiology Department, Brompton Hospital, London (UK))


    This paper investigates the requirements for image processing of digital chest X-ray images. These images are conventionally recorded on film and are characterised by large size, wide dynamic range and high resolution. X-ray detection systems are now becoming available for capturing these images directly in photoelectronic-digital form. The hardware and software facilities required for handling these images are described. These facilities include high resolution digital image displays, programmable video look up tables, image stores for image capture and processing and a full range of software tools for image manipulation. Examples are given of the applications of digital image processing techniques to this class of image.

  13. Attitude Control of a Satellite by using Digital Signal Processing

    Directory of Open Access Journals (Sweden)

    Adirelle C. Santana


    Full Text Available This article has discussed the development of a three-axis attitude digital controller for an artificial satellite using a digital signal processor. The main motivation of this study is the attitude control system of the satellite Multi-Mission Platform, developed by the Brazilian National Institute for Space Research for application in different sort of missions. The controller design was based on the theory of the Linear Quadratic Gaussian Regulator, synthesized from the linearized model of the motion of the satellite, i.e., the kinematics and dynamics of attitude. The attitude actuators considered in this study are pairs of cold gas jets powered by a pulse width/pulse frequency modulator. In the first stage of the project development, a system controller for continuous time was studied with the aim of testing the adequacy of the adopted control. The next steps had included an analysis of discretization techniques, the setting time of sampling rate, and the testing of the digital version of the Linear Quadratic Gaussian Regulator controller in the MATLAB/SIMULINK. To fulfill the study, the controller was implemented in a digital signal processor, specifically the Blackfin BF537 from Analog Devices, along with the pulse width/pulse frequency modulator. The validation tests used a scheme of co-simulation, where the model of the satellite was simulated in MATLAB/SIMULINK, while the controller and modulator were processed in the digital signal processor with a tool called Processor-In-the-Loop, which acted as a data communication link between both environments.function and required time to achieve a given mission accuracy are determined, and results are provided as illustration.

  14. CMOS imagers from phototransduction to image processing

    CERN Document Server

    Etienne-Cummings, Ralph


    The idea of writing a book on CMOS imaging has been brewing for several years. It was placed on a fast track after we agreed to organize a tutorial on CMOS sensors for the 2004 IEEE International Symposium on Circuits and Systems (ISCAS 2004). This tutorial defined the structure of the book, but as first time authors/editors, we had a lot to learn about the logistics of putting together information from multiple sources. Needless to say, it was a long road between the tutorial and the book, and it took more than a few months to complete. We hope that you will find our journey worthwhile and the collated information useful. The laboratories of the authors are located at many universities distributed around the world. Their unifying theme, however, is the advancement of knowledge for the development of systems for CMOS imaging and image processing. We hope that this book will highlight the ideas that have been pioneered by the authors, while providing a roadmap for new practitioners in this field to exploit exc...

  15. Fingerprint recognition using image processing (United States)

    Dholay, Surekha; Mishra, Akassh A.


    Finger Print Recognition is concerned with the difficult task of matching the images of finger print of a person with the finger print present in the database efficiently. Finger print Recognition is used in forensic science which helps in finding the criminals and also used in authentication of a particular person. Since, Finger print is the only thing which is unique among the people and changes from person to person. The present paper describes finger print recognition methods using various edge detection techniques and also how to detect correct finger print using a camera images. The present paper describes the method that does not require a special device but a simple camera can be used for its processes. Hence, the describe technique can also be using in a simple camera mobile phone. The various factors affecting the process will be poor illumination, noise disturbance, viewpoint-dependence, Climate factors, and Imaging conditions. The described factor has to be considered so we have to perform various image enhancement techniques so as to increase the quality and remove noise disturbance of image. The present paper describe the technique of using contour tracking on the finger print image then using edge detection on the contour and after that matching the edges inside the contour.

  16. An anti-image interference quadrature IF architecture for satellite receivers

    Directory of Open Access Journals (Sweden)

    He Weidong


    Full Text Available Since Global Navigation Satellite System (GNSS signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF receivers, image aliasing due to in-phase and quadrature (I/Q channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in analog-to-digital converters (ADC. As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is proposed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.

  17. An anti-image interference quadrature IF architecture for satellite receivers

    Institute of Scientific and Technical Information of China (English)

    He Weidong; Lu Xiaochun; He Chengyan; James Torley


    Since Global Navigation Satellite System (GNSS) signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF) receivers, image aliasing due to in-phase and quadrature (I/Q) channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in ana-log-to-digital converters (ADC). As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is pro-posed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR) can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.

  18. A Framework for Satellite Image Enhancement Using Quantum Genetic and Weighted IHS+Wavelet Fusion Method

    Directory of Open Access Journals (Sweden)

    Amal A. HAMED


    Full Text Available this paper examined the applicability of quantum genetic algorithms to solve optimization problems posed by satellite image enhancement techniques, particularly super-resolution, and fusion. We introduce a framework starting from reconstructing the higher-resolution panchromatic image by using the subpixel-shifts between a set of lower-resolution images (registration, then interpolation, restoration, till using the higher-resolution image in pan-sharpening a multispectral image by weighted IHS+Wavelet fusion technique. For successful super-resolution, accurate image registration should be achieved by optimal estimation of subpixel-shifts. Optimal-parameters blind restoration and interpolation should be performed for the optimal quality higher-resolution image. There is a trade-off between spatial and spectral enhancement in image fusion; it is difficult for the existing methods to do the best in both aspects. The objective here is to achieve all combined requirements with optimal fusion weights, and use the parameters constraints to direct the optimization process. QGA is used to estimate the optimal parameters needed for each mathematic model in this framework “Super-resolution and fusion.” The simulation results show that the QGA-based method can be used successfully to estimate automatically the approaching parameters which need the maximal accuracy, and achieve higher quality and efficient convergence rate more than the corresponding conventional GA-based and the classic computational methods.

  19. First Satellite Imaging of Auroral Pulsations by the Fast Auroral Imager on e-POP (United States)

    Lui, A.; Cogger, L.; Howarth, A. D.; Yau, A. W.


    We report the first satellite imaging of auroral pulsations by the Fast Auroral Imager (FAI) onboard the Enhanced Polar Outflow Probe (e-POP) satellite. The near-infrared camera of FAI is capable of providing up to two auroral images per second, ideal for investigation of pulsating auroras. The auroral pulsations were observed within the auroral bulge formed during a substorm interval on 2014 February 19. This first satellite view of these pulsations from FAI reveals that (1) several pulsating auroral channels (PACs) occur within the auroral bulge, (2) periods of the intensity pulsations span over one decade within the auroral bulge, and (3) there is no apparent trend of longer pulsation periods associated with higher latitudes for these PACs. Although PACs resemble in some respect stable pulsating auroras reported previously but they have several important differences in characteristics.PACs are not embedded in or emerging from omega bands or torches and are located at significant distances from the equatorward boundary of the auroral oval, unlike the characteristics of stable pulsating auroras.

  20. Utilizing Chinese high-resolution satellite images for inspection of unauthorized constructions in Beijing

    Institute of Scientific and Technical Information of China (English)

    LI DeRen; WANG Mi; HU Fen


    After Beijing wins the bit to host the 29th Olympic Games, in order to manifest the technical support advantages and capabilities of the autonomously-developed RS and GIS based change detection techniques in 2008 Beijing Olympic Games, and from the standpoints of executing new city planning, relieving the traffic congestion as well as maintaining the historic features, an automatic satellite monitoring system has been studied and established to accomplish the mission of unauthorized construction inspection within the Sixth Ring Road of Beijing city quarterly, by adopting the CBERS-2 satellite images and combining technologies of GIS, GPS, etc. This article discusses the applicable procedures and key issues when utilizing such Chinese satellite images and relevant techniques to discover the illegal constructions, and introduces the monitoring system from both the design and implementation aspects; additionally, some typical application cases in the practice of the system are also illustrated. The monitoring system can timely supply abundant information to facilitate the policy-making of relevant planning departments, thus providing consolidate technical support to eliminate the illegal constructing behaviors in the blossom. During the five years' excellent performance, it has helped China save large amounts of expenditures for processing of unauthorized constructed buildings.

  1. Integrated use of satellite images, DEMs, soil and substrate data in studying mountainous lands (United States)

    Giannetti, Fabio; Montanarella, Luca; Salandin, Roberto

    A method based on the integration into a GIS of satellite images of different spatial resolution (Landsat TM and SPOT), Digital Elevation Models, geo-lithological maps and some soil-landscape data was developed and applied to a test area on a sector of the Italian northwestern Alps in the Piemonte region (Pellice, Po, Varaita and Maira valleys southwest of Torino). The main working steps performed (using GIS software) in this area were: (1) acquisition of geo-lithological and geomorphological maps available and a first definition of homogeneous zones obtained by joining different classes with pedogenic criteria; (2) processing and classification of satellite images to define homogeneous areas with reference to prevailing land cover, land use pattern, relief shape and spectral characters; (3) integration of the previous two layers to obtain a first set of cartographic units showing a distinctive and often repetitive pattern of land form, land cover and parent material; and (4) processing DEMs (slope and aspect), soil or soil-landscape data in order to refine data and characterise the units. The resulting cartographic units were superimposed on a soil-landscape map realised by means of stereoscopic interpretation of aerial photographs by IPLA at the same scale (1:250,000). This comparison was used to verify the correctness of the satellite image processing steps and consistency with the map scale used. A larger scale application was also developed for grassland at 1:50,000 scale to demonstrate the practical use of remote sensing and GIS data in assisting mountainous land development.

  2. Best period for high spatial resolution satellite images for the detection of marks of buried structures

    Directory of Open Access Journals (Sweden)

    Dimitrios Kaimaris


    Full Text Available Improvements in sensor technology in recent decades led to the creation of ground, air and space imaging systems, whose data can be used in archaeological studies. Greece is one of the lucky areas that are rich in archaeological heritage. The detection of prehistoric/historic undiscovered constructions on satellite images or aerial photos is a complex and complicated matter. These marks are not visible from the ground, they can, however, be traced on satellite or aerial images, because of the differences in tone and texture. These differences appear as crop, soil and shadow marks. Undoubtedly, the detection of buried structures requires a suitable spatial resolution image, taken under appropriate meteorological conditions and during the best period of the vegetation growing cycle. According to the pertinent literature, detecting covered memorials may be achieved either accidentally or, usually, after a systematic investigation based on historical narratives. The purpose of this study is to determine the factors that facilitate or hinder the detection of buried structures through high spatial resolution satellite imagery. In this study, pan sharpened images from the QuickBird-2 satellite were used, of a spatial resolution of 0.60-0.70 m. This study concerns the detection of marks of the ancient Via Egnatia, from the ancient Amphipolis to Philippi (Eastern Macedonia, Greece. We studied different types of vegetation in the region and their phenological cycle. Taking into account the vegetation phenological cycle of the study area as well as the meteorological data, four pan sharpened QuickBird-2 images of a spatial resolution of 0.60–0.70 m. were used, during four different seasons. By processing the four images, we can determine the one acquired during the most appropriate conditions for the detection of buried structures. The application of this methodology in the study area had positive results, and not only was the main purpose of this

  3. A graph-based approach to detect spatiotemporal dynamics in satellite image time series (United States)

    Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal


    Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

  4. Comparision of Clustering Algorithms usingNeural Network Classifier for Satellite Image Classification

    Directory of Open Access Journals (Sweden)



    Full Text Available This paper presents a hybrid clustering algorithm and feed-forward neural network classifier for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for segmentation. The pre-processed image is segmented using the hybrid genetic-Artificial Bee Colony(ABC algorithm that is developed by hybridizing the ABC and FCM to obtain the effective segmentation in satellite image and classified using neural network . The performance of the proposed hybrid algorithm is compared with the algorithms like, k-means, Fuzzy C means(FCM, Moving K-means, Artificial Bee Colony(ABC algorithm, ABC-GA algorithm, Moving KFCM and KFCM algorithm.

  5. Computer image processing: Geologic applications (United States)

    Abrams, M. J.


    Computer image processing of digital data was performed to support several geological studies. The specific goals were to: (1) relate the mineral content to the spectral reflectance of certain geologic materials, (2) determine the influence of environmental factors, such as atmosphere and vegetation, and (3) improve image processing techniques. For detection of spectral differences related to mineralogy, the technique of band ratioing was found to be the most useful. The influence of atmospheric scattering and methods to correct for the scattering were also studied. Two techniques were used to correct for atmospheric effects: (1) dark object subtraction, (2) normalization of use of ground spectral measurements. Of the two, the first technique proved to be the most successful for removing the effects of atmospheric scattering. A digital mosaic was produced from two side-lapping LANDSAT frames. The advantages were that the same enhancement algorithm can be applied to both frames, and there is no seam where the two images are joined.

  6. Multimedia image and video processing

    CERN Document Server

    Guan, Ling


    As multimedia applications have become part of contemporary daily life, numerous paradigm-shifting technologies in multimedia processing have emerged over the last decade. Substantially updated with 21 new chapters, Multimedia Image and Video Processing, Second Edition explores the most recent advances in multimedia research and applications. This edition presents a comprehensive treatment of multimedia information mining, security, systems, coding, search, hardware, and communications as well as multimodal information fusion and interaction. Clearly divided into seven parts, the book begins w

  7. GIPSY : Groningen Image Processing System

    NARCIS (Netherlands)

    Allen, R. J.; Ekers, R. D.; Terlouw, J. P.; Vogelaar, M. G. R.


    GIPSY is an acronym of Groningen Image Processing SYstem. It is a highly interactive software system for the reduction and display of astronomical data. It supports multi-tasking using a versatile user interface, it has an advanced data structure, a powerful script language and good display faciliti

  8. Concept Learning through Image Processing. (United States)

    Cifuentes, Lauren; Yi-Chuan, Jane Hsieh

    This study explored computer-based image processing as a study strategy for middle school students' science concept learning. Specifically, the research examined the effects of computer graphics generation on science concept learning and the impact of using computer graphics to show interrelationships among concepts during study time. The 87…

  9. Linear Algebra and Image Processing (United States)

    Allali, Mohamed


    We use the computing technology digital image processing (DIP) to enhance the teaching of linear algebra so as to make the course more visual and interesting. Certainly, this visual approach by using technology to link linear algebra to DIP is interesting and unexpected to both students as well as many faculty. (Contains 2 tables and 11 figures.)

  10. On Processing Hexagonally Sampled Images (United States)


    Definition Addition Negation Subtraction Scalar Multiplication                  2121 2121 21 2 aacc aarr aa pp1...coordinate system for addressing a hexagonal grid that provides support for efficient image processing • Efficient ASA methods were shown for gradient

  11. The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation

    Directory of Open Access Journals (Sweden)

    Xiao-fang Xie


    Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.

  12. On the Use of Machine Vision Techniques to Detect Human Settlements in Satellite Images

    Energy Technology Data Exchange (ETDEWEB)

    Kamath, C; Sengupta, S K; Poland, D; Futterman, J A H


    The automated production of maps of human settlement from recent satellite images is essential to studies of urbanization, population movement, and the like. The spectral and spatial resolution of such imagery is often high enough to successfully apply computer vision techniques. However, vast amounts of data have to be processed quickly. In this paper, we propose an approach that processes the data in several different stages. At each stage, using features appropriate to that stage, we identify the portion of the data likely to contain information relevant to the identification of human settlements. This data is used as input to the next stage of processing. Since the size of the data has reduced, we can now use more complex features in this next stage. These features can be more representative of human settlements, and also more time consuming to extract from the image data. Such a hierarchical approach enables us to process large amounts of data in a reasonable time, while maintaining the accuracy of human settlement identification. We illustrate our multi-stage approach using IKONOS 4-band and panchromatic images, and compare it with the straight-forward processing of the entire image.

  13. Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram


    Paul, F


    Although animated images are very popular on the internet, they have so far found only limited use for glaciological applications. With long time series of satellite images becoming increasingly available and glaciers being well recognized for their rapid changes and variable flow dynamics, animated sequences of multiple satellite images reveal glacier dynamics in a time-lapse mode, making the otherwise slow changes of glacier movement visible and understandable to the wider...

  14. Assessment of temporal variations of water quality in inland water bodies using atmospheric corrected satellite remotely sensed image data. (United States)

    Hadjimitsis, Diofantos G; Clayton, Chris


    Although there have been many studies conducted on the use of satellite remote sensing for water quality monitoring and assessment in inland water bodies, relatively few studies have considered the problem of atmospheric intervention of the satellite signal. The problem is especially significant when using time series multi-spectral satellite data to monitor water quality surveillance in inland waters such as reservoirs, lakes, and dams because atmospheric effects constitute the majority of the at-satellite reflectance over water. For the assessment of temporal variations of water quality, the use of multi-date satellite images is required so atmospheric corrected image data must be determined. The aim of this study is to provide a simple way of monitoring and assessing temporal variations of water quality in a set of inland water bodies using an earth observation- based approach. The proposed methodology is based on the development of an image-based algorithm which consists of a selection of sampling area on the image (outlet), application of masking and convolution image processing filter, and application of the darkest pixel atmospheric correction. The proposed method has been applied in two different geographical areas, in UK and Cyprus. Mainly, the method has been applied to a series of eight archived Landsat-5 TM images acquired from March 1985 up to November 1985 of the Lower Thames Valley area in the West London (UK) consisting of large water treatment reservoirs. Finally, the method is further tested to the Kourris Dam in Cyprus. It has been found that atmospheric correction is essential in water quality assessment studies using satellite remotely sensed imagery since it improves significantly the water reflectance enabling effective water quality assessment to be made.

  15. A versatile system for processing geostationary satellite data with run-time visualization capability (United States)

    Landsfeld, M.; Gautier, C.; Figel, T.


    To better predict global climate change, scientists are developing climate models that require interdisciplinary and collaborative efforts in their building. We are currently involved in several such projects but will briefly discuss activities in support of two such complementary projects: the Atmospheric Radiation Measurement (ARM) program of the Department of Energy and Sequoia 2000, a joint venture of the University of California, the private sector, and government agencies. Our contribution to the ARM program is to investigate the role of clouds on the top of the atmosphere and on surface radiance fields through the data analysis of surface and satellite observations and complex modeling of the interaction of radiation with clouds. One of our first ARM research activities involves the computation of the broadband shortwave surface irradiance from satellite observations. Geostationary satellite images centered over the first ARM observation site are received hourly over the Internet network and processed in real time to compute hourly and daily composite shortwave irradiance fields. The images and the results are transferred via a high-speed network to the Sequoia 2000 storage facility in Berkeley, where they are archived These satellite-derived results are compared with the surface observations to evaluate the accuracy of the satellite estimate and the spatial representation of the surface observations. In developing the software involved in calculating the surface shortwave irradiance, we have produced an environment whereby we can easily modify and monitor the data processing as required. Through the principles of modular programming, we have developed software that is easily modified as new algorithms for computation are developed or input data availability changes. In addition, the software was designed so that it could be run from an interactive, icon-driven, graphical interface, TCL-TK, developed by Sequoia 2000 participants. In this way, the data flow

  16. An error analysis of tropical cyclone divergence and vorticity fields derived from satellite cloud winds on the Atmospheric and Oceanographic Information Processing System (AOIPS) (United States)

    Hasler, A. F.; Rodgers, E. B.


    An advanced Man-Interactive image and data processing system (AOIPS) was developed to extract basic meteorological parameters from satellite data and to perform further analyses. The errors in the satellite derived cloud wind fields for tropical cyclones are investigated. The propagation of these errors through the AOIPS system and their effects on the analysis of horizontal divergence and relative vorticity are evaluated.

  17. Solar resources estimation combining digital terrain models and satellite images techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)


    One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)

  18. Fast Road Network Extraction in Satellite Images Using Mathematical Morphology and Markov Random Fields

    Directory of Open Access Journals (Sweden)

    Thierry Géraud


    Full Text Available We present a fast method for road network extraction in satellite images. It can be seen as a transposition of the segmentation scheme “watershed transform + region adjacency graph + Markov random fields” to the extraction of curvilinear objects. Many road extractors which are composed of two stages can be found in the literature. The first one acts like a filter that can decide from a local analysis, at every image point, if there is a road or not. The second stage aims at obtaining the road network structure. In the method we propose to rely on a “potential” image, that is, unstructured image data that can be derived from any road extractor filter. In such a potential image, the value assigned to a point is a measure of its likelihood to be located in the middle of a road. A filtering step applied on the potential image relies on the area closing operator followed by the watershed transform to obtain a connected line which encloses the road network. Then a graph describing adjacency relationships between watershed lines is built. Defining Markov random fields upon this graph, associated with an energetic model of road networks, leads to the expression of road network extraction as a global energy minimization problem. This method can easily be adapted to other image processing fields, where the recognition of curvilinear structures is involved.

  19. Image processing with ImageJ

    NARCIS (Netherlands)

    Abramoff, M.D.; Magalhães, Paulo J.; Ram, Sunanda J.


    Wayne Rasband of NIH has created ImageJ, an open source Java-written program that is now at version 1.31 and is used for many imaging applications, including those that that span the gamut from skin analysis to neuroscience. ImageJ is in the public domain and runs on any operating system (OS). Image

  20. Evaluation of Satellite Image Correction Methods Caused by Differential Terrain Illumination

    Directory of Open Access Journals (Sweden)

    Purnama Budi Santosa


    Full Text Available The problem due to differential terrain illumination on satellite imagery is experienced by most of areas which are on mountainous terrain. This may cause variations in reflectance of similar ground features which lead to a misclassification of land cover classes due to different topographic positions. This phenomenon most commonly occurred in the areas which are located on southern and northern hemisphere because of the low sun inclination. This problem has been a major interest for researchers to be solved prior to the land cover classification process. For satellite images which experience this kind of problem, topographic correction need to be applied in order to reduce the illumination effects prior to land cover classification process. This research is aimed at conducting topographic correction of multi spectral SPOT satellite data as well as evaluating the three topographic correction methods. They are Cosine which is based on Lambertian reflectance assumption, as well as Minnaert correction and C correction methods which are based on non-Lambertian reflectance assumption. The data used in this study are two scenes of SPOT images of forested mountainous area of Miyazaki Prefecture, Kyushu, Japan. Research steps had been conducted in this study including geometric correction, sample data collection for calculating Minnaert constants and C constants at location which represents the whole study area, topographic correction for two scenes SPOT images, and results analysis. The results show that Cosine method did not show good performance for the study area which is topographically dominated by rugged terrain. Whereas Minnaert method and C method gave satisfactory results as is indicated by the statistical data as well as visual interpretation. However the Minnaert correction method showed slightly better performance than the C correction method.

  1. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images. (United States)

    Li, Lin; Wang, Wei; Luo, Heng; Ying, Shen


    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images.

  2. Detailed Analysis of Indian Summer Monsoon Rainfall Processes with Modern/High-Quality Satellite Observations (United States)

    Smith, Eric A.; Kuo, Kwo-Sen; Mehta, Amita V.; Yang, Song


    We examine, in detail, Indian Summer Monsoon rainfall processes using modernhigh quality satellite precipitation measurements. The focus here is on measurements derived from three NASA cloud and precipitation satellite missionslinstruments (TRMM/PR&TMI, AQUNAMSRE, and CLOUDSATICPR), and a fourth TRMM Project-generated multi-satellite precipitation measurement dataset (viz., TRMM standard algorithm 3b42) -- all from a period beginning in 1998 up to the present. It is emphasized that the 3b42 algorithm blends passive microwave (PMW) radiometer-based precipitation estimates from LEO satellites with infi-ared (IR) precipitation estimates from a world network of CEO satellites (representing -15% of the complete space-time coverage) All of these observations are first cross-calibrated to precipitation estimates taken from standard TRMM combined PR-TMI algorithm 2b31, and second adjusted at the large scale based on monthly-averaged rain-gage measurements. The blended approach takes advantage of direct estimates of precipitation from the PMW radiometerequipped LEO satellites -- but which suffer fi-om sampling limitations -- in combination with less accurate IR estimates from the optical-infrared imaging cameras on GEO satellites -- but which provide continuous diurnal sampling. The advantages of the current technologies are evident in the continuity and coverage properties inherent to the resultant precipitation datasets that have been an outgrowth of these stable measuring and retrieval technologies. There is a wealth of information contained in the current satellite measurements of precipitation regarding the salient precipitation properties of the Indian Summer Monsoon. Using different datasets obtained from the measuring systems noted above, we have analyzed the observations cast in the form of: (1) spatially distributed means and variances over the hierarchy of relevant time scales (hourly I diurnally, daily, monthly, seasonally I intra-seasonally, and inter

  3. Comparative Study of Image Denoising Algorithms in Digital Image Processing

    Directory of Open Access Journals (Sweden)



    Full Text Available This paper proposes a basic scheme for understanding the fundamentals of digital image processing and the image denising algorithm. There are three basic operation categorized on during image processing i.e. image rectification and restoration, enhancement and information extraction. Image denoising is the basic problem in digital image processing. The main task is to make the image free from Noise. Salt & pepper (Impulse noise and the additive white Gaussian noise and blurredness are the types of noise that occur during transmission and capturing. For denoising the image there are some algorithms which denoise the image.

  4. Comparative Study of Image Denoising Algorithms in Digital Image Processing

    Directory of Open Access Journals (Sweden)

    Aarti Kumari


    Full Text Available This paper proposes a basic scheme for understanding the fundamentals of digital image processing and the image denising algorithm. There are three basic operation categorized on during image processing i.e. image rectification and restoration, enhancement and information extraction. Image denoising is the basic problem in digital image processing. The main task is to make the image free from Noise. Salt & pepper (Impulse noise and the additive white Gaussian noise and blurredness are the types of noise that occur during transmission and capturing. For denoising the image there are some algorithms which denoise the image.


    Directory of Open Access Journals (Sweden)

    N. Khalili Moghadam


    Full Text Available With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user’s intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.

