Sample records for multi-spectral image analysis

  1. Multi-spectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

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


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

  2. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    with corresponding sensory data would be of great interest. The purpose of this research was to produce a method capable of quantifying and/or predicting the spoilage status (e.g. express in TVC counts as well as on sensory evaluation) using a multi spectral image of a meat sample and thereby avoid any time...... classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat...... samples. In the case where all data were taken together the misclassification error amounted to 16%. When spoilage status was based on visual sensory data, the model produced a MER of 22% for the combined dataset. These results suggest that it is feasible to employ a multi spectral image...

  3. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    ) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...... classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat...... samples regarding the spoilage process as evaluated from sensory as well as from microbiological data. The support vector classification (SVC) model outperformed other models. Specifically, the misclassification error rate (MER), derived from odour characteristics, was 18% for both aerobic and MAP meat...

  4. Multi-spectral imager

    CSIR Research Space (South Africa)

    Stolper, R


    Full Text Available This poster highlights the design and development of a camera which combines ultraviolet, infrared and visual imaging techniques for advanced diagnostic inspections, and also shows some evaluations carried out to demonstrate the operability...

  5. Multi Spectral Fluorescence Imager (MSFI) (United States)

    Caron, Allison


    Genetic transformation with in vivo reporter genes for fluorescent proteins can be performed on a variety of organisms to address fundamental biological questions. Model organisms that may utilize an ISS imager include unicellular organisms (Saccharomyces cerevisiae), plants (Arabidopsis thaliana), and invertebrates (Caenorhabditis elegans). The multispectral fluorescence imager (MSFI) will have the capability to accommodate 10 cm x 10 cm Petri plates, various sized multi-well culture plates, and other custom culture containers. Features will include programmable temperature and light cycles, ethylene scrubbing (less than 25 ppb), CO2 control (between 400 ppm and ISS-ambient levels in units of 100 ppm) and sufficient airflow to prevent condensation that would interfere with imaging.

  6. Compact multi-spectral imaging system for dermatology and neurosurgery (United States)

    Noordmans, Herke Jan; de Roode, Rowland; Verdaasdonk, Rudolf


    A compact multi-spectral imaging system is presented as diagnostic tool in dermatology and neurosurgery. Using an electronically tunable filter, a sensitive high resolution digital camera, 140 spectral images from 400 nm up to 720 nm are acquired in 40 s. Advanced image processing algorithms are used to enable interactive acquisition, viewing, image registration and image analysis. Experiments in the department of dermatology and neurosurgery show that multispectral imaging reveals much more detail than conventional medical photography or a surgical microscope, as images can be reprocessed to enhance the view on e.g. tumor boundaries. Using a hardware-based interactive registration algorithm, multi-spectral images can be aligned to correct for motion occurred during image acquisition or to compare acquisitions from different moments in time. The system shows to be a powerful diagnostics tool for medical imaging in the visual and near IR range.

  7. Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin (United States)

    Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.


    In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

  8. Retinal oxygen saturation evaluation by multi-spectral fundus imaging (United States)

    Khoobehi, Bahram; Ning, Jinfeng; Puissegur, Elise; Bordeaux, Kimberly; Balasubramanian, Madhusudhanan; Beach, James


    Purpose: To develop a multi-spectral method to measure oxygen saturation of the retina in the human eye. Methods: Five Cynomolgus monkeys with normal eyes were anesthetized with intramuscular ketamine/xylazine and intravenous pentobarbital. Multi-spectral fundus imaging was performed in five monkeys with a commercial fundus camera equipped with a liquid crystal tuned filter in the illumination light path and a 16-bit digital camera. Recording parameters were controlled with software written specifically for the application. Seven images at successively longer oxygen-sensing wavelengths were recorded within 4 seconds. Individual images for each wavelength were captured in less than 100 msec of flash illumination. Slightly misaligned images of separate wavelengths due to slight eye motion were registered and corrected by translational and rotational image registration prior to analysis. Numerical values of relative oxygen saturation of retinal arteries and veins and the underlying tissue in between the artery/vein pairs were evaluated by an algorithm previously described, but which is now corrected for blood volume from averaged pixels (n > 1000). Color saturation maps were constructed by applying the algorithm at each image pixel using a Matlab script. Results: Both the numerical values of relative oxygen saturation and the saturation maps correspond to the physiological condition, that is, in a normal retina, the artery is more saturated than the tissue and the tissue is more saturated than the vein. With the multi-spectral fundus camera and proper registration of the multi-wavelength images, we were able to determine oxygen saturation in the primate retinal structures on a tolerable time scale which is applicable to human subjects. Conclusions: Seven wavelength multi-spectral imagery can be used to measure oxygen saturation in retinal artery, vein, and tissue (microcirculation). This technique is safe and can be used to monitor oxygen uptake in humans. This work

  9. Performance Analysis of Multi Spectral Band Image Compression using Discrete Wavelet Transform

    Directory of Open Access Journals (Sweden)