  6. The Black Sea coastal zone in the high resolution satellite images (United States)

    Yurovskaya, Maria; Dulov, Vladimir; Kozlov, Igor


    Landsat data with spatial resolution of 30-100 m provide the ability of regular monitoring of ocean phenomena with scale of 100-1000 m. Sentinel-1 is equipped with C-band synthetic aperture radar. The images allow recognizing the features that affect either the sea surface roughness, or its color characteristics. The possibilities of using the high spatial resolution satellite data are considered for observation and monitoring of Crimean coastal zone. The analyzed database includes all Landsat-8 (Level 1) multi-channel images from January 2013 to August 2015 and all Sentinel-1 radar images in May-August 2015. The goal of the study is to characterize the descriptiveness of these data for research and monitoring of the Crimean coastal areas. The observed marine effects are reviewed and the physical mechanisms of their signatures in the satellite images are described. The effects associated with the roughness variability are usually manifested in all bands, while the subsurface phenomena are visible only in optical data. Confidently observed structures include internal wave trains, filamentous natural slicks, which reflect the eddy coastal dynamics, traces of moving ships and the oil films referred to anthropogenic pollution of marine environment. The temperature fronts in calm conditions occur due to surfactant accumulation in convergence zone. The features in roughness field can also be manifested in Sentinel-1 data. Subsurface processes observed in Landsat-8 images primarily include transport and distribution of suspended matter as a result of floods and sandy beach erosion. The surfactant always concentrates on the sea surface in contaminated areas, so that these events are also observed in Sentinel-1 images. A search of wastewater discharge manifestations is performed. The investigation provides the basis for further development of approaches to obtain quantitative characteristics of the phenomena themselves. Funding by Russian Science Foundation under grant 15

  7. Imaging-Duration Embedded Dynamic Scheduling of Earth Observation Satellites for Emergent Events

    Directory of Open Access Journals (Sweden)

    Xiaonan Niu


    Full Text Available We present novel two-stage dynamic scheduling of earth observation satellites to provide emergency response by making full use of the duration of the imaging task execution. In the first stage, the multiobjective genetic algorithm NSGA-II is used to produce an optimal satellite imaging schedule schema, which is robust to dynamic adjustment as possible emergent events occur in the future. In the second stage, when certain emergent events do occur, a dynamic adjusting heuristic algorithm (CTM-DAHA is applied to arrange new tasks into the robust imaging schedule. Different from the existing dynamic scheduling methods, the imaging duration is embedded in the two stages to make full use of current satellite resources. In the stage of robust satellite scheduling, total task execution time is used as a robust indicator to obtain a satellite schedule with less imaging time. In other words, more imaging time is preserved for future emergent events. In the stage of dynamic adjustment, a compact task merging strategy is applied to combine both of existing tasks and emergency tasks into a composite task with least imaging time. Simulated experiments indicate that the proposed method can produce a more robust and effective satellite imaging schedule.

  8. Turbine Blade Image Processing System (United States)

    Page, Neal S.; Snyder, Wesley E.; Rajala, Sarah A.


    A vision system has been developed at North Carolina State University to identify the orientation and three dimensional location of steam turbine blades that are stacked in an industrial A-frame cart. The system uses a controlled light source for structured illumination and a single camera to extract the information required by the image processing software to calculate the position and orientation of a turbine blade in real time.

  9. Implementation Aspects of Image Processing


    Nordlöv, Per


    This Master's Thesis discusses the different trade-offs a programmer needs to consider when constructing image processing systems. First, an overview of the different alternatives available is given followed by a focus on systems based on general hardware. General, in this case, means mass-market with a low price-performance-ratio. The software environment is focused on UNIX, sometimes restricted to Linux, together with C, C++ and ANSI-standardized APIs.

  10. General logarithmic image processing convolution. (United States)

    Palomares, Jose M; González, Jesús; Ros, Eduardo; Prieto, Alberto


    The logarithmic image processing model (LIP) is a robust mathematical framework, which, among other benefits, behaves invariantly to illumination changes. This paper presents, for the first time, two general formulations of the 2-D convolution of separable kernels under the LIP paradigm. Although both formulations are mathematically equivalent, one of them has been designed avoiding the operations which are computationally expensive in current computers. Therefore, this fast LIP convolution method allows to obtain significant speedups and is more adequate for real-time processing. In order to support these statements, some experimental results are shown in Section V.

  11. Image post-processing in dental practice. (United States)

    Gormez, Ozlem; Yilmaz, Hasan Huseyin


    Image post-processing of dental digital radiographs, a function which used commonly in dental practice is presented in this article. Digital radiography has been available in dentistry for more than 25 years and its use by dental practitioners is steadily increasing. Digital acquisition of radiographs enables computer-based image post-processing to enhance image quality and increase the accuracy of interpretation. Image post-processing applications can easily be practiced in dental office by a computer and image processing programs. In this article, image post-processing operations such as image restoration, image enhancement, image analysis, image synthesis, and image compression, and their diagnostic efficacy is described. In addition this article provides general dental practitioners with a broad overview of the benefits of the different image post-processing operations to help them understand the role of that the technology can play in their practices.

  12. Using very high resolution satellite images to identify coastal zone dynamics at North Western Black Sea (United States)

    Florin Zoran, Liviu; Ionescu Golovanov, Carmen; Zoran, Maria


    The availability of updated information about the extension and characteristics of land cover is a crucial issue in the perspective of a correct landscape planning and management of marine coastal zones. Satellite remote sensing data can provide accurate information about land coverage at different scales and the recent availability of very high resolution images definitely improved the precision of coastal zone spatio-temporal changes. The Romanian North Western coastal and shelf zones of the Black Sea and Danube delta are a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in the Black Sea's ecosystem and resources are due to natural and anthropogenic causes (increase in the nutrient and pollutant load of rivers input, industrial and municipal wastewater pollution along the coast, and dumping on the open sea). A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic processes, coastal erosion, sedimentation dynamics, mapping of macrophyte fields, water quality, and climatic change effects. Use of satellite images is of great help for coastal zone monitoring and environmental impact assessment. Synergetic use of in situ measurements with multisensors satellite data could provide a complex assessment of spatio-temporal changes. In this study was developed a method for extracting coastal zone features information as well as landcover dynamics from IKONOS, very high resolution images for North-Western Black Sea marine coastal zone. The main objective was obtaining reliable data about the spatio-temporal coastal zone changes in two study areas located in Constanta urban area and Danube Delta area. We used an object-oriented approach based on preliminary segmentation and classification of the resulting object. First of all, segmentation parameters were tested and selected comparing segmented polygons with

  13. Satellite Images-based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles

    Directory of Open Access Journals (Sweden)

    Mehmet Bodur


    Full Text Available In this study, a method for the generation of tracking trajectory points, detection and positioning of obstacles in agricultural fields have been presented. Our principal contribution is to produce traceable GPS trajectories for agricultural vehicles to be utilized by path planning algorithms, rather than a new path planning algorithm. The proposed system works with minimal initialization requirements, specifically, a single geographical coordinate entry of an agricultural field. The automation of agricultural plantation requires many aspects to be addressed, many of which have been covered in previous studies. Depending on the type of crop, different agricultural vehicles may be used in the field. However, regardless of their application, they all follow a specified trajectory in the field. This study takes advantage of satellite images for the detection and positioning of obstacles, and the generation of GPS trajectories in the agricultural realm. A set of image processing techniques is applied in Matlab for detection and positioning.

  14. A method of using commercial virtual satellite image to check the pattern painting spot effect (United States)

    Wang, Zheng-gang; Kang, Qing; Shen, Zhi-qiang; Cui, Chang-bin


    A method of using commercial virtual satellite image to check the pattern painting spot effect contrast with the satellite images before painting and after painting have been discussed. Using a housetop as the testing platform analyses and discusses the factors' influence such as resolution of satellite image, spot size and color of pattern painting spot and pattern painting camouflage method choosing to the plan implement. The pattern painting design and spot size used in the testing has been ensured, and housetop pattern painting has been painted. Finally, the small spot pattern painting camouflage effect of engineering using upon painting pattern size, color and texture have been checked, contrasting with the satellite image before painting and after painting.

  15. A study on quality and availability of COCTS images of HY- 1 satellite by simulation

    Institute of Scientific and Technical Information of China (English)

    李淑菁; 毛天明; 潘德炉


    Hy-1 is a first China's ocean color satellite which will be launched as a piggyback satellite on FY- 1 satellite using Long March rocket. On the satellite there are two sensors: one is the China's ocean color and temperature scanner (COCTS), the other is CCD coastal zone imager (CZI).The COCTS is considered to be a main sensor to play a key role. In order to understand the characteristics of future ocean color images observed, a simulation and evaluation study on the quality and availability of the COCTS image has been done. First, the simulation models are introduced briefly, and typical simulated cases of radiance images at visible bands are introduced, in which the radiance distribution is based on geographic location, the satellite orbital parameters and sensor properties, the simulated method to evaluate the image quality and availability is developed by using the characteristics of image called the complex signal noise ratio ( CSNR ). Meanwhile, a series of the CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of the COCTS images before the HY - 1 is placed in orbit. Finally, the quality and availability of the COCTS images are quantitatively analyzed with the simulated CSNR data. The results will be beneficial to all scientists who are in charge of the COCTS mission and to those who plan to use the data from the COCTS.

  16. Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos (United States)

    Liang, Yu-Li

    Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

  17. NOAA Geostationary Operational Environmental Satellite (GOES) Imager Data (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Geostationary Operational Environmental Satellite (GOES) series provides continuous measurements of the atmosphere and surface over the Western Hemisphere....

  18. NEPR World View 2 Satellite Mosaic - NOAA TIFF Image (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a mosaic of World View 2 panchromatic satellite imagery of Northeast Puerto Rico that contains the shallow water area (0-35m deep) surrounding...

  19. Fast processing of foreign fiber images by image blocking

    Directory of Open Access Journals (Sweden)

    Yutao Wu


    Full Text Available In the textile industry, it is always the case that cotton products are constitutive of many types of foreign fibers which affect the overall quality of cotton products. As the foundation of the foreign fiber automated inspection, image process exerts a critical impact on the process of foreign fiber identification. This paper presents a new approach for the fast processing of foreign fiber images. This approach includes five main steps, image block, image pre-decision, image background extraction, image enhancement and segmentation, and image connection. At first, the captured color images were transformed into gray-scale images; followed by the inversion of gray-scale of the transformed images ; then the whole image was divided into several blocks. Thereafter, the subsequent step is to judge which image block contains the target foreign fiber image through image pre-decision. Then we segment the image block via OSTU which possibly contains target images after background eradication and image strengthening. Finally, we connect those relevant segmented image blocks to get an intact and clear foreign fiber target image. The experimental result shows that this method of segmentation has the advantage of accuracy and speed over the other segmentation methods. On the other hand, this method also connects the target image that produce fractures therefore getting an intact and clear foreign fiber target image.

  20. A configurable distributed high-performance computing framework for satellite's TDI-CCD imaging simulation (United States)

    Xue, Bo; Mao, Bingjing; Chen, Xiaomei; Ni, Guoqiang


    This paper renders a configurable distributed high performance computing(HPC) framework for TDI-CCD imaging simulation. It uses strategy pattern to adapt multi-algorithms. Thus, this framework help to decrease the simulation time with low expense. Imaging simulation for TDI-CCD mounted on satellite contains four processes: 1) atmosphere leads degradation, 2) optical system leads degradation, 3) electronic system of TDI-CCD leads degradation and re-sampling process, 4) data integration. Process 1) to 3) utilize diversity data-intensity algorithms such as FFT, convolution and LaGrange Interpol etc., which requires powerful CPU. Even uses Intel Xeon X5550 processor, regular series process method takes more than 30 hours for a simulation whose result image size is 1500 * 1462. With literature study, there isn't any mature distributing HPC framework in this field. Here we developed a distribute computing framework for TDI-CCD imaging simulation, which is based on WCF[1], uses Client/Server (C/S) layer and invokes the free CPU resources in LAN. The server pushes the process 1) to 3) tasks to those free computing capacity. Ultimately we rendered the HPC in low cost. In the computing experiment with 4 symmetric nodes and 1 server , this framework reduced about 74% simulation time. Adding more asymmetric nodes to the computing network, the time decreased namely. In conclusion, this framework could provide unlimited computation capacity in condition that the network and task management server are affordable. And this is the brand new HPC solution for TDI-CCD imaging simulation and similar applications.


    Directory of Open Access Journals (Sweden)

    Stefano Mugnoli


    Full Text Available ISTAT geographic data, updated to realize census 2010 project in October 2011, represents an useful resource to improve the results derived from Land cover/use cartography or satellite image processing. In fact, both ISTAT vector data and other cartography data (i.e. satellite image classification can be integrated to realize a product that can help to better understand land cover data especially in urban environment (i. e. urban sprawl, although it can’t be considered a cartography product in a strict sense. This paper summarizes an experimental study based on a LANDSAT 8 image that cover completely 5 provinces in the north of Italy, where it’s shown that ISTAT data, DEM and combine of NDVI and NDBI indices can improve the results of the satellite image classification process, especially in urban areas. Used SW: ARCGIS 10.1 for desktop (ArcInfo license and ERDAS Imagine.

  2. Review of Biomedical Image Processing

    Directory of Open Access Journals (Sweden)

    Ciaccio Edward J


    Full Text Available Abstract This article is a review of the book: 'Biomedical Image Processing', by Thomas M. Deserno, which is published by Springer-Verlag. Salient information that will be useful to decide whether the book is relevant to topics of interest to the reader, and whether it might be suitable as a course textbook, are presented in the review. This includes information about the book details, a summary, the suitability of the text in course and research work, the framework of the book, its specific content, and conclusions.

  3. Multispectral Image Processing for Plants (United States)

    Miles, Gaines E.


    The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

  4. On-Ground Processing of Yaogan-24 Remote Sensing Satellite Attitude Data and Verification Using Geometric Field Calibration. (United States)

    Wang, Mi; Fan, Chengcheng; Yang, Bo; Jin, Shuying; Pan, Jun


    Satellite attitude accuracy is an important factor affecting the geometric processing accuracy of high-resolution optical satellite imagery. To address the problem whereby the accuracy of the Yaogan-24 remote sensing satellite's on-board attitude data processing is not high enough and thus cannot meet its image geometry processing requirements, we developed an approach involving on-ground attitude data processing and digital orthophoto (DOM) and the digital elevation model (DEM) verification of a geometric calibration field. The approach focuses on three modules: on-ground processing based on bidirectional filter, overall weighted smoothing and fitting, and evaluation in the geometric calibration field. Our experimental results demonstrate that the proposed on-ground processing method is both robust and feasible, which ensures the reliability of the observation data quality, convergence and stability of the parameter estimation model. In addition, both the Euler angle and quaternion could be used to build a mathematical fitting model, while the orthogonal polynomial fitting model is more suitable for modeling the attitude parameter. Furthermore, compared to the image geometric processing results based on on-board attitude data, the image uncontrolled and relative geometric positioning result accuracy can be increased by about 50%.

  5. Cassini Imaging of Auroral Emissions on the Galilean Satellites (United States)

    Geissler, P.; McEwen, A.; Porco, C.


    Cassini captured several sequences of images showing Io, Europa and Ganymede while the moons were eclipsed by Jupiter. Io was the best studied of the satellites, with 4 eclipses successfully recorded. Earlier eclipse imaging by Galileo (Geissler et al., Science 295, 870-874) had shown colorful atmospheric emissions from Io and raised questions concerning their temporal variability and the identity of the emitting species. With its high data rate and numerous filter combinations, Cassini was able to fill some of the gaps in our knowledge of Io's visible aurorae. Io's bright equatorial glows were detected at previously unknown wavelengths and were also seen in motion. One eclipse took place on 12/29/2000 while Io was far from the plasma torus center. The pair of equatorial glows near the sub-Jupiter and anti-Jupiter points appeared about equal in brightness and changed little in location or intensity over a two hour period. Io crossed the plasma torus center during the next eclipse on 1/01/2001, as it passed through System III magnetic longitudes from 250 to 303 degrees. The equatorial glows were seen to shift in latitude during this eclipse, tracking the tangent points of the jovian magnetic field lines. This behaviour is similar to that observed for ultraviolet and other atomic emissions, and confirms that these visible glows are powered by Birkeland currents connecting Io and Jupiter. The eclipse on 1/05/2001 provided the best spectral measurements of the aurorae. The equatorial glows were detected at near ultraviolet wavelengths, consistent with their interpretation as molecular SO2 emissions. More than 100 kR were recorded in the ISS UV3 filter (300-380 nm) along with a similar intensity in BL1 (290-500 nm), comparable to Galileo estimates. At least 50 kR were detected in UV2 images (265-330 nm). No detection was made in UV1 (235-280 nm), allowing us to place an upper limit of about 100 kR. A new detection of the equatorial glows was made in the IR1 band (670

  6. Digital image processing mathematical and computational methods

    CERN Document Server

    Blackledge, J M


    This authoritative text (the second part of a complete MSc course) provides mathematical methods required to describe images, image formation and different imaging systems, coupled with the principle techniques used for processing digital images. It is based on a course for postgraduates reading physics, electronic engineering, telecommunications engineering, information technology and computer science. This book relates the methods of processing and interpreting digital images to the 'physics' of imaging systems. Case studies reinforce the methods discussed, with examples of current research

  7. Classification of textures in satellite image with Gabor filters and a multi layer perceptron with back propagation algorithm obtaining high accuracy

    Directory of Open Access Journals (Sweden)

    Adriano Beluco, Paulo M. Engel, Alexandre Beluco


    Full Text Available The classification of images, in many cases, is applied to identify an alphanumeric string, a facial expression or any other characteristic. In the case of satellite images is necessary to classify all the pixels of the image. This article describes a supervised classification method for remote sensing images that integrates the importance of attributes in selecting features with the efficiency of artificial neural networks in the classification process, resulting in high accuracy for real images. The method consists of a texture segmentation based on Gabor filtering followed by an image classification itself with an application of a multi layer artificial neural network with a back propagation algorithm. The method was first applied to a synthetic image, like training, and then applied to a satellite image. Some results of experiments are presented in detail and discussed. The application of the method to the synthetic image resulted in the identification of 89.05% of the pixels of the image, while applying to the satellite image resulted in the identification of 85.15% of the pixels. The result for the satellite image can be considered a result of high accuracy.

  8. Neural Network Change Detection Model for Satellite Images Using Textural and Spectral Characteristics

    Directory of Open Access Journals (Sweden)

    A. K. Helmy


    Full Text Available Problem statement: Change detection is the process of identifying difference of the state of an object or phenomena by observing it at different time. Essentially, it involves the ability to quantify temporal effects using multi-temporal data sets. Information about change is necessary for evaluating land cover and the management of natural resources. Approach: A neural network model based on both spectral and textural analysis is developed. Change detection system in this study is presented using modified version of back-propagation-training algorithm with dynamic learning rate and momentum. Through proposed model, the two images at different dates are fed into the input layer of neural network, in addition with Variance, Skewness and Eculedian for each image that represent different texture measure. This leads to better discrimination process. Results: The results showed that the trained network with texture measures achieve 23% higher accuracy than that without textural parameters. Conclusion: Adding textural parameters of satellite images through training phase increases the efficiently of change detection process also, it provides adequate information about the type of changes. It also found, when using dynamic momentum and learning rate, time and effort needed to select their appropriate value is reduced.

  9. Deep and shallow structures in the Arctic region imaged by satellite magnetic and gravity data (United States)

    Gaina, Carmen; Panet, Isabelle; Shephard, Grace


    The last decade has seen an increase in geoscientific data collection, which, together with available and older classified data made publicly available, is contributing to increasing our knowledge about Earth's structure and evolution. Despite this development, there are many gaps in data coverage in remote, hard-to-access regions. Satellite data have the advantage of acquiring measurements steadily and covering the entire globe. From a tectonics point of view, the specific heights of various satellites allow for the identification of moderate to large tectonic features, and can shed light on Earth's lower crust and lithosphere structure. In this contribution I discuss the use of magnetic and gravity models based on satellite data in deciphering the tectonic structure of remote areas. The present day Circum-Arctic region comprises a variety of tectonic settings: from active seafloor spreading in the North Atlantic and Eurasian Basin, and subduction in the North Pacific, to long-lived stable continental platforms in North America and Asia. A series of rifted margins, abandoned rifted areas and presumably extinct oceanic basins fringe these regions. Moreover, rifting- and seafloor spreading-related processes formed many continental splinters and terranes that were transported and docked at higher latitudes. Volcanic provinces of different ages have also been identified, from the Permian-Triassic Siberian traps at ca. 251 Ma to the (presumably) Cretaceous HALIP and smaller Cenozoic provinces in northern Greenland and the Barents Sea. We inspect global lithospheric magnetic data in order to identify the signature of the main volcanic provinces in the High Arctic. One of the most striking features in the Arctic domain is the strong magnetic anomaly close to the North Pole that correlates with a large, igneous oceanic plateau called the Alpha Mendeleev Ridge. The intensity and extent of the magnetic anomalies recorded by aircraft or satellites point towards a very thick

  10. Super-resolution post-processing for satellites with yaw-steering capability

    CSIR Research Space (South Africa)

    Van den Dool, R


    Full Text Available We describe a method for improving Earth observation satellite image resolution, for specific areas of interest where the sensor design resolution is insufficient. Our method may be used for satellites with yaw-steering capability, such as NigeriaSat...

  11. Building identification from very high-resolution satellite images (United States)

    Lhomme, Stephane

    (geometric and radiometric quality), the basic image of our analysis. A review of existing methods clearly show a common limit: the detection of building boundaries. Consequently, we evaluate the efficiency of several segmentation methods that finally induces a change in our methodological approach. The fourth chapter contains the central part of our work, which consists in the development of a building extraction method. After strict formalisation of our, objectives, we present the theoretical principles of our approach based on textural buildings definition. In the identification process we use only one parameter that accounts at the same time for the variance of the building and the variance of its immediate surroundings. In the following, additional information (shadow and vegetation) is integrated to reduce commission errors. The last chapter exposes the results. They clearly show the capacity of our method for building identification. However, they show some limitations of application, especially on large size buildings and/or in heterogeneous areas. We also propose possible applications such as analysis of suburban buildings or detection of natural disaster damages. The main outcome of this work is the originality of our theoretical approach that encourages new reflections for future research.

  12. Power Processing Unit For Micro Satellite Electric Propulsion System

    Directory of Open Access Journals (Sweden)

    Savvas Spiridon


    Full Text Available The Micro Satellite Electric Propulsion System (MEPS program has been originated by the increasing need to provide a low-cost and low-power Electric Propulsion System (EPS for small satellites ( 92%, small size and weight and high reliability. Its functional modules and preliminary results obtained at breadboard level are also presented.

  13. Autonomous Sub-Pixel Satellite Track Endpoint Determination for Space Based Images

    Energy Technology Data Exchange (ETDEWEB)

    Simms, L M


    An algorithm for determining satellite track endpoints with sub-pixel resolution in spaced-based images is presented. The algorithm allows for significant curvature in the imaged track due to rotation of the spacecraft capturing the image. The motivation behind the subpixel endpoint determination is first presented, followed by a description of the methodology used. Results from running the algorithm on real ground-based and simulated spaced-based images are shown to highlight its effectiveness.

  14. Three attempts of earthquake prediction with satellite cloud images

    Directory of Open Access Journals (Sweden)

    G. Guangmeng


    Full Text Available Thermal anomalies detected from satellite data are widely reported. Nearly all the anomalies are reported after the quake. Here we report three earthquake predictions in Italy and Iran according to satellite cloud anomalies. These cloud anomalies usually show a linear pattern, stay there for hours and do not move with winds. According to these anomalies, we can give a rough estimation about impending earthquake activities. All the estimated dates and magnitudes are in good agreement with the earthquake facts, and the only unsatisfactory point is that the distance error is 100–300 km. Because the cloud anomaly is long, we can not reduce the distance error further. A possible way is to combine geophysical data and satellite data together to estimate the epicenter and this will increase the prediction accuracy.

  15. Fast Fractal Compression of Satellite and Medical Images Based on Domain-Range Entropy

    Directory of Open Access Journals (Sweden)

    Ramesh Babu Inampudi


    Full Text Available Fractal image Compression is a lossy compression technique developed in the early 1990s. It makes use of the local self-similarity property existing in an image and finds a contractive mapping affine transformation (fractal transformT, such that the fixed point of T is close to the given image in a suitable metric. It has generated much interest due to its promise of high compression ratios with good decompression quality. The other advantage is its multi resolution property, i.e. an image can be decoded at higher or lower resolutions than the original without much degradation in quality. However, the encoding time is computationally intensive. In this paper, a fast fractal image compression method based on the domain-range entropy is proposed to reduce the encoding time, while maintaining the fidelity and compression ratio of the decoded image. The method is a two-step process. First, domains that are similar i.e. domains having nearly equal variances are eliminated from the domain pool. Second, during the encoding phase, only domains and ranges having equal entropies (with an adaptive error threshold, λdepth for each quadtree depth are compared for a match within the rms error tolerance. As a result, many unqualified domains are removed from comparison and a significant reduction in encoding time is expected. The method is applied for compression of satellite and medical images (512x512, 8-bit gray scale. Experimental results show that the proposed method yields superior performance over Fisher’s classified search and other methods.

  16. Precision Navigation of Cassini Images Using Rings, Icy Satellites, and Fuzzy Bodies (United States)

    French, Robert S.; Showalter, Mark R.; Gordon, Mitchell K.


    Before images from the Cassini spacecraft can be analyzed, errors in the published pointing information (up to ~110 pixels for the Imaging Science Subsystem Narrow Angle Camera) must be corrected so that the line of sight vector for each pixel is known. This complicated and labor-intensive process involves matching the image contents with known features such as stars, rings, or moons. Metadata, such as lighting geometry or ring radius and longitude, must be computed for each pixel as well. Both steps require mastering the SPICE toolkit, a highly capable piece of software with a steep learning curve. Only after these steps are completed can the actual scientific investigation begin.We have embarked on a three-year project to perform these steps for all 400,000+ Cassini ISS images as well as images taken by the VIMS, UVIS, and CIRS instruments. The result will be a series of SPICE kernels that include accurate pointing information and a series of backplanes that include precomputed metadata for each pixel. All data will be made public through the PDS Ring-Moon Systems Node ( We expect this project to dramatically decrease the time required for scientists to analyze Cassini data.In a previous poster (French et al. 2014, DPS #46, 422.01) we discussed our progress navigating images using stars, simple ring models, and well-defined icy bodies. In this poster we will report on our current progress including the use of more sophisticated ring models, navigation of "fuzzy" bodies such as Titan and Saturn, and use of crater matching on high-resolution images of the icy satellites.

  17. Wildfire monitoring using satellite images, ontologies and linked geospatial data

    NARCIS (Netherlands)

    Kyzirakos, K.; Karpathiotakis, M.; Garbis, G.; Nikolaou, C.; Bereta, K.; Papoutsis, I.; Herekakis, T.; Michail, D.; Koubarakis, M.; Kontoes, C.


    Advances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation data archives have been constantly increasing in size in the last few years, and have become a valuable source of data for many scientific and

  18. Remote sensing place : Satellite images as visual spatial imaginaries

    NARCIS (Netherlands)

    Shim, David

    How do people come to know the world? How do they get a sense of place and space? Arguably, one of the ways in which they do this is through the practice of remote sensing, among which satellite imagery is one of the most widespread and potent tools of engaging, representing and constructing space.

  19. Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction (United States)

    Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.


    Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively

  20. Image Post-Processing in Dental Practice


    Gormez, Ozlem; Yilmaz, Hasan Huseyin


    Image post-processing of dental digital radiographs, a function which used commonly in dental practice is presented in this article. Digital radiography has been available in dentistry for more than 25 years and its use by dental practitioners is steadily increasing. Digital acquisition of radiographs enables computer-based image post-processing to enhance image quality and increase the accuracy of interpretation. Image post-processing applications can easily be practiced in dental office by ...

  1. Interactive Image Processing demonstrations for the web


    Tella Amo, Marcel


    The main goal in this project is to improve the way how image processing developers can test their algorithms, and show them to other people to demonstrate their performance. This diploma thesis aims to provide a framework for developing web applications for ImagePlus, the software develpment platform in C++ of the Image Processing Group of the Technical University of Catalonia (UPC). These web applications are to demonstrate the functionality of the image processing algorithms to any ...

  2. Crop Investigation Using High-Resolution Worldview-1 and Quickbird-2 Satellite Images on a Test Site in Bulgaria (United States)

    Vassilev, Vassil


    The paper aims to investigate the capabilities of using high-resolution satellite images: panchromatic WorldView-1 satellite image acquired on 30/11/2011 and multispectral QuickBird-2 satellite image acquired on 31/05/2009 for crop analysis, which includes crop identification, crop condition assessment and crop area estimates applications in Bulgaria using the power and flexibility of ERDAS IMAGINE tools. The crop identification was accomplished using unsupervised and supervised classification processing techniques using as reference ground data. After the supervised classification, fuzzy convolution filter was applied to reduce the mixed pixels using ERDAS Imagine software. Accuracy totals, error matrix and kappa statistics were calculated using accuracy assessment tool in ERDAS Imagine to assess the quality of the classification process. Crop condition assessment was accomplished using the derived Normalized Difference Vegetation Index (NDVI) image from the QuickBird-2 image, which was reclassified and was given meaningful estimations on the crop condition. Crop area was estimated using pixel counting approach. Pixel counting methods are known for introducing bias to the crop area estimates but using the high Overall Accuracy of 90.86% and overall Kappa Statistics of 0.8538 for the classified QuickBird-2 image and Overall Accuracy of 86.71% and overall Kappa Statistics of 0.7721% for the classified WorldView-1 allows that option to be utilized according to (Gallego, 2004). As a conclusion it can be stated that using the benefits that high-resolution satellite images gives in combination with the power and flexibility of ERDAS Imagine tools, crop identification can be achieved more accurately by increasing the identification accuracy and also by having the necessary ground information for selecting appropriate training samples. Crop identification by applying an arable mask is better practice, because it is reducing the mixed pixels problem i.e. also known as

  3. Scilab and SIP for Image Processing

    CERN Document Server

    Fabbri, Ricardo; Costa, Luciano da Fontoura


    This paper is an overview of Image Processing and Analysis using Scilab, a free prototyping environment for numerical calculations similar to Matlab. We demonstrate the capabilities of SIP -- the Scilab Image Processing Toolbox -- which extends Scilab with many functions to read and write images in over 100 major file formats, including PNG, JPEG, BMP, and TIFF. It also provides routines for image filtering, edge detection, blurring, segmentation, shape analysis, and image recognition. Basic directions to install Scilab and SIP are given, and also a mini-tutorial on Scilab. Three practical examples of image analysis are presented, in increasing degrees of complexity, showing how advanced image analysis techniques seems uncomplicated in this environment.

  4. Eliminating "Hotspots" in Digital Image Processing (United States)

    Salomon, P. M.


    Signals from defective picture elements rejected. Image processing program for use with charge-coupled device (CCD) or other mosaic imager augmented with algorithm that compensates for common type of electronic defect. Algorithm prevents false interpretation of "hotspots". Used for robotics, image enhancement, image analysis and digital television.


    Directory of Open Access Journals (Sweden)

    H. Miyazaki


    Full Text Available We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST, Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel-based cloud assessment and pixel value correction over seasonal variations.

  6. Tensors in image processing and computer vision

    CERN Document Server

    De Luis García, Rodrigo; Tao, Dacheng; Li, Xuelong


    Tensor signal processing is an emerging field with important applications to computer vision and image processing. This book presents the developments in this branch of signal processing, offering research and discussions by experts in the area. It is suitable for advanced students working in the area of computer vision and image processing.

  7. Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management. (United States)

    Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn


    Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. The Compact High Resolution Imaging Spectrometer (CHRIS): the future of hyperspectral satellite sensors. Imagery of Oostende coastal and inland waters


    B. De Mol; Ruddick, K


    The gap between airborne imaging spectroscopy and traditional multi spectral satellite sensors is decreasing thanks to a new generation of satellite sensors of which CHRIS mounted on the small and low-cost PROBA satellite is the prototype. Although image acquisition and analysis are still in a test phase, the high spatial and spectral resolution and pointability have proved their potential. Because of the high resolution small features, which were before only visible on airborne images, becom...

  9. Adaptive Optics for Satellite and Debris Imaging in LEO and GEO (United States)

    Copeland, M.; Bennet, F.; Zovaro, A.; Riguat, F.; Piatrou, P.; Korkiakoski, V.; Smith, C.


    The Research School of Astronomy and Astrophysics (RSAA) at the Australian National University has developed and Adaptive Optics (AO) system for satellite and debris imaging in low Earth orbit (LEO) and geostationary orbit (GEO). In LEO the size, shape and orientation of objects will be measured with resolution of 50 cm for objects at 800 km range at an 800 nm imaging wavelength. In GEO satellite position will be measured using precision astrometry of nearby stars. We use an AO system with a deformable mirror (DM) of 277 actuators and Shack-Hartmann wavefront sensor operating at 2 kHz. Imaging is performed at a rate of >30 Hz to reduce image blur due to tip-tilt and rotation. We use two imaging modes; a high resolution mode to obtain Nyquist sampled images and a acquisition mode with 75 arcsecond field of view to aid in finding targets.

  10. Biomass prediction model in maize based on satellite images (United States)

    Mihai, Herbei; Florin, Sala


    Monitoring of crops by satellite techniques is very useful in the context of precision agriculture, regarding crops management and agricultural production. The present study has evaluated the interrelationship between maize biomass production and satellite indices (NDVI and NDBR) during five development stages (BBCH code), highlighting different levels of correlation. Biomass production recorded was between 2.39±0.005 t ha-1 (12-13 BBCH code) and 51.92±0.028 t ha-1 (83-85 BBCH code), in relation to vegetation stages studied. Values of chlorophyll content ranged from 24.1±0.25 SPAD unit (12-13 BBCH code) to 58.63±0.47 SPAD unit (71-73 BBCH code), and the obtained satellite indices ranged from 0.035641±0.002 and 0.320839±0.002 for NDVI indices respectively 0.035095±0.034 and 0.491038±0.018 in the case of NDBR indices. By regression analysis it was possible to obtain predictive models of biomass in maize based on the satellite indices, in statistical accurate conditions. The most accurate prediction was possible based on NDBR index (R2 = 0.986, F = 144.23, p<0.001, RMSE = 1.446), then based on chlorophyll content (R2 = 0.834, F = 16.14, p = 0.012, RMSE = 6.927) and NDVI index (R2 = 0.682, F = 3.869, p = 0.116, RMSE = 12.178).

  11. Nightfire method to track volcanic eruptions from multispectral satellite images (United States)

    Trifonov, Grigory; Zhizhin, Mikhail; Melnikov, Dmitry


    This work presents the first results of an application of the Nightfire hotspot algorithm towards volcano activity detection. Nightfire algorithm have been developed to play along with a Suomi-NPP polar satellite launched in 2011, which has a new generation multispectral VIIRS thermal sensor on board, to detect gas flares related to the upstream and downstream production of oil and natural gas. Simultaneously using of nighttime data in SWIR, MWIR, and LWIR sensor bands the algorithm is able to estimate the hotspot temperature, size and radiant heat. Four years of non-filtered observations have been accumulated in a spatio-temporal detection database, which currently totals 125 GB in size. The first part of this work presents results of retrospective cross-match of the detection database with the publicly available observed eruptions databases. The second part discusses how an approximate 3D shape of a lava lake could be modeled based on the apparent source size and satellite zenith angle. The third part presents the results of fusion Landsat-8 and Himawari-8 satellites data with the VIIRS Nightfire for several active volcanoes.

  12. Updating Object for GIS Database Information Using High Resolution Satellite Images: a Case Study Zonguldak (United States)

    Alkan, M.; Arca, D.; Bayik, Ç.; Marangoz, A. M.


    Nowadays Geographic Information Systems (GIS) uses Remote Sensing (RS) data for a lot of applications. One of the application areas is the updating of the GIS database using high resolution imagery. In this context high resolution satellite imagery data is very important for many applications areas today's and future. And also, high resolution satellite imagery data will be used in many applications for different purposes. Information systems needs to high resolution imagery data for updating. Updating is very important component for the any of the GIS systems. One of this area will be updated and kept alive GIS database information. High resolution satellite imagery is used with different data base which serve map information via internet and different aims of information systems applications in future topographic and cartographic information systems will very important in our country in this sense use of the satellite images will be unavoidable. In this study explain to how is acquired to satellite images and how is use this images in information systems for object and roads. Firstly, pan-sharpened two of the IKONOS's images have been produced by fusion of high resolution PAN and MS images using PCI Geomatica v9.1 software package. Automatic object extraction has been made using eCognition v4.0.6. On the other hand, these objects have been manually digitized from high resolution images using ArcGIS v9.3. software package. Application section of in this study, satellite images data will be compared each other and GIS objects and road database. It is also determined which data is useful in Geographic Information Systems. Finally, this article explains that integration of remote sensing technology and GIS applications.

  13. Fuzzy image processing and applications with Matlab

    CERN Document Server

    Chaira, Tamalika


    In contrast to classical image analysis methods that employ ""crisp"" mathematics, fuzzy set techniques provide an elegant foundation and a set of rich methodologies for diverse image-processing tasks. However, a solid understanding of fuzzy processing requires a firm grasp of essential principles and background knowledge.Fuzzy Image Processing and Applications with MATLAB® presents the integral science and essential mathematics behind this exciting and dynamic branch of image processing, which is becoming increasingly important to applications in areas such as remote sensing, medical imaging,

  14. Combining image-processing and image compression schemes (United States)

    Greenspan, H.; Lee, M.-C.


    An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

  15. Continuous evaluation of land cover restoration of tsunami struck plains in Japan by using several kinds of optical satellite image in time series (United States)

    Hashiba, H.


    The Mw 9.0 earthquake that struck Japan in 2011 was followed by a large-scale tsunami in the Tohoku region. The damage in the coastal plane was extensively displayed through many satellite images. Furthermore, satellite imaging is requested for the ongoing evaluation of the restoration process. The reconstruction of the urban structure, farmlands, grassland, and coastal forest that collapsed under the large tsunami requires effective long-term monitoring. Moreover, the post-tsunami land cover dynamics can be effectively modeled using time-constrained satellite data to establish a prognosis method for the mitigation of future tsunami impact. However, the remote satellite capture of a long-term restoration process is compromised by accumulating spatial resolution effects and seasonal influences. Therefore, it is necessary to devise a method for data selection and dataset structure. In the present study, the restoration processes were investigated in four years following the disaster in a part of the Sendai plain, northeast Japan, from same-season satellite images acquired by different optical sensors. Coastal plains struck by the tsunami are evaluated through land-cover classification processing using the clustering method. The changes in land cover are analyzed from time-series optical images acquired by Landsat-5/TM, 7/ETM+, 8/OLI, EO-1/ALI, and ALOS-1/AVNIR-2. The study reveals several characteristics of the change in the inundation area and signs of artificial and natural restoration.

  16. Object Based and Pixel Based Classification Using Rapideye Satellite Imager of ETI-OSA, Lagos, Nigeria


    Esther Oluwafunmilayo Makinde; Ayobami Taofeek Salami; James Bolarinwa Olaleye; Oluwapelumi Comfort Okewusi


    Several studies have been carried out to find an appropriate method to classify the remote sensing data. Traditional classification approaches are all pixel-based, and do not utilize the spatial information within an object which is an important source of information to image classification. Thus, this study compared the pixel based and object based classification algorithms using RapidEye satellite image of Eti-Osa LGA, Lagos. In the object-oriented approach, the image was segmented to homog...

  17. Developing an efficient technique for satellite image denoising and resolution enhancement for improving classification accuracy (United States)

    Thangaswamy, Sree Sharmila; Kadarkarai, Ramar; Thangaswamy, Sree Renga Raja


    Satellite images are corrupted by noise during image acquisition and transmission. The removal of noise from the image by attenuating the high-frequency image components removes important details as well. In order to retain the useful information, improve the visual appearance, and accurately classify an image, an effective denoising technique is required. We discuss three important steps such as image denoising, resolution enhancement, and classification for improving accuracy in a noisy image. An effective denoising technique, hybrid directional lifting, is proposed to retain the important details of the images and improve visual appearance. The discrete wavelet transform based interpolation is developed for enhancing the resolution of the denoised image. The image is then classified using a support vector machine, which is superior to other neural network classifiers. The quantitative performance measures such as peak signal to noise ratio and classification accuracy show the significance of the proposed techniques.

  18. Trend Assessment of Spatio-Temporal Change of Tehran Heat Island Using Satellite Images (United States)

    Saradjian, M. R.; Sherafati, Sh.


    Numerous investigations on Urban Heat Island (UHI) show that land cover change is the main factor of increasing Land Surface Temperature (LST) in urban areas, especially conversion of vegetation and bare soil to concrete, asphalt and other man-made structures. On the other hand, other human activities like those which cause to burning fossil fuels, that increase the amount of carbon dioxide, may raise temperature in global scale in comparison with small scales (urban areas). In this study, multiple satellite images with different spatial and temporal resolutions have been used to determine Land Surface Temperature (LST) variability in Tehran metropolitan area. High temporal resolution of AVHRR images have been used as the main data source when investigating temperature variability in the urban area. The analysis shows that UHI appears more significant at afternoon and night hours. But the urban class temperature is almost equal to its surrounding vegetation and bare soil classes at around noon. It also reveals that there is no specific difference in UHI intense during the days throughout the year. However, it can be concluded that in the process of city expansion in years, UHI has been grown both spatially and in magnitude. In order to locate land-cover types and relate them to LST, Thematic Mapper (TM) images have been exploited. The influence of elevation on the LST has also been studied, using digital elevation model derived from SRTM database.


    Directory of Open Access Journals (Sweden)

    M. R. Saradjian


    Full Text Available Numerous investigations on Urban Heat Island (UHI show that land cover change is the main factor of increasing Land Surface Temperature (LST in urban areas, especially conversion of vegetation and bare soil to concrete, asphalt and other man-made structures. On the other hand, other human activities like those which cause to burning fossil fuels, that increase the amount of carbon dioxide, may raise temperature in global scale in comparison with small scales (urban areas. In this study, multiple satellite images with different spatial and temporal resolutions have been used to determine Land Surface Temperature (LST variability in Tehran metropolitan area. High temporal resolution of AVHRR images have been used as the main data source when investigating temperature variability in the urban area. The analysis shows that UHI appears more significant at afternoon and night hours. But the urban class temperature is almost equal to its surrounding vegetation and bare soil classes at around noon. It also reveals that there is no specific difference in UHI intense during the days throughout the year. However, it can be concluded that in the process of city expansion in years, UHI has been grown both spatially and in magnitude. In order to locate land-cover types and relate them to LST, Thematic Mapper (TM images have been exploited. The influence of elevation on the LST has also been studied, using digital elevation model derived from SRTM database.

  20. Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images

    CERN Document Server

    Kodge, B G


    In this paper, we study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery, and to detect changes from the extracted open space area during the period 2003, 2006 and 2008. This automatic extraction and change detection algorithm uses some filters, segmentation and grouping that are applied on satellite images. The resultant images may be used to calculate the total available open space area and the built up area. It may also be used to compare the difference between present and past open space area using historical urban satellite images of that same projection, which is an important geo spatial data management application.

  1. Mesh Processing in Medical Image Analysis

    DEFF Research Database (Denmark)

    The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation....

  2. An overview of medical image processing methods

    African Journals Online (AJOL)



    Jun 14, 2010 ... theoretical subjects about methods and algorithms used are explained. In the forth section, ... image processing techniques such as image segmentation, compression .... A convolution mask like -1 | 0 | 1 could be used in each.

  3. Programmable remapper for image processing (United States)

    Juday, Richard D. (Inventor); Sampsell, Jeffrey B. (Inventor)


    A video-rate coordinate remapper includes a memory for storing a plurality of transformations on look-up tables for remapping input images from one coordinate system to another. Such transformations are operator selectable. The remapper includes a collective processor by which certain input pixels of an input image are transformed to a portion of the output image in a many-to-one relationship. The remapper includes an interpolative processor by which the remaining input pixels of the input image are transformed to another portion of the output image in a one-to-many relationship. The invention includes certain specific transforms for creating output images useful for certain defects of visually impaired people. The invention also includes means for shifting input pixels and means for scrolling the output matrix.

  4. Mesh Processing in Medical Image Analysis

    DEFF Research Database (Denmark)

    The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation.......The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation....


    Directory of Open Access Journals (Sweden)

    P. Javadi


    Full Text Available The best technique to extract information from remotely sensed image is classification. The problem of traditional classification methods is that each pixel is assigned to a single class by presuming all pixels within the image. Mixed pixel classification or spectral unmixing, is a process that extracts the proportions of the pure components of each mixed pixel. This approach is called spectral unmixing. Hyper spectral images have higher spectral resolution than multispectral images. In this paper, pixel-based classification methods such as the spectral angle mapper, maximum likelihood classification and subpixel classification method (linear spectral unmixing were implemented on the AVIRIS hyper spectral images. Then, pixel-based and subpixel based classification algorithms were compared. Also, the capabilities and advantages of spectral linear unmixing method were investigated. The spectral unmixing method that implemented here is an effective technique for classifying a hyperspectral image giving the classification accuracy about 89%. The results of classification when applying on the original images are not good because some of the hyperspectral image bands are subject to absorption and they contain only little signal. So it is necessary to prepare the data at the beginning of the process. The bands can be stored according to their variance. In bands with a high variance, we can distinguish the features from each other in a better mode in order to increase the accuracy of classification. Also, applying the MNF transformation on the hyperspectral images increase the individual classes accuracy of pixel based classification methods as well as unmixing method about 20 percent and 9 percent respectively.

  6. Amplitude image processing by diffractive optics. (United States)

    Cagigal, Manuel P; Valle, Pedro J; Canales, V F


    In contrast to the standard digital image processing, which operates over the detected image intensity, we propose to perform amplitude image processing. Amplitude processing, like low pass or high pass filtering, is carried out using diffractive optics elements (DOE) since it allows to operate over the field complex amplitude before it has been detected. We show the procedure for designing the DOE that corresponds to each operation. Furthermore, we accomplish an analysis of amplitude image processing performances. In particular, a DOE Laplacian filter is applied to simulated astronomical images for detecting two stars one Airy ring apart. We also check by numerical simulations that the use of a Laplacian amplitude filter produces less noisy images than the standard digital image processing.

  7. Study of Image Processing, Enhancement and Restoration

    Directory of Open Access Journals (Sweden)

    Bhausaheb Shivajirao Shinde


    Full Text Available Digital image processing is a means by which the valuable information in observed raw image data can be revealed. A web-based image processing pipeline was created under the ambitious educational program Venus Transit 2004 (VT-2004. The active participants in the VT-2004 can apply the basic processing methods to the images obtained by their amateur telescopes and/or they can process an image observed at any observatory involved in the project. The processed result image is displayed immediately on the display. Above that all participants can follow the distance Sun-Venus centers computation performed at the professional observatory in the real time. There is a possibility to submit an image from their own observation into the database. It will be used for the distance Earth-Sun computation.

  8. Image processing in medical ultrasound

    DEFF Research Database (Denmark)

    Hemmsen, Martin Christian

    as a double blinded study. The result of the pre-clinical trialmotivated for a larger scale clinical trial. Each of the two clinical trials were performed in collaboration with Copenhagen University Hospital, Rigshospitalet, and Copenhagen University, Department of Biostatistic. Evaluations were performed...... by medical doctors and experts in ultrasound, using the developed Image Quality assessment program (IQap). The study concludes that the image quality in terms of spatial resolution, contrast and unwanted artifacts is statistically better using SASB imaging than conventional imaging. The third and final...

  9. Image processing in diabetic related causes

    CERN Document Server

    Kumar, Amit


    This book is a collection of all the experimental results and analysis carried out on medical images of diabetic related causes. The experimental investigations have been carried out on images starting from very basic image processing techniques such as image enhancement to sophisticated image segmentation methods. This book is intended to create an awareness on diabetes and its related causes and image processing methods used to detect and forecast in a very simple way. This book is useful to researchers, Engineers, Medical Doctors and Bioinformatics researchers.

  10. A methodology for near real-time change detection between Unmanned Aerial Vehicle and wide area satellite images (United States)

    Fytsilis, Anastasios L.; Prokos, Anthony; Koutroumbas, Konstantinos D.; Michail, Dimitrios; Kontoes, Charalambos C.


    In this paper a novel integrated hybrid methodology for unsupervised change detection between Unmanned Aerial Vehicle (UAV) and satellite images, which can be utilized in various fields like security applications (e.g. border surveillance) and damage assessment, is proposed. This is a challenging problem mainly due to the difference in geographic coverage and the spatial resolution of the two images, as well as to the acquisition modes which lead to misregistration errors. The methodology consists of the following steps: (a) pre-processing, where the part of the satellite image that corresponds to the UAV image is determined and the UAV image is ortho-rectified using information provided by a Digital Terrain Model, (b) the detection of potential changes, which is based exclusively on intensity and image gradient information, (c) the generation of the region map, where homogeneous regions are produced by the previous potential changes via a seeded region growing algorithm and placed on the region map, and (d) the evaluation of the above regions, in order to characterize them as true changes or not. The methodology has been applied on demanding real datasets with very encouraging results. Finally, its robustness to the misregistration errors is assessed via extensive experimentation.

  11. A Multi-stage Method to Extract Road from High Resolution Satellite Image (United States)

    Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang


    Extracting road information from high-resolution satellite images is complex and hardly achieves by exploiting only one or two modules. This paper presents a multi-stage method, consisting of automatic information extraction and semi-automatic post-processing. The Multi-scale Enhancement algorithm enlarges the contrast of human-made structures with the background. The Statistical Region Merging segments images into regions, whose skeletons are extracted and pruned according to geometry shape information. Setting the start and the end skeleton points, the shortest skeleton path is constructed as a road centre line. The Bidirectional Adaptive Smoothing technique smoothens the road centre line and adjusts it to right position. With the smoothed line and its average width, a Buffer algorithm reconstructs the road region easily. Seen from the last results, the proposed method eliminates redundant non-road regions, repairs incomplete occlusions, jumps over complete occlusions, and reserves accurate road centre lines and neat road regions. During the whole process, only a few interactions are needed.

  12. Effective System for Automatic Bundle Block Adjustment and Ortho Image Generation from Multi Sensor Satellite Imagery (United States)

    Akilan, A.; Nagasubramanian, V.; Chaudhry, A.; Reddy, D. Rajesh; Sudheer Reddy, D.; Usha Devi, R.; Tirupati, T.; Radhadevi, P. V.; Varadan, G.


    Block Adjustment is a technique for large area mapping for images obtained from different remote sensingsatellites.The challenge in this process is to handle huge number of satellite imageries from different sources with different resolution and accuracies at the system level. This paper explains a system with various tools and techniques to effectively handle the end-to-end chain in large area mapping and production with good level of automation and the provisions for intuitive analysis of final results in 3D and 2D environment. In addition, the interface for using open source ortho and DEM references viz., ETM, SRTM etc. and displaying ESRI shapes for the image foot-prints are explained. Rigorous theory, mathematical modelling, workflow automation and sophisticated software engineering tools are included to ensure high photogrammetric accuracy and productivity. Major building blocks like Georeferencing, Geo-capturing and Geo-Modelling tools included in the block adjustment solution are explained in this paper. To provide optimal bundle block adjustment solution with high precision results, the system has been optimized in many stages to exploit the full utilization of hardware resources. The robustness of the system is ensured by handling failure in automatic procedure and saving the process state in every stage for subsequent restoration from the point of interruption. The results obtained from various stages of the system are presented in the paper.

  13. Improving a DWT-based compression algorithm for high image-quality requirement of satellite images (United States)

    Thiebaut, Carole; Latry, Christophe; Camarero, Roberto; Cazanave, Grégory


    Past and current optical Earth observation systems designed by CNES are using a fixed-rate data compression processing performed at a high-rate in a pushbroom mode (also called scan-based mode). This process generates fixed-length data to the mass memory and data downlink is performed at a fixed rate too. Because of on-board memory limitations and high data rate processing needs, the rate allocation procedure is performed over a small image area called a "segment". For both PLEIADES compression algorithm and CCSDS Image Data Compression recommendation, this rate allocation is realised by truncating to the desired rate a hierarchical bitstream of coded and quantized wavelet coefficients for each segment. Because the quantisation induced by truncation of the bit planes description is the same for the whole segment, some parts of the segment have a poor image quality. These artefacts generally occur in low energy areas within a segment of higher level of energy. In order to locally correct these areas, CNES has studied "exceptional processing" targeted for DWT-based compression algorithms. According to a criteria computed for each part of the segment (called block), the wavelet coefficients can be amplified before bit-plane encoding. As usual Region of Interest handling, these multiplied coefficients will be processed earlier by the encoder than in the nominal case (without exceptional processing). The image quality improvement brought by the exceptional processing has been confirmed by visual image analysis and fidelity criteria. The complexity of the proposed improvement for on-board application has also been analysed.

  14. A new tool for supervised classification of satellite images available on web servers: Google Maps as a case study (United States)

    García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun


    This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.

  15. Coordination in serial-parallel image processing (United States)

    Wójcik, Waldemar; Dubovoi, Vladymyr M.; Duda, Marina E.; Romaniuk, Ryszard S.; Yesmakhanova, Laura; Kozbakova, Ainur


    Serial-parallel systems used to convert the image. The control of their work results with the need to solve coordination problem. The paper summarizes the model of coordination of resource allocation in relation to the task of synchronizing parallel processes; the genetic algorithm of coordination developed, its adequacy verified in relation to the process of parallel image processing.

  16. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods (United States)

    Osipov, Gennady


    We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode

  17. Global near real-time disturbance monitoring using MODIS satellite image time series (United States)

    Verbesselt, J.; Kalomenopoulos, M.; de Jong, R.; Zeileis, A.; Herold, M.


    Global disturbance monitoring in forested ecosystems is critical to retrieve information on carbon storage dynamics, biodiversity, and other socio-ecological processes. Satellite remote sensing provides a means for cost-effective monitoring at frequent time steps over large areas. However, for information about current change processes, it is required to analyse image time series in a fast and accurate manner and to detect abnormal change in near real time. An increasing number of change detection techniques have become available that are able to process historical satellite image time series data to detect changes in the past. However, methods that detect changes near real-time, i.e. analysing newly acquired data with respect to the historical series, are lacking. We propose a statistical technique for monitoring change in near-real time by comparing current data with a seasonal-trend model fitted onto the historical time series. As such, identification of consistent and abnormal change in near-real time becomes possible as soon as new image data is captured. The method is based on the "Break For Additive Seasonal Trend" (BFAST) concept ( Disturbances are detected by analysing 16-daily MODIS combined vegetation and temperature indices. Validation is carried out by comparing the detected disturbances with available disturbance data sets (e.g. deforestation in Brazil and MODIS fire products). Preliminary results demonstrated that abrupt changes at the end of time series can be successfully detected while the method remains robust for strong seasonality and atmospheric noise. Cloud masking, however, was identified as a critical issue since periods of persistent cloudiness can be detected as abnormal change. The proposed method is an automatic and robust change detection approach that can be applied on different types of data (e.g. future sensors like the Sentinel constellation that provide higher spatial resolution at regular time

  18. Thematic mapping from satellite imagery

    CERN Document Server

    Denègre, J


    Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

  19. Gemini Planet Imager Observational Calibrations VIII: Characterization and Role of Satellite Spots

    CERN Document Server

    Wang, Jason J; Graham, James R; Savransky, Dmitry; Ingraham, Patrick J; Ward-Duong, Kimberly; Patience, Jennifer; De Rosa, Robert J; Bulger, Joanna; Sivaramakrishnan, Anand; Perrin, Marshall D; Thomas, Sandrine J; Sadakuni, Naru; Greenbaum, Alexandra Z; Pueyo, Laurent; Marois, Christian; Oppenheimer, Ben R; Kalas, Paul; Cardwell, Andrew; Goodsell, Stephen; Hibon, Pascale; Rantakyrö, Fredrik T


    The Gemini Planet Imager (GPI) combines extreme adaptive optics, an integral field spectrograph, and a high performance coronagraph to directly image extrasolar planets in the near-infrared. Because the coronagraph blocks most of the light from the star, it prevents the properties of the host star from being measured directly. Instead, satellite spots, which are created by diffraction from a square grid in the pupil plane, can be used to locate the star and extract its spectrum. We describe the techniques implemented into the GPI Data Reduction Pipeline to measure the properties of the satellite spots and discuss the precision of the reconstructed astrometry and spectrophotometry of the occulted star. We find the astrometric precision of the satellite spots in an $H$-band datacube to be $0.05$ pixels and is best when individual satellite spots have a signal to noise ratio (SNR) of $> 20$. In regards to satellite spot spectrophotometry, we find that the total flux from the satellite spots is stable to $\\sim 7\\...

  20. Crater Relaxation and Stereo Imaging of the Icy Satellites of Jupiter and Saturn (United States)

    Phillips, C. B.; Beyer, R. A.; Nimmo, F.; Roberts, J. H.; Robuchon, G.


    Crater relaxation has been used as a probe of subsurface temperature structure for over thirty years, both on terrestrial bodies and icy satellites. We are developing and testing two independent methods for processing stereo pairs to produce digital elevation models, to address how crater relaxation depends on crater diameter, geographic location, and stratigraphic position on the icy satellites of Jupiter and Saturn. Our topographic profiles will then serve as input into two numerical models, one viscous and one viscoelastic, to allow us to probe the subsurface thermal profiles and relaxation histories of these satellites. We are constructing stereo topography from Galileo and Cassini image pairs using the NASA Ames Stereo Pipeline (Moratto et al. 2010), an automated stereogrammetry tool designed for processing planetary imagery captured from orbiting and landed robotic explorers on other planets. We will also be using the commercial program SOCET SET from BAE Systems (Miller and Walker 1993; 1995). Qualitatively, it is clear that there are large spatial variations in the degree of crater relaxation among Jupiter’s and Saturn’s satellites. However, our use of stereo topography will allow quantitative measures of crater relaxation (e.g. depth:diameter ratio or equivalent) to be derived. Such measures are essential to derive quantitative estimates of the heat fluxes responsible for this relaxation. Estimating how surface heat flux has varied with time provides critical constraints on satellite thermal (and orbital) evolution. Craters undergo viscous relaxation over time at a rate that depends on the temperature gradient and crater scale. We are investigating how the near-surface satellite heat flux varied in time and space, based on our crater relaxation observations. Once we have crater profiles from our DEMs, we use them as input to two theoretical approaches: a relatively simple (viscous) numerical model in which time-varying heat fluxes can be included, and

  1. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images (United States)

    Dabrowska-Zielinska, K.; Budzynska, M.; Kowalik, W.; Turlej, K.


    The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  2. A DHIP Algorithm for SAR Satellite Imaging Planning%SAR卫星成像任务规划的DHIP方法

    Institute of Scientific and Technical Information of China (English)

    朱小满; 王钧; 李军; 景宁


    The emergence of earth observing satellite with Synthetic Aperture Radar (SAR) onboard provides a significant instrument to obtain geo-space information. This paper studies rightly on the SAR satellite imaging planning problem. Firstly, the general imaging process of SAR satellite is described to illustrate that the methods pertinent to optical satellite imaging planning are no longer suitable for the problem of a SAR satellite imaging planning. Secondly, the main influential constraints of SAR satellite are induced. Based on that, an approach called DHIP (Double Hierarchy Insert Planning) is proposed and described detailedly. The main idea of this method is to form an optimized scheme by tentatively inserting every candidate imaging request through two hierarchies, which are the hierarchy of SAR opening and closing, and that of photographing, by a checking while constructing method. The final experimental results show that the DHIP algorithm works fast and is able to get a satisfying scheme under general circumstances.%合成孔径雷达(SAR)卫星的出现为获取地球空间信息提供了重要手段,本文研究的即是SAR卫星成像任务规划问题.首先描述了SAR成像卫星的一般工作流程,说明针对可见光卫星进行成像任务规划的方法不再适用于SAR成像卫星任务规划;然后归纳了影响SAR卫星成像的主要约束.在此基础上,提出了双层插入规划(DHIP)方法,该方法将待规划任务在星载SAR开关机信息元组级和成像信息元组级两个层级上逐次进行试探性插入,采用边构造边检测的方法获得该问题的优化解.实验结果表明,该方法计算速度快,可以有效解决SAR卫星成像任务规划问题.

  3. Flood hazard and flood risk assessment using a time series of satellite images: a case study in Namibia. (United States)

    Skakun, Sergii; Kussul, Nataliia; Shelestov, Andrii; Kussul, Olga


    In this article, the use of time series of satellite imagery to flood hazard mapping and flood risk assessment is presented. Flooded areas are extracted from satellite images for the flood-prone territory, and a maximum flood extent image for each flood event is produced. These maps are further fused to determine relative frequency of inundation (RFI). The study shows that RFI values and relative water depth exhibit the same probabilistic distribution, which is confirmed by Kolmogorov-Smirnov test. The produced RFI map can be used as a flood hazard map, especially in cases when flood modeling is complicated by lack of available data and high uncertainties. The derived RFI map is further used for flood risk assessment. Efficiency of the presented approach is demonstrated for the Katima Mulilo region (Namibia). A time series of Landsat-5/7 satellite images acquired from 1989 to 2012 is processed to derive RFI map using the presented approach. The following direct damage categories are considered in the study for flood risk assessment: dwelling units, roads, health facilities, and schools. The produced flood risk map shows that the risk is distributed uniformly all over the region. The cities and villages with the highest risk are identified. The proposed approach has minimum data requirements, and RFI maps can be generated rapidly to assist rescuers and decisionmakers in case of emergencies. On the other hand, limitations include: strong dependence on the available data sets, and limitations in simulations with extrapolated water depth values.

  4. Digital signal processing techniques and applications in radar image processing

    CERN Document Server

    Wang, Bu-Chin


    A self-contained approach to DSP techniques and applications in radar imagingThe processing of radar images, in general, consists of three major fields: Digital Signal Processing (DSP); antenna and radar operation; and algorithms used to process the radar images. This book brings together material from these different areas to allow readers to gain a thorough understanding of how radar images are processed.The book is divided into three main parts and covers:* DSP principles and signal characteristics in both analog and digital domains, advanced signal sampling, and

  5. Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera. (United States)

    Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng


    The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

  6. Effect of satellite formations and imaging modes on global albedo estimation (United States)

    Nag, Sreeja; Gatebe, Charles K.; Miller, David W.; de Weck, Olivier L.


    We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static referencecase. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/m2 or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than

  7. The application of very high resolution satellite image in urban vegetation cover investigation: a case study of Xiamen City

    Institute of Scientific and Technical Information of China (English)

    CHENGChengqi; LiBin; MATing


    With the technological improvements of satellite sensors, we will acquire more information about the earth so that we have reached a new application epoch of observation on earth environmental change and cartography. But with the enhancement of spatial resolution, some questions have arisen in the application of using traditional image processing and classification methods. Aiming for such questions, we studied the application of IKONOS very high resolution image (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the difference between the very high resolution image and traditional low spatial resolution image at classification,information abstraction etc. It is an advantageous test for the large-scale application of very high resolution data in the future.

  8. Computers in Public Schools: Changing the Image with Image Processing. (United States)

    Raphael, Jacqueline; Greenberg, Richard


    The kinds of educational technologies selected can make the difference between uninspired, rote computer use and challenging learning experiences. University of Arizona's Image Processing for Teaching Project has worked with over 1,000 teachers to develop image-processing techniques that provide students with exciting, open-ended opportunities for…

  9. Fuzzy Methods and Image Fusion in a Digital Image Processing

    Directory of Open Access Journals (Sweden)

    Jaroslav Vlach


    Full Text Available Although the basics of image processing were laid more than 50 years ago, significant development occurred mainly in the last 25 years with the entrance of personal computers and today's problems are already very sophisticated and quick. This article is a contribution to the study of the use of fuzzy logic methods and image fusion for image processing using LabVIEW tools for quality management, in this case especially in the jewelry industry.  

  10. Image quality dependence on image processing software in computed radiography

    Directory of Open Access Journals (Sweden)

    Lourens Jochemus Strauss


    Full Text Available Background. Image post-processing gives computed radiography (CR a considerable advantage over film-screen systems. After digitisation of information from CR plates, data are routinely processed using manufacturer-specific software. Agfa CR readers use MUSICA software, and an upgrade with significantly different image appearance was recently released: MUSICA2. Aim. This study quantitatively compares the image quality of images acquired without post-processing (flatfield with images processed using these two software packages. Methods. Four aspects of image quality were evaluated. An aluminium step-wedge was imaged using constant mA at tube voltages varying from 40 to 117kV. Signal-to-noise ratios (SNRs and contrast-to-noise Ratios (CNRs were calculated from all steps. Contrast variation with object size was evaluated with visual assessment of images of a Perspex contrast-detail phantom, and an image quality figure (IQF was calculated. Resolution was assessed using modulation transfer functions (MTFs. Results. SNRs for MUSICA2 were generally higher than the other two methods. The CNRs were comparable between the two software versions, although MUSICA2 had slightly higher values at lower kV. The flatfield CNR values were better than those for the processed images. All images showed a decrease in CNRs with tube voltage. The contrast-detail measurements showed that both MUSICA programmes improved the contrast of smaller objects. MUSICA2 was found to give the lowest (best IQF; MTF measurements confirmed this, with values at 3.5 lp/mm of 10% for MUSICA2, 8% for MUSICA and 5% for flatfield. Conclusion. Both MUSICA software packages produced images with better contrast resolution than unprocessed images. MUSICA2 has slightly improved image quality than MUSICA.

  11. A fast and automatic mosaic method for high-resolution satellite images (United States)

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


    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.

  12. Meteo-marine parameters for highly variable environment in coastal regions from satellite radar images (United States)

    Pleskachevsky, A. L.; Rosenthal, W.; Lehner, S.


    The German Bight of the North Sea is the area with highly variable sea state conditions, intensive ship traffic and with a high density of offshore installations, e.g. wind farms in use and under construction. Ship navigation and the docking on offshore constructions is impeded by significant wave heights HS > 1.3 m. For these reasons, improvements are required in recognition and forecasting of sea state HS in the range 0-3 m. Thus, this necessitates the development of new methods to determine the distribution of meteo-marine parameters from remote sensing data with an accuracy of decimetres for HS. The operationalization of these methods then allows the robust automatic processing in near real time (NRT) to support forecast agencies by providing validations for model results. A new empirical algorithm XWAVE_C (C = coastal) for estimation of significant wave height from X-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed, adopted for coastal applications using TerraSAR-X (TS-X) and Tandem-X (TD-X) satellites in the German Bight and implemented into the Sea Sate Processor (SSP) for fully automatic processing for NRT services. The algorithm is based on the spectral analysis of subscenes and the model function uses integrated image spectra parameters as well as local wind information from the analyzed subscene. The algorithm is able to recognize and remove the influence of non-sea state produced signals in the Wadden Sea areas such as dry sandbars as well as nonlinear SAR image distortions produced by e.g. short wind waves and breaking waves. Also parameters of very short waves, which are not visible in SAR images and produce only unsystematic clutter, can be accurately estimated. The SSP includes XWAVE_C, a pre-filtering procedure for removing artefacts such as ships, seamarks, buoys, offshore constructions and slicks, and an additional procedure performing a check of results based on the statistics of the whole scene. The SSP allows an

  13. A cloud solution for medical image processing

    Directory of Open Access Journals (Sweden)

    Ali Mirarab,


    Full Text Available The rapid growth in the use of Electronic Health Records across the globe along with the rich mix of multimedia held within an EHR combined with the increasing level of detail due to advances in diagnostic medical imaging means increasing amounts of data can be stored for each patient. Also lack of image processing and analysis tools for handling the large image datasets has compromised researchers and practitioner‟s outcome. Migrating medical imaging applications and data to the Cloud can allow healthcare organizations to realize significant cost savings relating to hardware, software, buildings, power and staff, in addition to greater scalability, higher performance and resilience. This paper reviews medical image processing and its challenges, states cloud computing and cloud computing benefits due to medical image processing. Also, this paper introduces tools and methods for medical images processing using the cloud. Finally a method is provided for medical images processing based on Eucalyptus cloud infrastructure with image processing software “ImageJ” and using improved genetic algorithm for the allocation and distribution of resources. Based on conducted simulations and experimental results, the proposed method brings high scalability, simplicity, flexibility and fully customizability in addition to 40% cost reduction and twice increase in speed.

  14. Special Software for Planetary Image Processing and Research (United States)

    Zubarev, A. E.; Nadezhdina, I. E.; Kozlova, N. A.; Brusnikin, E. S.; Karachevtseva, I. P.


    The special modules of photogrammetric processing of remote sensing data that provide the opportunity to effectively organize and optimize the planetary studies were developed. As basic application the commercial software package PHOTOMOD™ is used. Special modules were created to perform various types of data processing: calculation of preliminary navigation parameters, calculation of shape parameters of celestial body, global view image orthorectification, estimation of Sun illumination and Earth visibilities from planetary surface. For photogrammetric processing the different types of data have been used, including images of the Moon, Mars, Mercury, Phobos, Galilean satellites and Enceladus obtained by frame or push-broom cameras. We used modern planetary data and images that were taken over the years, shooting from orbit flight path with various illumination and resolution as well as obtained by planetary rovers from surface. Planetary data image processing is a complex task, and as usual it can take from few months to years. We present our efficient pipeline procedure that provides the possibilities to obtain different data products and supports a long way from planetary images to celestial body maps. The obtained data - new three-dimensional control point networks, elevation models, orthomosaics - provided accurate maps production: a new Phobos atlas (Karachevtseva et al., 2015) and various thematic maps that derived from studies of planetary surface (Karachevtseva et al., 2016a).

  15. Applied medical image processing a basic course

    CERN Document Server

    Birkfellner, Wolfgang


    A widely used, classroom-tested text, Applied Medical Image Processing: A Basic Course delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. Avoiding excessive mathematical formalisms, the book presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data and illustrations on an accompanying CD-ROM or companion website. Organized as a complete textbook, it provides an overview of the physics of medical image processing and discusses image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction.

  16. Wave Period and Coastal Bathymetry Estimations from Satellite Images (United States)

    Danilo, Celine; Melgani, Farid


    We present an approach for wave period and coastal water depth estimation. The approach based on wave observations, is entirely independent of ancillary data and can theoretically be applied to SAR or optical images. In order to demonstrate its feasibility we apply our method to more than 50 Sentinel-1A images of the Hawaiian Islands, well-known for its long waves. Six wave buoys are available to compare our results with in-situ measurements. The results on Sentinel-1A images show that half of the images were unsuitable for applying the method (no swell or wavelength too small to be captured by the SAR). On the other half, 78% of the estimated wave periods are in accordance with buoy measurements. In addition, we present preliminary results of the estimation of the coastal water depth on a Landsat-8 image (with characteristics close to Sentinel-2A). With a squared correlation coefficient of 0.7 for ground truth measurement, this approach reveals promising results for monitoring coastal bathymetry.

  17. Detection of facilities in satellite imagery using semi-supervized image classification and auxiliary contextual observables (United States)

    Harvey, Neal R.; Ruggiero, C.; Pawley, N. H.; MacDonald, B.; Oyer, A.; Balick, L.; Brumby, S. P.


    Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervised assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.

  18. Improvement of dem Generation from Aster Images Using Satellite Jitter Estimation and Open Source Implementation (United States)

    Girod, L.; Nuth, C.; Kääb, A.


    The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a source of stereoscopic images covering the whole globe at a 15m resolution at a consistent quality for over 15 years. The potential of this data in terms of geomorphological analysis and change detection in three dimensions is unrivaled and needs to be exploited. However, the quality of the DEMs and ortho-images currently delivered by NASA (ASTER DMO products) is often of insufficient quality for a number of applications such as mountain glacier mass balance. For this study, the use of Ground Control Points (GCPs) or of other ground truth was rejected due to the global "big data" type of processing that we hope to perform on the ASTER archive. We have therefore developed a tool to compute Rational Polynomial Coefficient (RPC) models from the ASTER metadata and a method improving the quality of the matching by identifying and correcting jitter induced cross-track parallax errors. Our method outputs more accurate DEMs with less unmatched areas and reduced overall noise. The algorithms were implemented in the open source photogrammetric library and software suite MicMac.

  19. Detection of facilities in satellite imagery using semi-supervised image classification and auxiliary contextual observables

    Energy Technology Data Exchange (ETDEWEB)

    Harvey, Neal R [Los Alamos National Laboratory; Ruggiero, Christy E [Los Alamos National Laboratory; Pawley, Norma H [Los Alamos National Laboratory; Brumby, Steven P [Los Alamos National Laboratory; Macdonald, Brian [Los Alamos National Laboratory; Balick, Lee [Los Alamos National Laboratory; Oyer, Alden [Los Alamos National Laboratory


    Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervised assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.

  20. The Need of Nested Grids for Aerial and Satellite Images and Digital Elevation Models (United States)

    Villa, G.; Mas, S.; Fernández-Villarino, X.; Martínez-Luceño, J.; Ojeda, J. C.; Pérez-Martín, B.; Tejeiro, J. A.; García-González, C.; López-Romero, E.; Soteres, C.


    Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites) pose big interoperability problems, as for example: non-alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression-decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in "Big Data" environments. Most of them can be avoided, or at least greatly reduced, with the use of a common "nested grid" for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. "Nested grids" are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A "nested grid" must be complemented by an appropriate "tiling schema", ideally based on the "quad-tree" concept. In the last years a "de facto standard" grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its "WMTS Simple Profile" standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.

  1. Attitude motion compensation for imager on Fengyun-4 geostationary meteorological satellite (United States)

    Lyu, Wang; Dai, Shoulun; Dong, Yaohai; Shen, Yili; Song, Xiaozheng; Wang, Tianshu


    A compensation method is used in Chinese Fengyun-4 satellite to counteracting the line-of-sight influence by attitude motion during imaging. The method is acted on-board by adding the compensation amount to the instrument scanning control circuit. The mathematics simulation and the three-axis air-bearing test results show that the method works effectively.

  2. Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis (United States)

    Potter, Christopher S.


    Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).

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


    Marc Wieland; Massimiliano Pittore


    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 recognitio...

  4. Mapping land cover from satellite images: A basic, low cost approach (United States)

    Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.


    Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

  5. Extraction of DTM from Satellite Images Using Neural Networks


    Tapper, Gustav


    This thesis presents a way to generate a Digital Terrain Model (dtm) from a Digital Surface Model (dsm) and multi spectral images (including the Near Infrared (nir) color band). An Artificial Neural Network (ann) is used to pre-classify the dsm and multi spectral images. This in turn is used to filter the dsm to a dtm. The use of an ann as a classifier provided good results. Additionally, the addition of the nir color band resulted in an improvement of the accuracy of the classifier. Using th...

  6. Quantitative image processing in fluid mechanics (United States)

    Hesselink, Lambertus; Helman, James; Ning, Paul


    The current status of digital image processing in fluid flow research is reviewed. In particular, attention is given to a comprehensive approach to the extraction of quantitative data from multivariate databases and examples of recent developments. The discussion covers numerical simulations and experiments, data processing, generation and dissemination of knowledge, traditional image processing, hybrid processing, fluid flow vector field topology, and isosurface analysis using Marching Cubes.

  7. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A


    Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

  8. Water surface capturing by image processing (United States)

    An alternative means of measuring the water surface interface during laboratory experiments is processing a series of sequentially captured images. Image processing can provide a continuous, non-intrusive record of the water surface profile whose accuracy is not dependent on water depth. More trad...

  9. [The model of adaptive primary image processing]. (United States)

    Dudkin, K N; Mironov, S V; Dudkin, A K; Chikhman, V N


    A computer model of adaptive segmentation of the 2D visual objects was developed. Primary image descriptions are realised via spatial frequency filters and feature detectors performing as self-organised mechanisms. Simulation of the control processes related to attention, lateral, frequency-selective and cross-orientation inhibition, determines the adaptive image processing.

  10. Image processing techniques for remote sensing data

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.

    interpretation and for processing of scene data for autonomous machine perception. The technique of digital image processing are used for' automatic character/pattern recognition, industrial robots for product assembly and inspection, military recognizance... number of techniques have been suggested for restoration 37 of degraded images like inverse filter, wiener filter and constrained least square filter etc. The primary objective of scene analysis is to deduce from a single two dimensional image...

  11. 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


    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.

  12. SUPRIM: easily modified image processing software. (United States)

    Schroeter, J P; Bretaudiere, J P


    A flexible, modular software package intended for the processing of electron microscopy images is presented. The system consists of a set of image processing tools or filters, written in the C programming language, and a command line style user interface based on the UNIX shell. The pipe and filter structure of UNIX and the availability of command files in the form of shell scripts eases the construction of complex image processing procedures from the simpler tools. Implementation of a new image processing algorithm in SUPRIM may often be performed by construction of a new shell script, using already existing tools. Currently, the package has been used for two- and three-dimensional image processing and reconstruction of macromolecules and other structures of biological interest.

  13. Image processing and communications challenges 5

    CERN Document Server


    This textbook collects a series of research papers in the area of Image Processing and Communications which not only introduce a summary of current technology but also give an outlook of potential feature problems in this area. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in image processing and communications. The book is divided into two parts. Part I deals with image processing. A comprehensive survey of different methods  of image processing, computer vision  is also presented. Part II deals with the telecommunications networks and computer networks. Applications in these areas are considered. In conclusion, the edited book comprises papers on diverse aspects of image processing  and communications systems. There are theoretical aspects as well as application papers.

  14. Evidence of hydrocarbon pollution in soil exploiting satellite optical and radar images (United States)

    Monsivais-Huertero, A.; Galvan-Pineda, J.; Espinosa-Hernandez, A.; Jimenez-Escalona, J. C.; Ramos-Rodriguez, J. M.


    Oil spills are one of the most important sources of hydrocarbon pollution in soils of areas near centers of extraction, storage or transportation of petroleum products. These spills or leaks can occur arising from deficient maintenance of facilities or accidents. The effects of these spills can spread for kilometers affecting large areas. This has a strong impact on the local ecosystem disturbing the flora and fauna. In costal tourist areas, this type of contaminants represents significant health risks for visitors and therefore, economic losses for the place. For this reason, it is very important to know and identify the areas affected by this type of pollution in order to create action plans for remediation of the ecosystem. Due to the large land extensions that can cover such disasters, satellite images become a valuable tool because of their large spatial coverage. Nowadays, different satellite techniques have been developed to recognize land affected by the presence of hydrocarbons. In the optical spectrum, optical sensing imagery (e.g. Landsat, SPOT, MODIS, etc.) has been widely used. However, these techniques have the intrinsic limitation in scenes with vegetation cover. In contrast, techniques exploiting radar images are still rare. The type of signal that is detected by the radar provides information even in areas with vegetation cover. The radar signal interacts with the vegetation and soil collecting information about the dielectric properties of the soil. This study identifies zones of contaminated soil by using the synergy of optical and radar images. This site of study is located in Paraiso, Tabasco, in Southern Mexico (18°27'N 93°32'W). The region is composed of coastal and tropical forest ecosystems and includes the Port Dos Bocas. The Port Dos Bocas has its points of extractions 130m away from the coast. The annual activities report 10 millions of tons of hydrocarbons transported using around 5500 ships. The methodology presented in this paper

  15. 3D mapping from high resolution satellite images (United States)

    Goulas, D.; Georgopoulos, A.; Sarakenos, A.; Paraschou, Ch.


    In recent years 3D information has become more easily available. Users' needs are constantly increasing, adapting to this reality and 3D maps are in more demand. 3D models of the terrain in CAD or other environments have already been common practice; however one is bound by the computer screen. This is why contemporary digital methods have been developed in order to produce portable and, hence, handier 3D maps of various forms. This paper deals with the implementation of the necessary procedures to produce holographic 3D maps and three dimensionally printed maps. The main objective is the production of three dimensional maps from high resolution aerial and/or satellite imagery with the use of holography and but also 3D printing methods. As study area the island of Antiparos was chosen, as there were readily available suitable data. These data were two stereo pairs of Geoeye-1 and a high resolution DTM of the island. Firstly the theoretical bases of holography and 3D printing are described, and the two methods are analyzed and there implementation is explained. In practice a x-axis parallax holographic map of the Antiparos Island is created and a full parallax (x-axis and y-axis) holographic map is created and printed, using the holographic method. Moreover a three dimensional printed map of the study area has been created using 3dp (3d printing) method. The results are evaluated for their usefulness and efficiency.

  16. Topic Modelling for Object-Based Unsupervised Classification of VHR Panchromatic Satellite Images Based on Multiscale Image Segmentation

    Directory of Open Access Journals (Sweden)

    Li Shen


    Full Text Available Image segmentation is a key prerequisite for object-based classification. However, it is often difficult, or even impossible, to determine a unique optimal segmentation scale due to the fact that various geo-objects, and even an identical geo-object, present at multiple scales in very high resolution (VHR satellite images. To address this problem, this paper presents a novel unsupervised object-based classification for VHR panchromatic satellite images using multiple segmentations via the latent Dirichlet allocation (LDA model. Firstly, multiple segmentation maps of the original satellite image are produced by means of a common multiscale segmentation technique. Then, the LDA model is utilized to learn the grayscale histogram distribution for each geo-object and the mixture distribution of geo-objects within each segment. Thirdly, the histogram distribution of each segment is compared with that of each geo-object using the Kullback-Leibler (KL divergence measure, which is weighted with a constraint specified by the mixture distribution of geo-objects. Each segment is allocated a geo-object category label with the minimum KL divergence. Finally, the final classification map is achieved by integrating the multiple classification results at different scales. Extensive experimental evaluations are designed to compare the performance of our method with those of some state-of-the-art methods for three different types of images. The experimental results over three different types of VHR panchromatic satellite images demonstrate the proposed method is able to achieve scale-adaptive classification results, and improve the ability to differentiate the geo-objects with spectral overlap, such as water and grass, and water and shadow, in terms of both spatial consistency and semantic consistency.

  17. Digital radiography image quality: image processing and display. (United States)

    Krupinski, Elizabeth A; Williams, Mark B; Andriole, Katherine; Strauss, Keith J; Applegate, Kimberly; Wyatt, Margaret; Bjork, Sandra; Seibert, J Anthony


    This article on digital radiography image processing and display is the second of two articles written as part of an intersociety effort to establish image quality standards for digital and computed radiography. The topic of the other paper is digital radiography image acquisition. The articles were developed collaboratively by the ACR, the American Association of Physicists in Medicine, and the Society for Imaging Informatics in Medicine. Increasingly, medical imaging and patient information are being managed using digital data during acquisition, transmission, storage, display, interpretation, and consultation. The management of data during each of these operations may have an impact on the quality of patient care. These articles describe what is known to improve image quality for digital and computed radiography and to make recommendations on optimal acquisition, processing, and display. The practice of digital radiography is a rapidly evolving technology that will require timely revision of any guidelines and standards.


    Directory of Open Access Journals (Sweden)

    N. M. S. M. Kadhim


    Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates

  19. Mass Processing of Sentinel-1 Images for Maritime Surveillance

    Directory of Open Access Journals (Sweden)

    Carlos Santamaria


    Full Text Available The free, full and open data policy of the EU’s Copernicus programme has vastly increased the amount of remotely sensed data available to both operational and research activities. However, this huge amount of data calls for new ways of accessing and processing such “big data”. This paper focuses on the use of Copernicus’s Sentinel-1 radar satellite for maritime surveillance. It presents a study in which ship positions have been automatically extracted from more than 11,500 Sentinel-1A images collected over the Mediterranean Sea, and compared with ship position reports from the Automatic Identification System (AIS. These images account for almost all the Sentinel-1A acquisitions taken over the area during the two-year period from the start of the operational phase in October 2014 until September 2016. A number of tools and platforms developed at the European Commission’s Joint Research Centre (JRC that have been used in the study are described in the paper. They are: (1 Search for Unidentified Maritime Objects (SUMO, a tool for ship detection in Synthetic Aperture Radar (SAR images; (2 the JRC Earth Observation Data and Processing Platform (JEODPP, a platform for efficient storage and processing of large amounts of satellite images; and (3 Blue Hub, a maritime surveillance GIS and data fusion platform. The paper presents the methodology and results of the study, giving insights into the new maritime surveillance knowledge that can be gained by analysing such a large dataset, and the lessons learnt in terms of handling and processing the big dataset.

  20. Thermal precursors in satellite images of the 1999 eruption of Shishaldin Volcano (United States)

    Dehn, Jonathan; Dean, Kenneson; Engle, Kevin; Izbekov, Pavel


    Shishaldin Volcano, Unimak Island Alaska, began showing signs of thermal unrest in satellite images on 9 February 1999. A thermal anomaly and small steam plume were detected at the summit of the volcano in short-wave thermal infrared AVHRR (advanced very high resolution radiometer) satellite data. This was followed by over 2 months of changes in the observed thermal character of the volcano. Initially, the thermal anomaly was only visible when the satellite passed nearly directly over the volcano, suggesting a hot source deep in the central crater obscured from more oblique satellite passes. The "zenith angle" needed to see the anomaly increased with time, presumably as the thermal source rose within the conduit. Based on this change, an ascent rate of ca. 14 m per day for the thermal source was estimated, until it reached the summit on around 21 March. It is thought that Strombolian activity began around this time. The precursory activity culminated in a sub-Plinian eruption on 19 April, ejecting ash to over 45,000 ft. (13,700 m). The thermal energy output through the precursory period was calculated based on geometric constraints unique to Shishaldin. These calculations show fluctuations that can be tied to changes in the eruptive character inferred from seismic records and later geologic studies. The remote location of this volcano made satellite images a necessary observation tool for this eruption. To date, this is the longest thermal precursory activity preceding a sub-Plinian eruption recorded by satellite images in the region. This type of thermal monitoring of remote volcanoes is central in the efforts of the Alaska Volcano Observatory to provide timely warnings of volcanic eruption, and mitigate their associated hazards to air-traffic and local residents.

  1. Satellite and terrestrial radio positioning techniques a signal processing perspective

    CERN Document Server

    Dardari, Davide; Falletti, Emanuela


    * The first book to combine satellite and terrestrial positioning techniques - vital for the understanding and development of new technologies * Written and edited by leading experts in the field, with contributors belonging to the European Commission's FP7 Network of Excellence NEWCOM++ Applications to a wide range of fields, including sensor networks, emergency services, military use, location-based billing, location-based advertising, intelligent transportation, and leisure Location-aware personal devices and location-based services have become ever more prominent in the past few years

  2. Hammerhead-mediated processing of satellite pDo500 family transcripts from Dolichopoda cave crickets. (United States)

    Rojas, A A; Vazquez-Tello, A; Ferbeyre, G; Venanzetti, F; Bachmann, L; Paquin, B; Sbordoni, V; Cedergren, R


    This work reports the discovery and functional characterization of catalytically active hammerhead motifs within satellite DNA of the pDo500 family from several DOLICHOPODA: cave cricket species. We show that in vitro transcribed RNA of some members of this satellite DNA family do self-cleave in vitro. This self-cleavage activity is correlated with the efficient in vivo processing of long primary transcripts into monomer-sized RNA. The high sequence conservation of the satellite pDo500 DNA family among genetically isolated DOLICHOPODA: schiavazzii populations, as well as other DOLICHOPODA: species, along with the fact that satellite members are actively transcribed in vivo suggests that the hammerhead-encoding satellite transcripts are under selective pressure, perhaps because they fulfil an important physiological role or function. Remarkably, this is the third example of hammerhead ribozyme structures associated with transcribed repetitive DNA sequences from animals. The possibility that such an association may not be purely coincidental is discussed.

  3. Image processing for cameras with fiber bundle image relay. (United States)

    Olivas, Stephen J; Arianpour, Ashkan; Stamenov, Igor; Morrison, Rick; Stack, Ron A; Johnson, Adam R; Agurok, Ilya P; Ford, Joseph E


    Some high-performance imaging systems generate a curved focal surface and so are incompatible with focal plane arrays fabricated by conventional silicon processing. One example is a monocentric lens, which forms a wide field-of-view high-resolution spherical image with a radius equal to the focal length. Optical fiber bundles have been used to couple between this focal surface and planar image sensors. However, such fiber-coupled imaging systems suffer from artifacts due to image sampling and incoherent light transfer by the fiber bundle as well as resampling by the focal plane, resulting in a fixed obscuration pattern. Here, we describe digital image processing techniques to improve image quality in a compact 126° field-of-view, 30 megapixel panoramic imager, where a 12 mm focal length F/1.35 lens made of concentric glass surfaces forms a spherical image surface, which is fiber-coupled to six discrete CMOS focal planes. We characterize the locally space-variant system impulse response at various stages: monocentric lens image formation onto the 2.5 μm pitch fiber bundle, image transfer by the fiber bundle, and sensing by a 1.75 μm pitch backside illuminated color focal plane. We demonstrate methods to mitigate moiré artifacts and local obscuration, correct for sphere to plane mapping distortion and vignetting, and stitch together the image data from discrete sensors into a single panorama. We compare processed images from the prototype to those taken with a 10× larger commercial camera with comparable field-of-view and light collection.

  4. A dynamic and generic cloud computing model for glaciological image processing (United States)

    Ranisavljević, Élisabeth; Devin, Florent; Laffly, Dominique; Le Nir, Yannick


    As satellite imaging is quite expensive, and because of poor weather conditions including common heavy cloud cover at polar latitudes, daily satellite imaging is not always accessible or suitable to observe fast temporal evolutions. We complement satellite imagery with a set of ground based autonomous automated digital cameras which take three pictures a day. With these pictures we build a mosaic with their projection and apply a classification to define the temporal evolution of the snow cover. As the pictures are subject to heavy disturbance, some processing is needed to build the mosaic. Once the processes are defined, we present our model. This model is built upon a cloud computing environment using Web services workflow. Then we present how the processes are dynamically organized using a scheduler. This scheduler chooses the order and the processes to apply to every picture to build the mosaic. Once we obtain a mosaic we can study the variation of the snow cover.

  5. Cellular automata in image processing and geometry

    CERN Document Server

    Adamatzky, Andrew; Sun, Xianfang


    The book presents findings, views and ideas on what exact problems of image processing, pattern recognition and generation can be efficiently solved by cellular automata architectures. This volume provides a convenient collection in this area, in which publications are otherwise widely scattered throughout the literature. The topics covered include image compression and resizing; skeletonization, erosion and dilation; convex hull computation, edge detection and segmentation; forgery detection and content based retrieval; and pattern generation. The book advances the theory of image processing, pattern recognition and generation as well as the design of efficient algorithms and hardware for parallel image processing and analysis. It is aimed at computer scientists, software programmers, electronic engineers, mathematicians and physicists, and at everyone who studies or develops cellular automaton algorithms and tools for image processing and analysis, or develops novel architectures and implementations of mass...

  6. Modifications of the heliostat procedures for irradiance estimates from satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, H.G.; Costanzo, Claudio; Heinemann, Detlev [Oldenburg Univ. (Germany). Fachbereich 8 - Physik


    Images taken by geostationary satellites may be used to estimate solar irradiance fluxes at the earth`s surface. The Heliostat method is a widely applied procedure for this task. It is based on the empirical correlation between a satellite derived cloud index and the irradiance at the ground. Modifications to this procedure that may reduce the temporal variability of the correlation are presented. The modified method may open the way to the use of a generic relation of cloud index and global irradiance. (author)

  7. Surface rupture and slip distribution of the 2016 Mw7.8 Kaikoura earthquake (New Zealand) from optical satellite image correlation using MicMac (United States)

    Champenois, Johann; Klinger, Yann; Grandin, Raphaël; Satriano, Claudio; Baize, Stéphane; Delorme, Arthur; Scotti, Oona


    Remote sensing techniques, like optical satellite image correlation, are very efficient methods to localize and quantify surface displacements due to earthquakes. In this study, we use the french sub-pixel correlator MicMac (Multi Images Correspondances par Méthodes Automatiques de Corrélation). This free open-source software, developed by IGN, was recently adapted to process satellite images. This correlator uses regularization, and that provides good results especially in near-fault area with a high spatial resolution. We use co-seismic pair of ortho-images to measure the horizontal displacement field during the recent 2016 Mw7.8 Kaikoura earthquake. Optical satellite images from different satellites are processed (Sentinel-2A, Landsat8, etc.) to present a dense map of the surface ruptures and to analyze high density slip distribution along all major ruptures. We also provide a detail pattern of deformation along these main surface ruptures. Moreover, 2D displacement from optical correlation is compared to co-seismic measurements from GPS, static displacement from accelerometric records, geodetic marks and field investigations. Last but not least, we investigate the reconstruction of 3D displacement from combining InSAR, GPS and optic.

  8. An Investigation on Water Quality of Darlik Dam Drinking Water using Satellite Images

    Directory of Open Access Journals (Sweden)

    Erhan Alparslan


    Full Text Available Darlik Dam supplies 15% of the water demand of Istanbul Metropolitan City of Turkey. Water quality (WQ in the Darlik Dam was investigated from Landsat 5 TM satellite images of the years 2004, 2005, and 2006 in order to determine land use/land cover changes in the watershed of the dam that may deteriorate its WQ. The images were geometrically and atmospherically corrected for WQ analysis. Next, an investigation was made by multiple regression analysis between the unitless planetary reflectance values of the first four bands of the June 2005 Landsat TM image of the dam and WQ parameters, such as chlorophyll-a, total dissolved matter, turbidity, total phosphorous, and total nitrogen, measured at satellite image acquisition time at seven stations in the dam. Finally, WQ in the dam was studied from satellite images of the years 2004, 2005, and 2006 by pattern recognition techniques in order to determine possible water pollution in the dam. This study was compared to a previous study done by the authors in the Küçükçekmece water reservoir, also in Istanbul City.

  9. Improving Sediment Transport Prediction by Assimilating Satellite Images in a Tidal Bay Model of Hong Kong

    Directory of Open Access Journals (Sweden)

    Peng Zhang


    Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.


    Directory of Open Access Journals (Sweden)

    Kupidura Przemysław


    Full Text Available The article is focused on the analysis of possibilities of using granulometric analysis methods: the morphological profile, and granulometric maps in detecting buildings on satellite images. It briefly explains the theoretical basis for granulometric analysis of image and compares two methods used in research. Tests were carried out on a fragment of QuickBird satellite scene – pansharpened multispectral image. 8 variants of classification differing in terms of the data and the model of classification were compared. Evaluation of the effectiveness of the different options for classification based on the analysis factor kappa values and omission and commission errors. The results indicate the significant potential of the proposed methods, and analysis of the observed imperfections allows to specify the possible fields of their development

  11. On some applications of diffusion processes for image processing

    Energy Technology Data Exchange (ETDEWEB)

    Morfu, S., E-mail: smorfu@u-bourgogne.f [Laboratoire d' Electronique, Informatique et Image (LE2i), UMR Cnrs 5158, Aile des Sciences de l' Ingenieur, BP 47870, 21078 Dijon Cedex (France)


    We propose a new algorithm inspired by the properties of diffusion processes for image filtering. We show that purely nonlinear diffusion processes ruled by Fisher equation allows contrast enhancement and noise filtering, but involves a blurry image. By contrast, anisotropic diffusion, described by Perona and Malik algorithm, allows noise filtering and preserves the edges. We show that combining the properties of anisotropic diffusion with those of nonlinear diffusion provides a better processing tool which enables noise filtering, contrast enhancement and edge preserving.

  12. XSTREAM: A Highly Efficient High Speed Real-time Satellite Data Acquisition and Processing System using Heterogeneous Computing (United States)

    Pramod Kumar, K.; Mahendra, P.; Ramakrishna rReddy, V.; Tirupathi, T.; Akilan, A.; Usha Devi, R.; Anuradha, R.; Ravi, N.; Solanki, S. S.; Achary, K. K.; Satish, A. L.; Anshu, C.


    In the last decade, the remote sensing community has observed a significant growth in number of satellites, sensors and their resolutions, thereby increasing the volume of data to be processed each day. Satellite data processing is a complex and time consuming activity. It consists of various tasks, such as decode, decrypt, decompress, radiometric normalization, stagger corrections, ephemeris data processing for geometric corrections etc., and finally writing of the product in the form of an image file. Each task in the processing chain is sequential in nature and has different computing needs. Conventionally the processes are cascaded in a well organized workflow to produce the data products, which are executed on general purpose high-end servers / workstations in an offline mode. Hence, these systems are considered to be ineffective for real-time applications that require quick response and just-intime decision making such as disaster management, home land security and so on. This paper discusses anovel approach to processthe data online (as the data is being acquired) using a heterogeneous computing platform namely XSTREAM which has COTS hardware of CPUs, GPUs and FPGA. This paper focuses on the process architecture, re-engineering aspects and mapping of tasks to the right computing devicewithin the XSTREAM system, which makes it an ideal cost-effective platform for acquiring, processing satellite payload data in real-time and displaying the products in original resolution for quick response. The system has been tested for IRS CARTOSAT and RESOURCESAT series of satellites which have maximum data downlink speed of 210 Mbps.

  13. Modeling Research on Joint Scheduling of Multiple Imaging Satellites with Multiple Sensors%多星多载荷联合调度问题建模研究

    Institute of Scientific and Technical Information of China (English)

    潘鞘剑; 周装轻; 贺仁杰; 邢立宁


    在对多星多载荷联合调度过程及约束条件分析的基础上,从约束建模及启发式调度规则设计的角度对多星多载联合调度方案生成中的关键问题进行了深入研究.建立了基于阶段优化的多星多载荷联合调度模型.提出了基于规则的发式构造算法.%Guided by the application requirements of imaging satellite, the model construction and heuristic rule design of multi imaging satellites joint scheduling problem are focused. All of the research are based on the a-nalysis of the process of joint scheduling and imaging constraints. Firstly, this thesis analyses satellite imaging procedure , imaging constraints, input and output of the problem, ascertains the basic scheduling flow and characteristics of the multi imaging satellites joint scheduling problem. Secondly, in order to solve the problem the construction of heuristic algorithms is focused on.

  14. Applications of Digital Image Processing 11 (United States)

    Cho, Y. -C.


    A new technique, digital image velocimetry, is proposed for the measurement of instantaneous velocity fields of time dependent flows. A time sequence of single-exposure images of seed particles are captured with a high-speed camera, and a finite number of the single-exposure images are sampled within a prescribed period in time. The sampled images are then digitized on an image processor, enhanced, and superimposed to construct an image which is equivalent to a multiple exposure image used in both laser speckle velocimetry and particle image velocimetry. The superimposed image and a single-exposure Image are digitally Fourier transformed for extraction of information on the velocity field. A great enhancement of the dynamic range of the velocity measurement is accomplished through the new technique by manipulating the Fourier transform of both the single-exposure image and the superimposed image. Also the direction of the velocity vector is unequivocally determined. With the use of a high-speed video camera, the whole process from image acquisition to velocity determination can be carried out electronically; thus this technique can be developed into a real-time capability.

  15. Process perspective on image quality evaluation (United States)

    Leisti, Tuomas; Halonen, Raisa; Kokkonen, Anna; Weckman, Hanna; Mettänen, Marja; Lensu, Lasse; Ritala, Risto; Oittinen, Pirkko; Nyman, Göte


    The psychological complexity of multivariate image quality evaluation makes it difficult to develop general image quality metrics. Quality evaluation includes several mental processes and ignoring these processes and the use of a few test images can lead to biased results. By using a qualitative/quantitative (Interpretation Based Quality, IBQ) methodology, we examined the process of pair-wise comparison in a setting, where the quality of the images printed by laser printer on different paper grades was evaluated. Test image consisted of a picture of a table covered with several objects. Three other images were also used, photographs of a woman, cityscape and countryside. In addition to the pair-wise comparisons, observers (N=10) were interviewed about the subjective quality attributes they used in making their quality decisions. An examination of the individual pair-wise comparisons revealed serious inconsistencies in observers' evaluations on the test image content, but not on other contexts. The qualitative analysis showed that this inconsistency was due to the observers' focus of attention. The lack of easily recognizable context in the test image may have contributed to this inconsistency. To obtain reliable knowledge of the effect of image context or attention on subjective image quality, a qualitative methodology is needed.

  16. 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


    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...

  17. Applying Support Vector Machine in classifying satellite images for the assessment of urban sprawl (United States)

    murgante, Beniamino; Nolè, Gabriele; Lasaponara, Rosa; Lanorte, Antonio; Calamita, Giuseppe


    In last decades the spreading of new buildings, road infrastructures and a scattered proliferation of houses in zones outside urban areas, produced a countryside urbanization with no rules, consuming soils and impoverishing the landscape. Such a phenomenon generated a huge environmental impact, diseconomies and a decrease in life quality. This study analyzes processes concerning land use change, paying particular attention to urban sprawl phenomenon. The application is based on the integration of Geographic Information Systems and Remote Sensing adopting open source technologies. The objective is to understand size distribution and dynamic expansion of urban areas in order to define a methodology useful to both identify and monitor the phenomenon. In order to classify "urban" pixels, over time monitoring of settlements spread, understanding trends of artificial territories, classifications of satellite images at different dates have been realized. In order to obtain these classifications, supervised classification algorithms have been adopted. More particularly, Support Vector Machine (SVM) learning algorithm has been applied to multispectral remote data. One of the more interesting features in SVM is the possibility to obtain good results also adopting few classification pixels of training areas. SVM has several interesting features, such as the capacity to obtain good results also adopting few classification pixels of training areas, a high possibility of configuration parameters and the ability to discriminate pixels with similar spectral responses. Multi-temporal ASTER satellite data at medium resolution have been adopted because are very suitable in evaluating such phenomena. The application is based on the integration of Geographic Information Systems and Remote Sensing technologies by means of open source software. Tools adopted in managing and processing data are GRASS GIS, Quantum GIS and R statistical project. The area of interest is located south of Bari

  18. Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD. (United States)

    Bhandari, A K; Soni, V; Kumar, A; Singh, G K


    This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Design for embedded image processing on FPGAs

    CERN Document Server

    Bailey, Donald G


    "Introductory material will consider the problem of embedded image processing, and how some of the issues may be solved using parallel hardware solutions. Field programmable gate arrays (FPGAs) are introduced as a technology that provides flexible, fine-grained hardware that can readily exploit parallelism within many image processing algorithms. A brief review of FPGA programming languages provides the link between a software mindset normally associated with image processing algorithms, and the hardware mindset required for efficient utilization of a parallel hardware design. The bulk of the book will focus on the design process, and in particular how designing an FPGA implementation differs from a conventional software implementation. Particular attention is given to the techniques for mapping an algorithm onto an FPGA implementation, considering timing, memory bandwidth and resource constraints, and efficient hardware computational techniques. Extensive coverage will be given of a range of image processing...

  20. Imaging process and VIP engagement

    Directory of Open Access Journals (Sweden)

    Starčević Slađana


    Full Text Available It's often quoted that celebrity endorsement advertising has been recognized as "an ubiquitous feature of the modern marketing". The researches have shown that this kind of engagement has been producing significantly more favorable reactions of consumers, that is, a higher level of an attention for the advertising messages, a better recall of the message and a brand name, more favorable evaluation and purchasing intentions of the brand, in regard to engagement of the non-celebrity endorsers. A positive influence on a firm's profitability and prices of stocks has also been shown. Therefore marketers leaded by the belief that celebrities represent the effective ambassadors in building of positive brand image or company image and influence an improvement of the competitive position, invest enormous amounts of money for signing the contracts with them. However, this strategy doesn't guarantee success in any case, because it's necessary to take into account many factors. This paper summarizes the results of previous researches in this field and also the recommendations for a more effective use of this kind of advertising.

  1. Crack Length Detection by Digital Image Processing

    DEFF Research Database (Denmark)

    Lyngbye, Janus; Brincker, Rune


    It is described how digital image processing is used for measuring the length of fatigue cracks. The system is installed in a Personal Computer equipped with image processing hardware and performs automated measuring on plane metal specimens used in fatigue testing. Normally one can not achieve...... a resolution better then that of the image processing equipment. To overcome this problem an extrapolation technique is used resulting in a better resolution. The system was tested on a specimen loaded with different loads. The error σa was less than 0.031 mm, which is of the same size as human measuring...

  2. Crack Detection by Digital Image Processing

    DEFF Research Database (Denmark)

    Lyngbye, Janus; Brincker, Rune

    It is described how digital image processing is used for measuring the length of fatigue cracks. The system is installed in a Personal, Computer equipped with image processing hardware and performs automated measuring on plane metal specimens used in fatigue testing. Normally one can not achieve...... a resolution better than that of the image processing equipment. To overcome this problem an extrapolation technique is used resulting in a better resolution. The system was tested on a specimen loaded with different loads. The error σa was less than 0.031 mm, which is of the same size as human measuring...

  3. Algorithms for image processing and computer vision

    CERN Document Server

    Parker, J R


    A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It's an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists wh

  4. SENTINEL-2 image quality and level 1 processing (United States)

    Meygret, Aimé; Baillarin, Simon; Gascon, Ferran; Hillairet, Emmanuel; Dechoz, Cécile; Lacherade, Sophie; Martimort, Philippe; Spoto, François; Henry, Patrice; Duca, Riccardo


    In the framework of the Global Monitoring for Environment and Security (GMES) programme, the European Space Agency (ESA) in partnership with the European Commission (EC) is developing the SENTINEL-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a twin satellites configuration deployed in polar sun-synchronous orbit and is designed to offer a unique combination of systematic global coverage with a wide field of view (290km), a high revisit (5 days at equator with two satellites), a high spatial resolution (10m, 20m and 60 m) and multi-spectral imagery (13 bands in the visible and the short wave infrared spectrum). SENTINEL-2 will ensure data continuity of SPOT and LANDSAT multispectral sensors while accounting for future service evolution. This paper presents the main geometric and radiometric image quality requirements for the mission. The strong multi-spectral and multi-temporal registration requirements constrain the stability of the platform and the ground processing which will automatically refine the geometric physical model through correlation technics. The geolocation of the images will take benefits from a worldwide reference data set made of SENTINEL-2 data strips geolocated through a global space-triangulation. These processing are detailed through the description of the level 1C production which will provide users with ortho-images of Top of Atmosphere reflectances. The huge amount of data (1.4 Tbits per orbit) is also a challenge for the ground processing which will produce at level 1C all the acquired data. Finally we discuss the different geometric (line of sight, focal plane cartography, ...) and radiometric (relative and absolute camera sensitivity) in-flight calibration methods that will take advantage of the on-board sun diffuser and ground targets to answer the severe mission requirements.

  5. Lung Cancer Detection Using Image Processing Techniques

    Directory of Open Access Journals (Sweden)

    Mokhled S. AL-TARAWNEH


    Full Text Available Recently, image processing techniques are widely used in several medical areas for image improvement in earlier detection and treatment stages, where the time factor is very important to discover the abnormality issues in target images, especially in various cancer tumours such as lung cancer, breast cancer, etc. Image quality and accuracy is the core factors of this research, image quality assessment as well as improvement are depending on the enhancement stage where low pre-processing techniques is used based on Gabor filter within Gaussian rules. Following the segmentation principles, an enhanced region of the object of interest that is used as a basic foundation of feature extraction is obtained. Relying on general features, a normality comparison is made. In this research, the main detected features for accurate images comparison are pixels percentage and mask-labelling.

  6. Signal and image processing in medical applications

    CERN Document Server

    Kumar, Amit; Rahim, B Abdul; Kumar, D Sravan


    This book highlights recent findings on and analyses conducted on signals and images in the area of medicine. The experimental investigations involve a variety of signals and images and their methodologies range from very basic to sophisticated methods. The book explains how signal and image processing methods can be used to detect and forecast abnormalities in an easy-to-follow manner, offering a valuable resource for researchers, engineers, physicians and bioinformatics researchers alike.

  7. Energy preserving QMF for image processing. (United States)

    Lian, Jian-ao; Wang, Yonghui


    Implementation of new biorthogonal filter banks (BFB) for image compression and denoising is performed, using test images with diversified characteristics. These new BFB’s are linear-phase, have odd lengths, and with a critical feature, namely, the filters preserve signal energy very well. Experimental results show that the proposed filter banks demonstrate promising performance improvement over the filter banks of those widely used in the image processing area, such as the CDF 9/7.

  8. Optical imaging process based on two-dimensional Fourier transform for synthetic aperture imaging ladar (United States)

    Sun, Zhiwei; Zhi, Ya'nan; Liu, Liren; Sun, Jianfeng; Zhou, Yu; Hou, Peipei


    The synthetic aperture imaging ladar (SAIL) systems typically generate large amounts of data difficult to compress with digital method. This paper presents an optical SAIL processor based on compensation of quadratic phase of echo in azimuth direction and two dimensional Fourier transform. The optical processor mainly consists of one phase-only liquid crystal spatial modulator(LCSLM) to load the phase data of target echo and one cylindrical lens to compensate the quadratic phase and one spherical lens to fulfill the task of two dimensional Fourier transform. We show the imaging processing result of practical target echo obtained by a synthetic aperture imaging ladar demonstrator. The optical processor is compact and lightweight and could provide inherent parallel and the speed-of-light computing capability, it has a promising application future especially in onboard and satellite borne SAIL systems.

  9. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images (United States)

    Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.


    Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

  10. Direct Geolocation of Satellite Images with the EO-CFI Libraries (United States)

    de Miguel, Eduardo; Prado, Elena; Estebanez, Monica; Martin, Ana I.; Gonzalez, Malena


    The INTA Remote Sensing Laboratory has implemented a tool for the direct geolocation of satellite images. The core of the tool is a C code based on the "Earth Observation Mission CFI SW" from ESA. The tool accepts different types of inputs for satellite attitude (euler angles, quaternions, default attitude models). Satellite position can be provided either in ECEF or ECI coordinates. The line of sight of each individual detector is imported from an external file or is generated by the tool from camera parameters. Global DEM ACE2 is used to define ground intersection of the LOS.The tool has been already tailored for georeferencing images from the forthcoming Spanish Earth Observation mission SEOSat/Ingenio, and for the camera APIS onboard the INTA cubesat OPTOS. The next step is to configure it for the geolocation of Sentinel 2 L1b images.The tool has been internally validated by different means. This validation shows that the tool is suitable for georeferencing images from high spatial resolution missions. As part of the validation efforts, a code for simulating orbital info for LEO missions using EO-CFI has been produced.

  11. Image processing and computing in structural biology

    NARCIS (Netherlands)

    Jiang, Linhua


    With the help of modern techniques of imaging processing and computing, image data obtained by electron cryo-microscopy of biomolecules can be reconstructed to three-dimensional biological models at sub-nanometer resolution. These models allow answering urgent problems in life science, for instance,

  12. Digital Image Processing in Private Industry. (United States)

    Moore, Connie


    Examines various types of private industry optical disk installations in terms of business requirements for digital image systems in five areas: records management; transaction processing; engineering/manufacturing; information distribution; and office automation. Approaches for implementing image systems are addressed as well as key success…

  13. Coastal water quality estimation from Geostationary Ocean Color Imager (GOCI) satellite data using machine learning approaches (United States)

    Im, Jungho; Ha, Sunghyun; Kim, Yong Hoon; Ha, Hokyung; Choi, Jongkuk; Kim, Miae


    It is important to monitor coastal water quality using key parameters such as chlorophyll-a concentration and suspended sediment to better manage coastal areas as well as to better understand the nature of biophysical processes in coastal seawater. Remote sensing technology has been commonly used to monitor coastal water quality due to its ability of covering vast areas at high temporal resolution. While it is relatively straightforward to estimate water quality in open ocean (i.e., Case I water) using remote sensing, coastal water quality estimation is still challenging as many factors can influence water quality, including various materials coming from inland water systems and tidal circulation. There are continued efforts to accurately estimate water quality parameters in coastal seawater from remote sensing data in a timely manner. In this study, two major water quality indicators, chlorophyll-a concentration and the amount of suspended sediment, were estimated using Geostationary Ocean Color Imager (GOCI) satellite data. GOCI, launched in June 2010, is the first geostationary ocean color observation satellite in the world. GOCI collects data hourly for 8 hours a day at 6 visible and 2 near-infrared bands at a 500 m resolution with 2,500 x 2,500 km square around Korean peninsula. Along with conventional statistical methods (i.e., various linear and non-linear regression), three machine learning approaches such as random forest, Cubist, and support vector regression were evaluated for coastal water quality estimation. In situ measurements (63 samples; including location, two water quality parameters, and the spectra of surface water using a hand-held spectroradiometer) collected during four days between 2011 and 2012 were used as reference data. Due to the small sample size, leave-one-out cross validation was used to assess the performance of the water quality estimation models. Atmospherically corrected radiance data and selected band-ratioed images were used

  14. Checking Fits With Digital Image Processing (United States)

    Davis, R. M.; Geaslen, W. D.


    Computer-aided video inspection of mechanical and electrical connectors feasible. Report discusses work done on digital image processing for computer-aided interface verification (CAIV). Two kinds of components examined: mechanical mating flange and electrical plug.

  15. Contrail frequency over Europe from NOAA-satellite images

    Directory of Open Access Journals (Sweden)

    V. Gayler

    Full Text Available Contrail cloudiness over Europe and the eastern part of the North Atlantic Ocean was analyzed for the two periods September 1979 - December 1981 and September 1989 - August 1992 by visual inspection of quicklook photographic prints of NOAA/AVHRR infrared images. The averaged contrail cover exhibits maximum values along the transatlantic flight corridor around 50 °N (of almost 2% and over western Europe resulting in 0.5% contrail cloudiness on average. A strong yearly cycle appears with a maximum (<2% in spring and summer over the Atlantic and a smaller maximum (<1% in winter over southwestern Europe. Comparing the two time periods, which are separated by one decade, shows there is a significant decrease in contrail cloudiness over western Europe and a significant increase over the North Atlantic between March and July. Contrail cloud cover during daytime is about twice as high as during nighttime. Contrails are found preferentially in larger fields of 1000 km diameter which usually last for more than a day. Causes, possible errors and consequences are discussed.

  16. Contrail frequency over Europe from NOAA-satellite images (United States)

    Bakan, S.; Betancor, M.; Gayler, V.; Graßl, H.


    Contrail cloudiness over Europe and the eastern part of the North Atlantic Ocean was analyzed for the two periods September 1979 - December 1981 and September 1989 - August 1992 by visual inspection of quicklook photographic prints of NOAA/AVHRR infrared images. The averaged contrail cover exhibits maximum values along the transatlantic flight corridor around 50 °N (of almost 2%) and over western Europe resulting in 0.5% contrail cloudiness on average. A strong yearly cycle appears with a maximum (<2%) in spring and summer over the Atlantic and a smaller maximum (<1%) in winter over southwestern Europe. Comparing the two time periods, which are separated by one decade, shows there is a significant decrease in contrail cloudiness over western Europe and a significant increase over the North Atlantic between March and July. Contrail cloud cover during daytime is about twice as high as during nighttime. Contrails are found preferentially in larger fields of 1000 km diameter which usually last for more than a day. Causes, possible errors and consequences are discussed.

  17. Currency Recognition System Using Image Processing

    Directory of Open Access Journals (Sweden)

    S. M. Saifullah


    Full Text Available In the last few years a great technological advances in color printing, duplicating and scanning, counterfeiting problems have become more serious. In past only authorized printing house has the ability to make currency paper, but now a days it is possible for anyone to print fake bank note with the help of modern technology such as computer, laser printer. Fake notes are burning questions in almost every country. Like others country Bangladesh has also hit really heard and has become a very acute problem. Therefore there is a need to design a currency recognition system that can easily make a difference between real and fake banknote and the process will time consuming. Our system describes an approach for verification of Bangladeshi currency banknotes. The currency will be verified by using image processing techniques. The approach consists of a number of components including image processing, image segmentation, feature extraction, comparing images. The system is designed by MATLAB. Image processing involves changing the nature of an image in order to improve its pictorial information for human interpretation. The image processing software is a collection of functions that extends the capability of the MATLAB numeric computing environment. The result will be whether currency is real or fake.

  18. Recent developments in digital image processing at the Image Processing Laboratory of JPL. (United States)

    O'Handley, D. A.


    Review of some of the computer-aided digital image processing techniques recently developed. Special attention is given to mapping and mosaicking techniques and to preliminary developments in range determination from stereo image pairs. The discussed image processing utilization areas include space, biomedical, and robotic applications.

  19. The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce (United States)

    Chen, Xi; Zhou, Liqing


    With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

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

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.J.


    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.

  1. Bottom Topographic Changes of Poyang Lake During Past Decade Using Multi-temporal Satellite Images (United States)

    Zhang, S.


    Poyang Lake, as a well-known international wetland in the Ramsar Convention List, is the largest freshwater lake in China. It plays crucial ecological role in flood storage and biological diversity. Poyang Lake is facing increasingly serious water crises, including seasonal dry-up, decreased wetland area, and water resource shortage, all of which are closely related to progressive bottom topographic changes over recent years. Time-series of bottom topography would contribute to our understanding of the lake's evolution during the past several decades. However, commonly used methods for mapping bottom topography fail to frequently update quality bathymetric data for Poyang Lake restricted by weather and accessibility. These deficiencies have limited our ability to characterize the bottom topographic changes and understanding lake erosion or deposition trend. To fill the gap, we construct a decadal bottom topography of Poyang Lake with a total of 146 time series medium resolution satellite images based on the Waterline Method. It was found that Poyang Lake has eroded with a rate of -14.4 cm/ yr from 2000 to 2010. The erosion trend was attributed to the impacts of human activities, especially the operation of the Three Gorge Dams, sand excavation, and the implementation of water conservancy project. A decadal quantitative understanding bottom topography of Poyang Lake might provide a foundation to model the lake evolutionary processes and assist both researchers and local policymakers in ecological management, wetland protection and lake navigation safety.

  2. Extraction of subjective properties in image processing



    Most of the present digital images processing methods are related with objective characterization of external properties as shape, form or colour. This information concerns objective characteristics of different bodies and is applied to extract details to perform several different tasks. But in some occasions, some other type of information is needed. This is the case when the image processing system is going to be applied to some operation related with living bodies. In this case, some other...

  3. Fragmentation measurement using image processing

    Directory of Open Access Journals (Sweden)

    Farhang Sereshki


    Full Text Available In this research, first of all, the existing problems in fragmentation measurement are reviewed for the sake of its fast and reliable evaluation. Then, the available methods used for evaluation of blast results are mentioned. The produced errors especially in recognizing the rock fragments in computer-aided methods, and also, the importance of determination of their sizes in the image analysis methods are described. After reviewing the previous work done, an algorithm is proposed for the automated determination of rock particles’ boundary in the Matlab software. This method can determinate automatically the particles boundary in the minimum time. The results of proposed method are compared with those of Split Desktop and GoldSize software in two automated and manual states. Comparing the curves extracted from different methods reveals that the proposed approach is accurately applicable in measuring the size distribution of laboratory samples, while the manual determination of boundaries in the conventional software is very time-consuming, and the results of automated netting of fragments are very different with the real value due to the error in separation of the objects.

  4. Fuzzy Analytic Hierarchy Process for Risk Assessment to General-assembling of Satellite

    Directory of Open Access Journals (Sweden)

    J. Tian


    Full Text Available With a fuzzy analytic hierarchy process, the hierarchy of risk factors in satellite general-assembling process is established, based on which, the weights of various risk factors are determined one by one. Furthermore, the risk factors are quantitatively analyzed, and the comprehensive risk assessment model is established in the end. Taking a satellite model as an example, the risks in the satellite general-assembling process are assessed comprehensively, and the risk levels are quantitatively measured. The factors are sorted according to their impact capabilities to the overall risk level, and the key points of risk control for satellite general-assembling process is clarified. Results obtained from the analysis to risk sub-factors suggested that experience and techniques, narrow space and production rhythm are more detrimental to process risk than any other sub-factors. The results also show that the risk could be mitigated, provided that the effectiveness of engineering measures against deficiencies in the most influential (sub-factors is maintained. The rationality and feasibility of the proposed method model is proved by the engineering application, which provide the effective technical support for the risk control in satellite general-assembling process.

  5. GNSS Carrier Phase Integer Ambiguity Resolution with Camera and Satellite images (United States)

    Henkel, Patrick


    Ambiguity Resolution is the key to high precision position and attitude determination with GNSS. However, ambiguity resolution of kinematic receivers becomes challenging in environments with substantial multipath, limited satellite availability and erroneous cycle slip corrections. There is a need for other sensors, e.g. inertial sensors that allow an independent prediction of the position. The change of the predicted position over time can then be used for cycle slip detection and correction. In this paper, we provide a method to improve the initial ambiguity resolution for RTK and PPP with vision-based position information. Camera images are correlated with geo-referenced aerial/ satellite images to obtain an independent absolute position information. This absolute position information is then coupled with the GNSS and INS measurements in an extended Kalman filter to estimate the position, velocity, acceleration, attitude, angular rates, code multipath and biases of the accelerometers and gyroscopes. The camera and satellite images are matched based on some characteristic image points (e.g. corners of street markers). We extract these characteristic image points from the camera images by performing the following steps: An inverse mapping (homogenous projection) is applied to transform the camera images from the driver's perspective to bird view. Subsequently, we detect the street markers by performing (a) a color transformation and reduction with adaptive brightness correction to focus on relevant features, (b) a subsequent morphological operation to enhance the structure recognition, (c) an edge and corner detection to extract feature points, and (d) a point matching of the corner points with a template to recognize the street markers. We verified the proposed method with two low-cost u-blox LEA 6T GPS receivers, the MPU9150 from Invensense, the ASCOS RTK corrections and a PointGrey camera. The results show very precise and seamless position and attitude

  6. Fusion between Satellite and Geophysical images in the study of Archaeological Sites (United States)

    Karamitrou, A. A.; Tsokas, G. N.; Petrou, M.; Maggidis, C.


    In this work various image fusion techniques are used between one satellite (Quickbird) and one geophysical (electric resistivity) image to create various combinations with higher information content than the two original images independently. The resultant images provide more information about possible buried archaeological relics. The examined archaeological area is located in mainland Greece near the city of Boetia at the acropolis of Gla. The acropolis was built on a flat-topped bedrock outcrop at the north-eastern edge of the Kopais basin. When Kopais was filled with water, Glas was emerging as an island. At the end of 14th century the two palaces of Thebes and Orchomenos jointly utilized a large scale engineering project in order to transform the Kopais basin into a fertile plain. They used the acropolis to monitor the project, and as a warehouse to storage the harvest. To examine the Acropolis for potential archaeological remnants we use one Quickbird satellite image that covers the surrounding area of Gla. The satellite image includes one panchromatic (8532x8528 pixels) and one multispectral (2133x2132 pixels) image, collected on 30th of August 2011, covering an area of 20 square kilometers. On the other hand, geophysical measurements were performed using the electric resistivity method to the south west part of the Acropolis. To combine these images we investigate mean-value fusion, wavelets fusion, and curvelet fusion. In the cases of wavelet and curvelet fusion we apply as the fusion criterion the maximum frequency rule. Furthermore, the two original images, and excavations near the area suggest that the dominant orientations of the buried features are north-south and east-west. Therefore, in curvelet fusion method, in curvelet domain we enhance the image details along these specific orientations, additionally to the fusion. The resultant fused images succeed to map linear and rectangular features that were not easily visible in the original images

  7. Methodology for the detection of land cover changes in time series of daily satellite images. Application to burned area detection

    Directory of Open Access Journals (Sweden)

    J.A. Moreno-Ruiz


    Full Text Available We have developed a methodology for detection of observable phenomena at pixel level over time series of daily satellite images, based on using a Bayesian classifier. This methodology has been applied successfully to detect burned areas in the North American boreal forests using the LTDR dataset. The LTDR dataset represents the longest time series of global daily satellite images with 0.05° (~5 km of spatial resolution. The proposed methodology has several stages: 1 pre-processing daily images to obtain composite images of n days; 2 building of space of statistical variables or attributes to consider; 3 designing an algorithm, by selecting and filtering the training cases; 4 obtaining probability maps related to the considered thematic classes; 5 post-processing to improve the results obtained by applying multiple techniques (filters, ranges, spatial coherence, etc.. The generated results are analyzed using accuracy metrics derived from the error matrix (commission and omission errors, percentage of estimation and using scattering plots against reference data (correlation coefficient and slope of the regression line. The quality of the results obtained improves, in terms of spatial and timing accuracy, to other burned area products that use images of higher spatial resolution (500 m and 1 km, but they are only available after year 2000 as MCD45A1 and BA GEOLAND-2: the total burned area estimation for the study region for the years 2001-2011 was 28.56 millions of ha according to reference data and 12.41, 138.43 and 19.41 millions of ha for the MCD45A1, BA GEOLAND-2 and BA-LTDR burned area products, respectively.

  8. Effects of rubber shock absorber on the flywheel micro vibration in the satellite imaging system (United States)

    Deng, Changcheng; Mu, Deqiang; Jia, Xuezhi; Li, Zongxuan


    When a satellite is in orbit, its flywheel will generate micro vibration and affect the imaging quality of the camera. In order to reduce this effect, a rubber shock absorber is used, and a numerical model and an experimental setup are developed to investigate its effect on the micro vibration in the study. An integrated model is developed for the system, and a ray tracing method is used in the modeling. The spot coordinates and displacements of the image plane are obtained, and the modulate transfer function (MTF) of the system is calculated. A satellite including a rubber shock absorber is designed, and the experiments are carried out. Both simulation and experiments results show that the MTF increases almost 10 %, suggesting the rubber shock absorber is useful to decrease the flywheel vibration.

  9. A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink

    Directory of Open Access Journals (Sweden)

    Salemi Eric


    Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.

  10. Soil salinity detection from satellite image analysis: an integrated approach of salinity indices and field data. (United States)

    Morshed, Md Manjur; Islam, Md Tazmul; Jamil, Raihan


    This paper attempts to detect soil salinity from satellite image analysis using remote sensing and geographic information system. Salinity intrusion is a common problem for the coastal regions of the world. Traditional salinity detection techniques by field survey and sampling are time-consuming and expensive. Remote sensing and geographic information system offer economic and efficient salinity detection, monitoring, and mapping. To predict soil salinity, an integrated approach of salinity indices and field data was used to develop a multiple regression equation. The correlations between different indices and field data of soil salinity were calculated to find out the highly correlated indices. The best regression model was selected considering the high R (2) value, low P value, and low Akaike's Information Criterion. About 20% variation was observed between the field data and predicted EC from the satellite image analysis. The precision of this salinity detection technique depends on the accuracy and uniform distribution of field data.

  11. Investigation of Interpolation for Solar Irradiation in Non-Observed Point Based on Satellite Images (United States)

    Shinoda, Yukio; Fujisawa, Sei; Seki, Tomomichi

    Penetrating the Photovoltaic Power Generation System (PV) on an enormous scale over a next decade has some crucial problems which affect on, for example, power grid stabilization and operation including existing power stations for electric power utilities. It would be therefore important for future operation to estimate power output generated by PV in advance. We focus on interpolation using observed solar irradiation (SI) and brightness of pixel on a satellite visible image for estimating SI even in non-observed point. Our results by single regression analysis between observed SI and brightness on a satellite image as cloudiness show that a shift of highest determination coefficient on each hour would represent solar movement and this higher determination coefficient would indicate a position which SI and cloud would cross. Finally assessment of error in this interpolation shows enough accuracy at least in daytime period, which is important for electricity utilities.

  12. Challenges in 3DTV image processing (United States)

    Redert, André; Berretty, Robert-Paul; Varekamp, Chris; van Geest, Bart; Bruijns, Jan; Braspenning, Ralph; Wei, Qingqing


    Philips provides autostereoscopic three-dimensional display systems that will bring the next leap in visual experience, adding true depth to video systems. We identified three challenges specifically for 3D image processing: 1) bandwidth and complexity of 3D images, 2) conversion of 2D to 3D content, and 3) object-based image/depth processing. We discuss these challenges and our solutions via several examples. In conclusion, the solutions have enabled the market introduction of several professional 3D products, and progress is made rapidly towards consumer 3DTV.

  13. Hexagonal image processing a practical approach

    CERN Document Server

    Middleton, Lee


    This book provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates. The strengths offered by hexagonal lattices over square lattices to define digital images are considerable: higher packing density; uniform connectivity of points (pixels) in the lattice; better angular resolution by virtue of having more nearest neighbours; and superlative representation of curves. The utility of the HIP framework is shown by implementing severa

  14. Fingerprint image enhancement by differential hysteresis processing. (United States)

    Blotta, Eduardo; Moler, Emilce


    A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

  15. Intelligent Information Processing in Imaging Fuzes

    Institute of Scientific and Technical Information of China (English)

    王克勇; 郑链; 宋承天


    In order to study the problem of intelligent information processing in new types of imaging fuze, the method of extracting the invariance features of target images is adopted, and radial basis function neural network is used to recognize targets. Owing to its ability of parallel processing, its robustness and generalization, the method can realize the recognition of the conditions of missile-target encounters, and meet the requirements of real-time recognition in the imaging fuze. It is shown that based on artificial neural network target recognition and burst point control are feasible.

  16. Rotation Covariant Image Processing for Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Henrik Skibbe


    Full Text Available With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

  17. Adaptive filters for color image processing

    Directory of Open Access Journals (Sweden)

    Papanikolaou V.


    Full Text Available The color filters that are used to attenuate noise are usually optimized to perform extremely well when dealing with certain noise distributions. Unfortunately it is often the case that the noise corrupting the image is not known. It is thus beneficial to know a priori the type of noise corrupting the image in order to select the optimal filter. A method of extracting and characterizing the noise within a digital color image using the generalized Gaussian probability density function (pdf (B.D. Jeffs and W.H. Pun, IEEE Transactions on Image Processing, 4(10, 1451–1456, 1995 and Proceedings of the Int. Conference on Image Processing, 465–468, 1996, is presented. In this paper simulation results are included to demonstrate the effectiveness of the proposed methodology.

  18. Adaptive filters for color image processing

    Directory of Open Access Journals (Sweden)

    V. Papanikolaou


    Full Text Available The color filters that are used to attenuate noise are usually optimized to perform extremely well when dealing with certain noise distributions. Unfortunately it is often the case that the noise corrupting the image is not known. It is thus beneficial to know a priori the type of noise corrupting the image in order to select the optimal filter. A method of extracting and characterizing the noise within a digital color image using the generalized Gaussian probability density function (pdf (B.D. Jeffs and W.H. Pun, IEEE Transactions on Image Processing, 4(10, 1451–1456, 1995 and Proceedings of the Int. Conference on Image Processing, 465–468, 1996, is presented. In this paper simulation results are included to demonstrate the effectiveness of the proposed methodology.

  19. Satellite Remote Sensing Image Analysis Technology Based on eCognition%基于eCognition的卫星遥感影像分析技术

    Institute of Scientific and Technical Information of China (English)



    The satellite remote sensing image analysis is a research hotspot in recent years. In this paper,the current progress of information extraction technology on satellite sensing images is analyzed,the advantage of object-oriented high-resolution image analysis is highlighted,and the application of target change detection of satellite sensing images in military field is introduced. In this paper,the object-oriented multiscale segmentation strategy is used in the field of satellite remote sensing image processing,and secondary develop-ment processes is implemented based on eCognition SDK. The results of multiple experiments show that the proposed satellite remote sensing image analysis technology can implement better information extraction and analysis.%卫星遥感影像分析技术是近年来的一个研究热点问题。归纳总结了遥感影像信息提取技术的发展现状,阐述了面向对象的高分辨率遥感影像分析技术的优势,介绍了遥感影像目标变化检测技术的应用情况。将面向对象的多尺度分割策略应用在卫星遥感影像处理领域,实现了基于eCognition SDK的二次开发流程,取得了良好的实验效果。

  20. Titan. [physical and chemical processes in satellite atmosphere (United States)

    Hunten, D. M.; Tomasko, M. G.; Flasar, F. M.; Samuelson, R. E.; Strobel, D. F.; Stevenson, D. J.


    It is pointed out that Titan, which is the second largest satellite in the solar system, is considerably larger than Mercury. It is made unique by its dense atmosphere, which consists mainly of nitrogen, although a substantial component of methane is present. The basic properties of Titan are summarized in a table. Many of the data were obtained during the close pass of Voyager 1 in November 1980. The atmospheric temperature decreases from its surface value of 94 K at a pressure of 1500 mbar to a minimum of 71 K at a height of 42 km and a pressure of 128 mbar. Details of atmospheric composition and thermal structure are discussed, taking into account chemical identifications and abundances, the vertical temperature structure, the horizontal temperature and opacity structure, and the radiative equilibrium. The upper atmosphere composition and temperature is considered along with the properties of aerosols, and meteorology and atmospheric dynamics. Titan's interior has an average density of 1.88 g per cu cm. Attention is given to Titan's surface and interior, and its formation.


    Directory of Open Access Journals (Sweden)

    G. Villa


    Full Text Available Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites pose big interoperability problems, as for example: non-alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression-decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in “Big Data” environments. Most of them can be avoided, or at least greatly reduced, with the use of a common “nested grid” for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. “Nested grids” are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A “nested grid” must be complemented by an appropriate “tiling schema”, ideally based on the “quad-tree” concept. In the last years a “de facto standard” grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its “WMTS Simple Profile” standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.

  2. Procedure to detect impervious surfaces using satellite images and light detection and ranging (lidar) data (United States)

    Rodríguez-Cuenca, B.; Alonso-Rodríguez, M. C.; Domenech-Tofiño, E.; Valcárcel Sanz, N.; Delgado-Hernández, J.; Peces-Morera, Juan José; Arozarena-Villar, Antonio


    The detection of impervious surfaces is an important issue in the study of urban and rural environments. Imperviousness refers to water's inability to pass through a surface. Although impervious surfaces represent a small percentage of the Earth's surface, knowledge of their locations is relevant to planning and managing human activities. Impervious structures are primarily manmade (e.g., roads and rooftops). Impervious surfaces are an environmental concern because many processes that modify the normal function of land, air, and water resources are initiated during their construction. This paper presents a novel method of identifying impervious surfaces using satellite images and light detection and ranging (LIDAR) data. The inputs for the procedure are SPOT images formed by four spectral bands (corresponding to red, green, near-infrared and mid-infrared wavelengths), a digital terrain model, and an .las file. The proposed method computes five decision indexes from the input data to classify the studied area into two categories: impervious (subdivided into buildings and roads) and non-impervious surfaces. The impervious class is divided into two subclasses because the elements forming this category (mainly roads and rooftops) have different spectral and height properties, and it is difficult to combine these elements into one group. The classification is conducted using a decision tree procedure. For every decision index, a threshold is set for which every surface is considered impervious or non-impervious. The proposed method has been applied to four different regions located in the north, center, and south of Spain, providing satisfactory results for every dataset.

  3. Satellite image classification methods and Landsat 5TM bands

    CERN Document Server

    Tamouk, Jamshid; Farmanbar, Mina


    This paper attempts to find the most accurate classification method among parallelepiped, minimum distance and chain methods. Moreover, this study also challenges to find the suitable combination of bands, which can lead to better results in case combinations of bands occur. After comparing these three methods, the chain method over perform the other methods with 79% overall accuracy. Hence, it is more accurate than minimum distance with 67% and parallelepiped with 65%. On the other hand, based on bands features, and also by combining several researchers' findings, a table was created which includes the main objects on the land and the suitable combination of the bands for accurately detecting of landcover objects. During this process, it was observed that band 4 (out of 7 bands of Landsat 5TM) is the band, which can be used for increasing the accuracy of the combined bands in detecting objects on the land.

  4. Floods, floodplains, delta plains — A satellite imaging approach (United States)

    Syvitski, James P. M.; Overeem, Irina; Brakenridge, G. Robert; Hannon, Mark


    Thirty-three lowland floodplains and their associated delta plains are characterized with data from three remote sensing systems (AMSR-E, SRTM and MODIS). These data provide new quantitative information to characterize Late Quaternary floodplain landscapes and their penchant for flooding over the last decade. Daily proxy records for discharge since 2002 and for each of the 33 river systems can be derived with novel Advanced Microwave Scanning Radiometer (AMSR-E) methods. A descriptive framework based on analysis of Shuttle Radar Topography Mission (SRTM) data is used to capture the major landscape-scale floodplain elements or zones: 1) container valleys with their long and narrow pathways of largely sediment transit and bypass, 2) floodplain depressions that act as loci for frequent flooding and sediment storage, 3) zones of nodal avulsions common to many continental scale rivers, and often located seaward of container valleys, and 4) coastal floodplains and delta plains that offer both sediment bypass and storage but under the influence of marine processes. The SRTM data allow mapping of smaller-scale architectural elements in unprecedented systematic manner. Floodplain depressions were found to play a major role, which may largely be overlooked in conceptual floodplain models. Lastly, MODIS data (independently and combined with AMSR-E) allows the tracking of flood hydrographs and pathways and sedimentation patterns on a near-daily timescale worldwide. These remote-sensing data show that 85% of the studied major river systems experienced extensive flooding in the last decade. A new quantitative paradigm of floodplain processes, honoring the frequency and extent of floods, can be develop by careful analysis of these new remotely sensed data.

  5. Quantitative measurements of Jupiter, Saturn, their rings and satellites made from Voyager imaging data (United States)

    Collins, S. A.; Bunker, A. S.


    The Voyager spacecraft cameras use selenium-sulfur slow scan vidicons to convert focused optical images into sensible electrical signals. The vidicon-generated data thus obtained are the basis of measurements of much greater precision than was previously possible, in virtue of their superior linearity, geometric fidelity, and the use of in-flight calibration. Attention is given to positional, radiometric, and dynamical measurements conducted on the basis of vidicon data for the Saturn rings, the Saturn satellites, and the Jupiter atmosphere.

  6. IoSiS: a radar system for imaging of satellites in space (United States)

    Jirousek, M.; Anger, S.; Dill, S.; Schreiber, E.; Peichl, M.


    Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolution radar images are helpful in analyzing a possible damage. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi-purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a highpower traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1 m RX antenna mounted on a common steerable positioner. High-resolution radar images are obtained by using Inverse Synthetic Aperture Radar (ISAR) techniques. The guided tracking of known objects during overpass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system including the basic setup of the antenna, the radar instrument with the RF error correction, and the measurement strategy. Also a short description about a simulation tool for the whole instrument and expected images is shown.

  7. Estimating Advective Near-surface Currents from Ocean Color Satellite Images (United States)


    K., Arnone, R.A., et al. (2014). Forecasting the ocean’s optical environment using the BioCast system. Oceanography , 27, 46–57. 14 H. Yang et al...satellite images 0602435N 73-9358-09-5 Haoping Yang, Robert Arnone, Jason Jolliff Naval Research Laboratory Oceanography Division Stennis Space Center...U.S. East and Gulf coasts. The MCC calculation is validated in a series of Bio- Optical Forecasting (BioCast) experiments with predetermined synthetic

  8. Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging (United States)

    Nag, S.; Li, A.


    Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall

  9. Primena satelitskih snimaka za dopunu sadržaja topografskih karata / An application of satellite images for improving the content of topographic maps

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić


    Full Text Available Neažurnost sadržaja topografskih karata (TK, uslovljena ponajviše stvarnim ekonomskim teškoćama pri izradi novih i dopuni postojećih izdanja, kao i nedovoljnost i sve teže stanje pri izradi ostalih geotopografskih materijala (GTM, u velikoj meri otežavaju geotopografsko obezbeđenje (GTOb vojske u miru, kao i u svim periodima pripreme i vođenja ratnih dejstava. Rešenje ovog problema je u iznalaženju adekvatnog načina upotrebe proizvoda svih vrsta daljinskih snimanja, a naročito u obradi kvalitetnih satelitskih snimaka. Kao najbolji pokazatelj velikih mogućnosti daljinske detekcije, korišćenjem satelitskih snimaka, u kartografskoj praksi primenom kvalitetnih softverskih rešenja, u radu je predstavljena dopuna topografske karte nedostajućim topografskim sadržajem. / Lack of updated content of topographic maps (TMs, mainly due to economic issues regarding the publishing of existing or revised TMs, substantially affects geo-topographic supply (GTS of the Army both in peace and warfare time, as well as shortage of other geo-topographic materials (GTMs. The solution to this problem is in finding an appropriate method of using products of all types of remote sensing, high quality satellite images in particular. Having shown the best possibilities of remote sensing while using satellite images in mapping through the quality software solutions, the author presents an addition to topographic maps based on missing topographic data. Introduction Numerous natural and social phenomena are constantly observed, surveyed, registered and analyzed. Permanent or periodical satellite surveillance and recording for different purposes are growing in importance. The purposes can range from meteorological issues, through study of large water surfaces to military intelligence, etc. These recording can be used in making topographic, thematic and working maps as well as other geo-topographic material. Processing and analyzing of ikonos2 satellite images

  10. Processing Earth Observing images with Ames Stereo Pipeline (United States)

    Beyer, R. A.; Moratto, Z. M.; Alexandrov, O.; Fong, T.; Shean, D. E.; Smith, B. E.


    ICESat with its GLAS instrument provided valuable elevation measurements of glaciers. The loss of this spacecraft caused a demand for alternative elevation sources. In response to that, we have improved our Ames Stereo Pipeline (ASP) software (version 2.1+) to ingest satellite imagery from Earth satellite sources in addition to its support of planetary missions. This enables the open source community a free method to generate digital elevation models (DEM) from Digital Globe stereo imagery and alternatively other cameras using RPC camera models. Here we present details of the software. ASP is a collection of utilities written in C++ and Python that implement stereogrammetry. It contains utilities to manipulate DEMs, project imagery, create KML image quad-trees, and perform simplistic 3D rendering. However its primary application is the creation of DEMs. This is achieved by matching every pixel between the images of a stereo observation via a hierarchical coarse-to-fine template matching method. Matched pixels between images represent a single feature that is triangulated using each image's camera model. The collection of triangulated features represents a point cloud that is then grid resampled to create a DEM. In order for ASP to match pixels/features between images, it requires a search range defined in pixel units. Total processing time is proportional to the area of the first image being matched multiplied by the area of the search range. An incorrect search range for ASP causes repeated false positive matches at each level of the image pyramid and causes excessive processing times with no valid DEM output. Therefore our system contains automatic methods for deducing what the correct search range should be. In addition, we provide options for reducing the overall search range by applying affine epipolar rectification, homography transform, or by map projecting against a prior existing low resolution DEM. Depending on the size of the images, parallax, and image

  11. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content. (United States)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.


    Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

  12. Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

    Energy Technology Data Exchange (ETDEWEB)

    Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)


    The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.

  13. Investigation of the recent recolonisation of Beech on Mont Ventoux using historical records, vegetation analyses from satellite image and landscape genetics


    Prouillet-Leplat, Hélène


    In this study, we investigated the genetic structure and the recolonisation process of the European beech (Fagus sylvatica) over the north face of the Mont Ventoux Mountain, using of combination of historical record investigation, vegetation mapping from satellite image and unsupervised classification process, and a landscape genetic approach. Mont Ventoux has undergone large deforestation phases until the XIXth century due to over-grazing and over-logging for woof supply. Historical records ...

  14. Automated Astrometric Analysis of Satellite Observations using Wide-field Imaging (United States)

    Skuljan, J.; Kay, J.


    An observational trial was conducted in the South Island of New Zealand from 24 to 28 February 2015, as a collaborative effort between the United Kingdom and New Zealand in the area of space situational awareness. The aim of the trial was to observe a number of satellites in low Earth orbit using wide-field imaging from two separate locations, in order to determine the space trajectory and compare the measurements with the predictions based on the standard two-line elements. This activity was an initial step in building a space situational awareness capability at the Defence Technology Agency of the New Zealand Defence Force. New Zealand has an important strategic position as the last land mass that many satellites selected for deorbiting pass before entering the Earth's atmosphere over the dedicated disposal area in the South Pacific. A preliminary analysis of the trial data has demonstrated that relatively inexpensive equipment can be used to successfully detect satellites at moderate altitudes. A total of 60 satellite passes were observed over the five nights of observation and about 2600 images were collected. A combination of cooled CCD and standard DSLR cameras were used, with a selection of lenses between 17 mm and 50 mm in focal length, covering a relatively wide field of view of 25 to 60 degrees. The CCD cameras were equipped with custom-made GPS modules to record the time of exposure with a high accuracy of one millisecond, or better. Specialised software has been developed for automated astrometric analysis of the trial data. The astrometric solution is obtained as a two-dimensional least-squares polynomial fit to the measured pixel positions of a large number of stars (typically 1000) detected across the image. The star identification is fully automated and works well for all camera-lens combinations used in the trial. A moderate polynomial degree of 3 to 5 is selected to take into account any image distortions introduced by the lens. A typical RMS

  15. Application of LANDSAT data and digital image processing. [Ruhr Valley, Germany (United States)

    Bodechtel, J. (Principal Investigator)


    The author has identified the following significant results. Based on LANDSAT 1 and 2 data, applications in the fields of coal mining, lignite exploration, and thematic mapping in geology are demonstrated. The hybrid image processing system, its software, and its utilization for educational purposes is described. A pre-operational European satellite is proposed.

  16. True Color Images of the Earth created with the Geostationary Satellite Instrument MSG SEVIRI (United States)

    Reuter, Maximilian


    One of the most famous pictures ever taken was by the crew of Apollo 17 in 1972, showing our Earth from a distance of about 45000km. This picture was named 'Blue Marble' and it reminds us of the beauty and uniqueness of our home planet. With geostationary satellites, such views of the Earth are possible without the need to have a photographer in space. However, up to the present, the production of such Blue Marble type images from geostationary satellite data has been impaired by the lack of channels in the visible spectral region. A method for the generation of full disk MSG (METEOSAT Second Generation) SEVIRI (Scanning-Enhanced Visible and Infrared Imager) true colour composite images will be presented. The algorithm mainly uses the SEVIRI channels VIS006 (0.6μm), NIR008 (0.8μm) and NIR016 (1.6μm). The lack of information in the blue and green parts of the visible spectrum is compensated by using data from NASA's (National Aeronautics and Space Administration's) Blue Marble next generation (BMNG) project to fill a look-up table (LUT) transforming RGB (red/green/blue) false colour composite images of VIS006/NIR008/NIR016 into true colour images. Tabulated radiative transfer calculations of a pure Rayleigh atmosphere are used to add an impression of Rayleigh scattering towards the sunlit horizon. The resulting images satisfy naive expectations: clouds are white or transparent, vegetated surfaces are greenish, deserts are sandy-coloured, the ocean is dark blue to black and a narrow halo due to Rayleigh scattering is visible at the sunlit horizon. Therefore, such images are easily interpretable also for inexperienced users not familiar with the characteristics of typical MSG false colour composite images. The images can be used for scientific applications to illustrate specific meteorological conditions or for non-scientific purposes, for example, for raising awareness in the public of the Earth's worthiness of protection.

  17. TESIS experiment on XUV imaging spectroscopy of the Sun onboard the CORONAS-PHOTON satellite (United States)

    Kuzin, S. V.; Zhitnik, I. A.; Bogachev, S. A.; Shestov, S. V.; Bugaenko, O. I.; Suhodrev, N. K.; Pertsov, A. A.; Mitrofanov, A. V.; Ignat'ev, A. P.; Slemzin, V. A.

    We present a brief description of new complex of space telescopes and spectrographs, TESIS, which will be placed aboard the CORONAS-PHOTON satellite. The complex is intended for high-resolution imaging observation of full Sun in the coronal spectral lines and in the spectral lines of the solar transition region. TESIS will be launched at the end of 2007 - early of 2008. About 25 % of the daily TESIS images will be free for use and for downloading from the TESIS data center that is planned to open 2 months before the TESIS launching at

  18. Near real-time disturbance detection using satellite image time series

    NARCIS (Netherlands)

    Verbesselt, J.P.; Zeileis, A.; Herold, M.


    Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic

  19. Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (United States)

    Davis, Philip A.


    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

  20. Processing ISS Images of Titan's Surface (United States)

    Perry, Jason; McEwen, Alfred; Fussner, Stephanie; Turtle, Elizabeth; West, Robert; Porco, Carolyn; Knowles, Ben; Dawson, Doug


    One of the primary goals of the Cassini-Huygens mission, in orbit around Saturn since July 2004, is to understand the surface and atmosphere of Titan. Surface investigations are primarily accomplished with RADAR, the Visual and Infrared Mapping Spectrometer (VIMS), and the Imaging Science Subsystem (ISS) [1]. The latter two use methane "windows", regions in Titan's reflectance spectrum where its atmosphere is most transparent, to observe the surface. For VIMS, this produces clear views of the surface near 2 and 5 microns [2]. ISS uses a narrow continuum band filter (CB3) at 938 nanometers. While these methane windows provide our best views of the surface, the images produced are not as crisp as ISS images of satellites like Dione and Iapetus [3] due to the atmosphere. Given a reasonable estimate of contrast (approx.30%), the apparent resolution of features is approximately 5 pixels due to the effects of the atmosphere and the Modulation Transfer Function of the camera [1,4]. The atmospheric haze also reduces contrast, especially with increasing emission angles [5].

  1. Satellite Image Processing for the Agulhas Retroflexion Region. (United States)


    Research under ( npy contract Numbers NO0014-82-C-0019. NR 083-004. NE N00014-85-C-001. NR 083-004, and N00014-87-K-0007, 6 NR 083-004. Reproduction in...time the logical volume is recorded. 17 This indicates the sequence number of the physical volume, within a volume set, which contains the 1st record...of the lo- gical volume. A blank field implies no speci4ic sequence . The first physical volume is numbered as 1. 18 This will be the same as above

  2. Bistatic SAR: Signal Processing and Image Formation.

    Energy Technology Data Exchange (ETDEWEB)

    Wahl, Daniel E.; Yocky, David A.


    This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

  3. Search for astronomical sites suitable for infrared observations using GOES satellite images (United States)

    Ducati, Jorge R.; Feijo, Eleandro S.


    Images from GOES satellite were used to develop a method to search for sites suitable to astronomical observations in the infrared. An area of study located in the Peruvian Andes was chosen, with altitudes above 2500 m. Forty-three images from the GOES meteorological satellite in channels 3, 4 and 5 were used. The GOES images, spanning an 11-day period, in each channel, were combined to produced images expressing the surface visibility in each channel. Atmospheric turbulence could be estimated from the variation of visibility over six-hour periods, with one image per hour. As criteria to classify sites on the Andes, we combined information on altitude, visibility of the surface in the infrared, the amount of water vapor in the atmosphere, and atmospheric turbulence. Results of this new method showed that the region of Moquegua, in South Peru, is to be preferred in surveys for astronomical sites. Comparisons with results from other investigators, which used other approaches, indicated that this methodology can produce valid results and can be applied to studies covering larger periods. The general results of this study indicate that the method is valid and can effectively be used as an important resource in surveys for infrared astronomical sites.

  4. Search for astronomical sites suitable for infrared observations using goes satellite images release (United States)

    Ducati, J. R.; Feijó, E.


    Astronomical sites are traditionally found after studies performed over many years, including preliminary selection of places based in general information on climate, clear skies and logistical adequacy. It follows extensive "in situ" monitoring of seeing and cloudiness. Theses procedures are long and expensive, and alternatives can be looked for. In this study, images from GOES meteorological satellite were used to develop a method to search for sites suitable to astronomical observations in the infrared. An area of study located in the Peruvian Andes was chosen, with altitudes above 2500 m. 43 images from the GOES meteorological satellite in chanels 3, 4 and 5 were used. The GOES images, spanning a 11-day period, in each channel, were combined to produced images expressing the surface visibility in each channel. Atmospheric turbulence could be estimated from the variation of visibility over six-hour periods, with one image per hour. As criteria to classify sites on the Andes, we combined information on altitude, visibility of the surface in the infrared, the amount of water vapor in the atmosphere, and atmospheric turbulence. Results of this new method showed that the region of Moquegua, in South Peru, is to be preferred in surveys for astronomical sites. Comparisons with results from other investigators, which used other approaches, indicated that this methodology produces valid results and can be used to studies spanning larger periods. The general results of this study indicate that the method can efectively be used as an important resource in surveys for infrared astronomical sites

  5. a New Algorithm for Void Filling in a Dsm from Stereo Satellite Images in Urban Areas (United States)

    Gharib Bafghi, Z.; Tian, J.; d'Angelo, P.; Reinartz, P.


    Digital Surface Models (DSM) derived from stereo-pair satellite images are the main sources for many Geo-Informatics applications like 3D change detection, object classification and recognition. However since occlusion especially in urban scenes result in some deficiencies in the stereo matching phase, these DSMs contain some voids. In order to fill the voids a range of algorithms have been proposed, mainly including interpolation alone or along with auxiliary DSM. In this paper an algorithm for void filling in DSM from stereo satellite images has been developed. Unlike common previous approaches we didn't use any external DSM to fill the voids. Our proposed algorithm uses only the original images and the unfilled DSM itself. First a neighborhood around every void in the unfilled DSM and its corresponding area in multispectral image is defined. Then it is analysed to extract both spectral and geometric texture and accordingly to assign labels to each cell in the voids. This step contains three phases comprising shadow detection, height thresholding and image segmentation. Thus every cell in void has a label and is filled by the median value of its co-labelled neighbors. The results for datasets from WorldView-2 and IKONOS are shown and discussed.


    Directory of Open Access Journals (Sweden)

    Z. Gharib Bafghi


    Full Text Available Digital Surface Models (DSM derived from stereo-pair satellite images are the main sources for many Geo-Informatics applications like 3D change detection, object classification and recognition. However since occlusion especially in urban scenes result in some deficiencies in the stereo matching phase, these DSMs contain some voids. In order to fill the voids a range of algorithms have been proposed, mainly including interpolation alone or along with auxiliary DSM. In this paper an algorithm for void filling in DSM from stereo satellite images has been developed. Unlike common previous approaches we didn’t use any external DSM to fill the voids. Our proposed algorithm uses only the original images and the unfilled DSM itself. First a neighborhood around every void in the unfilled DSM and its corresponding area in multispectral image is defined. Then it is analysed to extract both spectral and geometric texture and accordingly to assign labels to each cell in the voids. This step contains three phases comprising shadow detection, height thresholding and image segmentation. Thus every cell in void has a label and is filled by the median value of its co-labelled neighbors. The results for datasets from WorldView-2 and IKONOS are shown and discussed.

  7. Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS (United States)

    Hong, Gi Hoon; Yang, Dong Beom; Lee, Hyun-Mi; Yang, Sung Ryull; Chung, Hee Woon; Kim, Chang Joon; Kim, Young-Il; Chung, Chang Soo; Ahn, Yu-Hwan; Park, Young-Je; Moon, Jeong-Eon


    Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.

  8. Imager-to-radiometer inflight cross calibration: RSP radiometric comparison with airborne and satellite sensors

    Directory of Open Access Journals (Sweden)

    J. McCorkel


    Full Text Available This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP that takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS, which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI. First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.


    National Research Council Canada - National Science Library

    Cooper, Nicholas J; Renner, Stéfan; Murray, Carl D; Evans, Michael W


    We present numerically derived orbits and mass estimates for the inner Saturnian satellites, Atlas, Prometheus, Pandora, Janus, and Epimetheus from a fit to 2580 new Cassini Imaging Science Subsystem...

  10. Magnetic Field Satellite (Magsat) data processing system specifications (United States)

    Berman, D.; Gomez, R.; Miller, A.


    The software specifications for the MAGSAT data processing system (MDPS) are presented. The MDPS is divided functionally into preprocessing of primary input data, data management, chronicle processing, and postprocessing. Data organization and validity, and checks of spacecraft and instrumentation are dicussed. Output products of the MDPS, including various plots and data tapes, are described. Formats for important tapes are presented. Dicussions and mathematical formulations for coordinate transformations and field model coefficients are included.

  11. Thermal Imaging Processes of Polymer Nanocomposite Coatings (United States)

    Meth, Jeffrey


    Laser induced thermal imaging (LITI) is a process whereby infrared radiation impinging on a coating on a donor film transfers that coating to a receiving film to produce a pattern. This talk describes how LITI patterning can print color filters for liquid crystal displays, and details the physical processes that are responsible for transferring the nanocomposite coating in a coherent manner that does not degrade its optical properties. Unique features of this process involve heating rates of 107 K/s, and cooling rates of 104 K/s, which implies that not all of the relaxation modes of the polymer are accessed during the imaging process. On the microsecond time scale, the polymer flow is forced by devolatilization of solvents, followed by deformation akin to the constrained blister test, and then fracture caused by differential thermal expansion. The unique combination of disparate physical processes demonstrates the gamut of physics that contribute to advanced material processing in an industrial setting.

  12. Tree detection in orchards from VHR satellite images using scale-space theory (United States)

    Mahour, Milad; Tolpekin, Valentyn; Stein, Alfred


    This study focused on extracting reliable and detailed information from very High Resolution (VHR) satellite images for the detection of individual trees in orchards. The images contain detailed information on spectral and geometrical properties of trees. Their scale level, however, is insufficient for spectral properties of individual trees, because adjacent tree canopies interlock. We modeled trees using a bell shaped spectral profile. Identifying the brightest peak was challenging due to sun illumination effects caused 1 by differences in positions of the sun and the satellite sensor. Crown boundary detection was solved by using the NDVI from the same image. We used Gaussian scale-space methods that search for extrema in the scale-space domain. The procedures were tested on two orchards with different tree types, tree sizes and tree observation patterns in Iran. Validation was done using reference data derived from an UltraCam digital aerial photo. Local extrema of the determinant of the Hessian corresponded well to the geographical coordinates and the size of individual trees. False detections arising from a slight asymmetry of trees were distinguished from multiple detections of the same tree with different extents. Uncertainty assessment was carried out on the presence and spatial extents of individual trees. The study demonstrated how the suggested approach can be used for image segmentation for orchards with different types of trees. We concluded that Gaussian scale-space theory can be applied to extract information from VHR satellite images for individual tree detection. This may lead to improved decision making for irrigation and crop water requirement purposes in future studies.

  13. Fundamental Concepts of Digital Image Processing (United States)

    Twogood, R. E.


    The field of a digital-image processing has experienced dramatic growth and increasingly widespread applicability in recent years. Fortunately, advances in computer technology have kept pace with the rapid growth in volume of image data in these and other applications. Digital image processing has become economical in many fields of research and in industrial and military applications. While each application has requirements unique from the others, all are concerned with faster, cheaper, more accurate, and more extensive computation. The trend is toward real-time and interactive operations, where the user of the system obtains preliminary results within a short enough time that the next decision can be made by the human processor without loss of concentration on the task at hand. An example of this is the obtaining of two-dimensional (2-D) computer-aided tomography (CAT) images. A medical decision might be made while the patient is still under observation rather than days later.

  14. Fundamental concepts of digital image processing

    Energy Technology Data Exchange (ETDEWEB)

    Twogood, R.E.


    The field of a digital-image processing has experienced dramatic growth and increasingly widespread applicability in recent years. Fortunately, advances in computer technology have kept pace with the rapid growth in volume of image data in these and other applications. Digital image processing has become economical in many fields of research and in industrial and military applications. While each application has requirements unique from the others, all are concerned with faster, cheaper, more accurate, and more extensive computation. The trend is toward real-time and interactive operations, where the user of the system obtains preliminary results within a short enough time that the next decision can be made by the human processor without loss of concentration on the task at hand. An example of this is the obtaining of two-dimensional (2-D) computer-aided tomography (CAT) images. A medical decision might be made while the patient is still under observation rather than days later.

  15. Image Processing in Intelligent Medical Robotic Systems

    Directory of Open Access Journals (Sweden)

    Shashev Dmitriy


    Full Text Available The paper deals with the use of high-performance computing systems with the parallel-operation architecture in intelligent medical systems, such as medical robotic systems, based on a computer vision system, is an automatic control system with the strict requirements, such as high reliability, accuracy and speed of performance. It shows the basic block-diagram of an automatic control system based on a computer vision system. The author considers the possibility of using a reconfigurable computing environment in such systems. The design principles of the reconfigurable computing environment allows to improve a reliability, accuracy and performance of whole system many times. The article contains the brief overview and the theory of the research, demonstrates the use of reconfigurable computing environments for the image preprocessing, namely morphological image processing operations. Present results of the successful simulation of the reconfigurable computing environment and implementation of the morphological image processing operations on the test image in the MATLAB Simulink.

  16. Employing image processing techniques for cancer detection using microarray images. (United States)

    Dehghan Khalilabad, Nastaran; Hassanpour, Hamid


    Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively.

  17. Digital-image processing and image analysis of glacier ice (United States)

    Fitzpatrick, Joan J.


    This document provides a methodology for extracting grain statistics from 8-bit color and grayscale images of thin sections of glacier ice—a subset of physical properties measurements typically performed on ice cores. This type of analysis is most commonly used to characterize the evolution of ice-crystal size, shape, and intercrystalline spatial relations within a large body of ice sampled by deep ice-coring projects from which paleoclimate records will be developed. However, such information is equally useful for investigating the stress state and physical responses of ice to stresses within a glacier. The methods of analysis presented here go hand-in-hand with the analysis of ice fabrics (aggregate crystal orientations) and, when combined with fabric analysis, provide a powerful method for investigating the dynamic recrystallization and deformation behaviors of bodies of ice in motion. The procedures described in this document compose a step-by-step handbook for a specific image acquisition and data reduction system built in support of U.S. Geological Survey ice analysis projects, but the general methodology can be used with any combination of image processing and analysis software. The specific approaches in this document use the FoveaPro 4 plug-in toolset to Adobe Photoshop CS5 Extended but it can be carried out equally well, though somewhat less conveniently, with software such as the image processing toolbox in MATLAB, Image-Pro Plus, or ImageJ.

  18. Image Processing by Compression: An Overview



    International audience; This article aims to present the various applications of data compression in image processing. Since some time ago, several research groups have been developing methods based on different data compression techniques to classify, segment, filter and detect digital images fakery. It is necessary to analyze the relationship between different methods and put them into a framework to better understand and better exploit the possibilities that compression provides us respect...

  19. Compression Techniques for Image Processing Tasks



    International audience; This article aims to present an overview of the different applications of data compression techniques in the image processing filed. Since some time ago, several research groups in the world have been developing various methods based on different data compression techniques to classify, segment, filter and detect digital images fakery. In this sense, it is necessary to analyze and clarify the relationship between different methods and put them into a framework to bette...

  20. A brief review of digital image processing (United States)

    Billingsley, F. C.


    The review is presented with particular reference to Skylab S-192 and Landsat MSS imagery. Attention is given to rectification (calibration) processing with emphasis on geometric correction of image distortions. Image enhancement techniques (e.g., the use of high pass digital filters to eliminate gross shading to allow emphasis of the fine detail) are described along with data analysis and system considerations (software philosophy).

  1. PCB Fault Detection Using Image Processing (United States)

    Nayak, Jithendra P. R.; Anitha, K.; Parameshachari, B. D., Dr.; Banu, Reshma, Dr.; Rashmi, P.


    The importance of the Printed Circuit Board inspection process has been magnified by requirements of the modern manufacturing environment where delivery of 100% defect free PCBs is the expectation. To meet such expectations, identifying various defects and their types becomes the first step. In this PCB inspection system the inspection algorithm mainly focuses on the defect detection using the natural images. Many practical issues like tilt of the images, bad light conditions, height at which images are taken etc. are to be considered to ensure good quality of the image which can then be used for defect detection. Printed circuit board (PCB) fabrication is a multidisciplinary process, and etching is the most critical part in the PCB manufacturing process. The main objective of Etching process is to remove the exposed unwanted copper other than the required circuit pattern. In order to minimize scrap caused by the wrongly etched PCB panel, inspection has to be done in early stage. However, all of the inspections are done after the etching process where any defective PCB found is no longer useful and is simply thrown away. Since etching process costs 0% of the entire PCB fabrication, it is uneconomical to simply discard the defective PCBs. In this paper a method to identify the defects in natural PCB images and associated practical issues are addressed using Software tools and some of the major types of single layer PCB defects are Pattern Cut, Pin hole, Pattern Short, Nick etc., Therefore the defects should be identified before the etching process so that the PCB would be reprocessed. In the present approach expected to improve the efficiency of the system in detecting the defects even in low quality images

  2. Digital image processing in neutron radiography

    CERN Document Server

    Körner, S


    automated neutron tomography facility has been built at the Atominstitut with this detector. Digital Image Processing: Due to special detector properties of the CCD-camera NR detector, a standard image processing procedure has been developed that always has to be applied, when the CCD-detector is used. It consists of the following steps: white spot correction - dark frame correction and flat field correction. Radiation, which hits the CCD-chip causes an overflow of one or several pixels, which appears in the image as white spots. These disturbing spots have to be removed by means of digital image processing. Several filters have been tested, but the results were insufficient. Therefore, a new threshold-median-mean value filter was designed and a proper code was written in IDL (interactive data language). The new filter removes white spots very well by hardly blurring the images. A dark frame is an image made with closed camera shutter. It contains undesired detector signal caused by read out noise and dark cu...

  3. Dust levitation as a major resurfacing process on the surface of a saturnian icy satellite, Atlas (United States)

    Hirata, Naoyuki; Miyamoto, Hideaki


    A small inner satellite of Saturn, Atlas, has an enigmatic saucer-like shape explained by an accumulation of particles from A-ring of Saturn. However, its unusual smooth surface remains unexplained. Gardening through continuous particle impact events cannot be a unique explanation for the smoothness, because Prometheus does not exhibit a similar surface, though it too would have experienced a similar bombardment. Here, a detailed investigation using close-up images of Atlas reveals the surface to be (1) covered by fine particles (i.e., probably as small as several tens of micrometers); (2) mostly void of impact craters (i.e., only one has been thus far identified); and (3) continuously smooth, even between the equatorial ridge and the undulating polar region. These findings imply that some sort of crater-erasing process has been active on the surface of Atlas. From electro-static analyses, we propose that the upper-most layer of the fine particles can become electro-statically unstable and migrate as a result of dust levitation, which resulted in erasing craters on the surface of Atlas. If true, Atlas would represent the first recognized body where resurfacing is dominated by dust levitation.

  4. Three-dimensional image signals: processing methods (United States)

    Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru


    Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

  5. Matlab-supported undergraduate image processing instruction (United States)

    Dawant, Benoit M.


    More and more often, undergraduate students express the desire to take a course on image processing. These students will learn the most if the theory and algorithms covered in class can be not only illustrated through examples shown by the instructor during class but also coded, tested, and evaluated by the class participants. In the past, the major hurdle to developing a hands-on approach to image processing instruction has been the amount of programming required to implement relatively simple applications. Typical undergraduate students lack experience with low level programming languages and time is spent teaching the language itself rather than experimenting with the algorithms. High level and interpreted programming languages such as Matlab permit to address this question. Even with very little practical exposure to the language, students can rapidly develop the level of skills required to implement a range of image processing algorithms. This presentation will go over the material covered in a senior level introductory course in image processing taught at Vanderbilt University. The course itself is taught in a traditional way but it is supported by laboratories during which students are asked to implement algorithms ranging from connected component labeling to image deblurring. The students are also assigned projects that span several weeks. Examples of such assignments and projects are presented.

  6. Multi Resolution Analysis (MRA of satellite images of oil spill disasters

    Directory of Open Access Journals (Sweden)

    Rashid Hussain


    Full Text Available Oil spill disasters monitoring and mitigation requires availability of state of the art applications and tools. Conventional technology gets benefit from latest trends and research in satellite imaginary. This research highlights multi-resolution wavelet analysis of satellite images of oil spill disasters. Multi-resolution analysis is one of the powerful techniques to analyze information content of images. This analysis enables us to have a scale-invariant interpretation of the image. At each resolution level, both smooth and detailed signals carry all the necessary information to reconstruct the smooth signal at the next level. The wavelet decomposition results in detail and approximate threshold coefficients. Multi resolution wavelet decomposition is used to analyze the image in both time and frequency domain. It provides better frequency resolution and poor time resolution for lower frequency; better time resolution and poor frequency resolution for higher frequency. This condition is fortunately suited for real applications; as signals have high frequency components for very short period of the interval and low frequency components for longer durations.

  7. Amazon Rainforest Deforestation Daily Detection Tool Using Artificial Neural Networks and Satellite Images

    Directory of Open Access Journals (Sweden)

    Silvio César Cazella


    Full Text Available The main purpose of this work was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA [1] sensor and Artificial Neural Networks. The developed tool provides the parameterization of the configuration for the neural network training to enable us to find the best neural architecture to address the problem. The tool makes use of confusion matrixes to determine the degree of success of the network. Part of the municipality of Porto Velho, in Rondônia state, is located inside the tile H11V09 of the MODIS/TERRA sensor, which was used as the study area. A spectrum-temporal analysis of this area was made on 57 images from 20 of May to 15 of July 2003 using the trained neural network. This analysis allowed us to verify the quality of the implemented neural network classification as well as helping our understanding of the dynamics of deforestation in the Amazon rainforest. The great potential of neural networks for image classification was perceived with this work. However, the generation of consistent alarms, in other words, detecting predatory actions at the beginning; instead of firing false alarms is a complex task that has not yet been solved. Therefore, the major contribution of this paper is to provide a theoretical basis and practical use of neural networks and satellite images to combat illegal deforestation.

  8. Semi-automatic verification of cropland and grassland using very high resolution mono-temporal satellite images (United States)

    Helmholz, Petra; Rottensteiner, Franz; Heipke, Christian


    Many public and private decisions rely on geospatial information stored in a GIS database. For good decision making this information has to be complete, consistent, accurate and up-to-date. In this paper we introduce a new approach for the semi-automatic verification of a specific part of the, possibly outdated GIS database, namely cropland and grassland objects, using mono-temporal very high resolution (VHR) multispectral satellite images. The approach consists of two steps: first, a supervised pixel-based classification based on a Markov Random Field is employed to extract image regions which contain agricultural areas (without distinction between cropland and grassland), and these regions are intersected with boundaries of the agricultural objects from the GIS database. Subsequently, GIS objects labelled as cropland or grassland in the database and showing agricultural areas in the image are subdivided into different homogeneous regions by means of image segmentation, followed by a classification of these segments into either cropland or grassland using a Support Vector Machine. The classification result of all segments belonging to one GIS object are finally merged and compared with the GIS database label. The developed approach was tested on a number of images. The evaluation shows that errors in the GIS database can be significantly reduced while also speeding up the whole verification task when compared to a manual process.

  9. Support Routines for In Situ Image Processing (United States)

    Deen, Robert G.; Pariser, Oleg; Yeates, Matthew C.; Lee, Hyun H.; Lorre, Jean


    This software consists of a set of application programs that support ground-based image processing for in situ missions. These programs represent a collection of utility routines that perform miscellaneous functions in the context of the ground data system. Each one fulfills some specific need as determined via operational experience. The most unique aspect to these programs is that they are integrated into the large, in situ image processing system via the PIG (Planetary Image Geometry) library. They work directly with space in situ data, understanding the appropriate image meta-data fields and updating them properly. The programs themselves are completely multimission; all mission dependencies are handled by PIG. This suite of programs consists of: (1)marscahv: Generates a linearized, epi-polar aligned image given a stereo pair of images. These images are optimized for 1-D stereo correlations, (2) marscheckcm: Compares the camera model in an image label with one derived via kinematics modeling on the ground, (3) marschkovl: Checks the overlaps between a list of images in order to determine which might be stereo pairs. This is useful for non-traditional stereo images like long-baseline or those from an articulating arm camera, (4) marscoordtrans: Translates mosaic coordinates from one form into another, (5) marsdispcompare: Checks a Left Right stereo disparity image against a Right Left disparity image to ensure they are consistent with each other, (6) marsdispwarp: Takes one image of a stereo pair and warps it through a disparity map to create a synthetic opposite- eye image. For example, a right eye image could be transformed to look like it was taken from the left eye via this program, (7) marsfidfinder: Finds fiducial markers in an image by projecting their approximate location and then using correlation to locate the markers to subpixel accuracy. These fiducial markets are small targets attached to the spacecraft surface. This helps verify, or improve, the

  10. Automatic geolocation of targets tracked by aerial imaging platforms using satellite imagery (United States)

    Shukla, P. K.; Goel, S.; Singh, P.; Lohani, B.


    Tracking of targets from aerial platforms is an important activity in several applications, especially surveillance. Knowled ge of geolocation of these targets adds additional significant and useful information to the application. This paper determines the geolocation of a target being tracked from an aerial platform using the technique of image registration. Current approaches utilize a POS to determine the location of the aerial platform and then use the same for geolocation of the targets using the principle of photogrammetry. The constraints of cost and low-payload restrict the applicability of this approach using UAV platforms. This paper proposes a methodology for determining the geolocation of a target tracked from an aerial platform in a partially GPS devoid environment. The method utilises automatic feature based registration technique of a georeferenced satellite image with an ae rial image which is already stored in UAV's database to retrieve the geolocation of the target. Since it is easier to register subsequent aerial images due to similar viewing parameters, the subsequent overlapping images are registered together sequentially thus resulting in the registration of each of the images with georeferenced satellite image thus leading to geolocation of the target under interest. Using the proposed approach, the target can be tracked in all the frames in which it is visible. The proposed concept is verified experimentally and the results are found satisfactory. Using the proposed method, a user can obtain location of target of interest as well features on ground without requiring any POS on-board the aerial platform. The proposed approach has applications in surveillance for target tracking, target geolocation as well as in disaster management projects like search and rescue operations.

  11. Real-time image and video processing

    CERN Document Server

    Kehtarnavaz, Nasser


    This book presents an overview of the guidelines and strategies for transitioning an image or video processing algorithm from a research environment into a real-time constrained environment. Such guidelines and strategies are scattered in the literature of various disciplines including image processing, computer engineering, and software engineering, and thus have not previously appeared in one place. By bringing these strategies into one place, the book is intended to serve the greater community of researchers, practicing engineers, industrial professionals, who are interested in taking an im

  12. Practical image and video processing using MATLAB

    CERN Document Server

    Marques, Oge


    "The book provides a practical introduction to the most important topics in image and video processing using MATLAB (and its Image Processing Toolbox) as a tool to demonstrate the most important techniques and algorithms. The contents are presented in a clear, technically accurate, objective way, with just enough mathematical detail. Most of the chapters are supported by figures, examples, illustrative problems, MATLAB scripts, suggestions for further reading, bibliographical references, useful Web sites, and exercises and computer projects to extend the understanding of their contents"--

  13. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.


    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.

  14. LineCast: line-based distributed coding and transmission for broadcasting satellite images. (United States)

    Wu, Feng; Peng, Xiulian; Xu, Jizheng


    In this paper, we propose a novel coding and transmission scheme, called LineCast, for broadcasting satellite images to a large number of receivers. The proposed LineCast matches perfectly with the line scanning cameras that are widely adopted in orbit satellites to capture high-resolution images. On the sender side, each captured line is immediately compressed by a transform-domain scalar modulo quantization. Without syndrome coding, the transmission power is directly allocated to quantized coefficients by scaling the coefficients according to their distributions. Finally, the scaled coefficients are transmitted over a dense constellation. This line-based distributed scheme features low delay, low memory cost, and low complexity. On the receiver side, our proposed line-based prediction is used to generate side information from previously decoded lines, which fully utilizes the correlation among lines. The quantized coefficients are decoded by the linear least square estimator from the received data. The image line is then reconstructed by the scalar modulo dequantization using the generated side information. Since there is neither syndrome coding nor channel coding, the proposed LineCast can make a large number of receivers reach the qualities matching their channel conditions. Our theoretical analysis shows that the proposed LineCast can achieve Shannon's optimum performance by using a high-dimensional modulo-lattice quantization. Experiments on satellite images demonstrate that it achieves up to 1.9-dB gain over the state-of-the-art 2D broadcasting scheme and a gain of more than 5 dB over JPEG 2000 with forward error correction.

  15. VIPS: an image processing system for large images (United States)

    Cupitt, John; Martinez, Kirk


    This paper describes VIPS (VASARI Image Processing System), an image processing system developed by the authors in the course of the EU-funded projects VASARI (1989-1992) and MARC (1992-1995). VIPS implements a fully demand-driven dataflow image IO (input- output) system. Evaluation of library functions is delayed for as long as possible. When evaluation does occur, all delayed operations evaluate together in a pipeline, requiring no space for storing intermediate images and no unnecessary disc IO. If more than one CPU is available, then VIPS operations will automatically evaluate in parallel, giving an approximately linear speed-up. The evaluation system can be controlled by the application programmer. We have implemented a user-interface for the VIPS library which uses expose events in an X window rather than disc output to drive evaluation. This makes it possible, for example, for the user to rotate an 800 MByte image by 12 degrees and immediately scroll around the result.

  16. Monitoring of global geodynamic processes using satellite observations

    Directory of Open Access Journals (Sweden)

    S.K. Tatevian


    One of the active tectonic zones of Egypt located in Aswan, is characterized by regional basement rock uplift and regional faulting. In 1997, the African Regional Geodynamic Network was developed around the northern part of Lake Nasser, consists of 11 points, on both sides of the Lake. Its main goal is to study the geodynamical behavior around the northern part of the lake. The collected data were processed using the Bernese software version 5.0. From the velocity results, including also the African plate motion, it can be noticed that all stations of this network are moved to the northeast direction and it is typically the direction of the African plate motion.

  17. FLIPS: Friendly Lisp Image Processing System (United States)

    Gee, Shirley J.


    The Friendly Lisp Image Processing System (FLIPS) is the interface to Advanced Target Detection (ATD), a multi-resolutional image analysis system developed by Hughes in conjunction with the Hughes Research Laboratories. Both menu- and graphics-driven, FLIPS enhances system usability by supporting the interactive nature of research and development. Although much progress has been made, fully automated image understanding technology that is both robust and reliable is not a reality. In situations where highly accurate results are required, skilled human analysts must still verify the findings of these systems. Furthermore, the systems often require processing times several orders of magnitude greater than that needed by veteran personnel to analyze the same image. The purpose of FLIPS is to facilitate the ability of an image analyst to take statistical measurements on digital imagery in a timely fashion, a capability critical in research environments where a large percentage of time is expended in algorithm development. In many cases, this entails minor modifications or code tinkering. Without a well-developed man-machine interface, throughput is unduly constricted. FLIPS provides mechanisms which support rapid prototyping for ATD. This paper examines the ATD/FLIPS system. The philosophy of ATD in addressing image understanding problems is described, and the capabilities of FLIPS are discussed, along with a description of the interaction between ATD and FLIPS. Finally, an overview of current plans for the system is outlined.

  18. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan (United States)

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


    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

  19. Processing Images of Craters for Spacecraft Navigation (United States)

    Cheng, Yang; Johnson, Andrew E.; Matthies, Larry H.


    A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.

  20. Comparing Manual and Semi-Automated Landslide Mapping Based on Optical Satellite Images from Different Sensors

    Directory of Open Access Journals (Sweden)

    Daniel Hölbling


    Full Text Available Object-based image analysis (OBIA has been increasingly used to map geohazards such as landslides on optical satellite images. OBIA shows various advantages over traditional image analysis methods due to its potential for considering various properties of segmentation-derived image objects (spectral, spatial, contextual, and textural for classification. For accurately identifying and mapping landslides, however, visual image interpretation is still the most widely used method. The major question therefore is if semi-automated methods such as OBIA can achieve results of comparable quality in contrast to visual image interpretation. In this paper we apply OBIA for detecting and delineating landslides in five selected study areas in Austria and Italy using optical Earth Observation (EO data from different sensors (Landsat 7, SPOT-5, WorldView-2/3, and Sentinel-2 and compare the OBIA mapping results to outcomes from visual image interpretation. A detailed evaluation of the mapping results per study area and sensor is performed by a number of spatial accuracy metrics, and the advantages and disadvantages of the two approaches for landslide mapping on optical EO data are discussed. The analyses show that both methods produce similar results, whereby the achieved accuracy values vary between the study areas.