    S. S. Ramakrishnan


    Full Text Available Problem statement: Efficient and effective utilization of transmission bandwidth and storage capacity have been a core area of research for remote sensing images. Hence image compression is required for multi-band satellite imagery. In addition, image quality is also an important factor after compression and reconstruction. Approach: In this investigation, the discrete wavelet transform is used to compress the Landsat5 agriculture and forestry image using various wavelets and the spectral signature graph is drawn. Results: The compressed image performance is analyzed using Compression Ratio (CR, Peak Signal to Noise Ratio (PSNR. The compressed image using dmey wavelet is selected based on its Digital Number Minimum (DNmin and Digital Number Maximum (DNmax. Then it is classified using maximum likelihood classification and the accuracy is determined using error matrix, kappa statistics and over all accuracy. Conclusion: Hence the proposed compression technique is well suited to compress the agriculture and forestry multi-band image.

  10. Precise acquisition and unsupervised segmentation of multi-spectral images

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær


    In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral images and a novel multi-spectral image segmentation algorithm are proposed. The system collects up to 20 different spectral bands within a range that vary from 395 nm to 970 nm. The system is designed...... to acquire geometrically and chromatically corrected images in homogeneous and diffuse illumination, so images can be compared over time. The proposed segmentation algorithm combines the information provided by all the spectral bands to segment the different regions of interest. Three experiments...

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

    NARCIS (Netherlands)

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


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

  12. Multi-spectral confocal microendoscope for in-vivo imaging (United States)

    Rouse, Andrew Robert

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

  13. Precise Multi-Spectral Dermatological Imaging

    DEFF Research Database (Denmark)

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


    . These spectral bands vary from ultraviolet to near infrared. The welldefined and diffuse illumination of the optically closed scene aims to avoid shadows and specular reflections. Furthermore, the system has been developed to guarantee the reproducibility of the collected images. This allows for comparative...

  14. Semiconductor Laser Multi-Spectral Sensing and Imaging

    Directory of Open Access Journals (Sweden)

    Han Q. Le


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

  15. Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images. (United States)

    Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina


    This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude.

  16. Software defined multi-spectral imaging for Arctic sensor networks (United States)

    Siewert, Sam; Angoth, Vivek; Krishnamurthy, Ramnarayan; Mani, Karthikeyan; Mock, Kenrick; Singh, Surjith B.; Srivistava, Saurav; Wagner, Chris; Claus, Ryan; Vis, Matthew Demi


    Availability of off-the-shelf infrared sensors combined with high definition visible cameras has made possible the construction of a Software Defined Multi-Spectral Imager (SDMSI) combining long-wave, near-infrared and visible imaging. The SDMSI requires a real-time embedded processor to fuse images and to create real-time depth maps for opportunistic uplink in sensor networks. Researchers at Embry Riddle Aeronautical University working with University of Alaska Anchorage at the Arctic Domain Awareness Center and the University of Colorado Boulder have built several versions of a low-cost drop-in-place SDMSI to test alternatives for power efficient image fusion. The SDMSI is intended for use in field applications including marine security, search and rescue operations and environmental surveys in the Arctic region. Based on Arctic marine sensor network mission goals, the team has designed the SDMSI to include features to rank images based on saliency and to provide on camera fusion and depth mapping. A major challenge has been the design of the camera computing system to operate within a 10 to 20 Watt power budget. This paper presents a power analysis of three options: 1) multi-core, 2) field programmable gate array with multi-core, and 3) graphics processing units with multi-core. For each test, power consumed for common fusion workloads has been measured at a range of frame rates and resolutions. Detailed analyses from our power efficiency comparison for workloads specific to stereo depth mapping and sensor fusion are summarized. Preliminary mission feasibility results from testing with off-the-shelf long-wave infrared and visible cameras in Alaska and Arizona are also summarized to demonstrate the value of the SDMSI for applications such as ice tracking, ocean color, soil moisture, animal and marine vessel detection and tracking. The goal is to select the most power efficient solution for the SDMSI for use on UAVs (Unoccupied Aerial Vehicles) and other drop


    Institute of Scientific and Technical Information of China (English)

    Zhang Yifan; He Mingyi


    Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspectral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR) method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.

  18. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

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


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

  20. Bandwidth Controllable Tunable Filter for Hyper-/Multi-Spectral Imager Project (United States)

    National Aeronautics and Space Administration — This SBIR Phase I proposal introduces a fast speed bandwidth controllable tunable filter for hyper-/multi-spectral (HS/MS) imagers. It dynamically passes a variable...

  1. Multi-Spectral imaging of vegetation for detecting CO2 leaking from underground

    Energy Technology Data Exchange (ETDEWEB)

    Rouse, J.H.; Shaw, J.A.; Lawrence, R.L.; Lewicki, J.L.; Dobeck, L.M.; Repasky, K.S.; Spangler, L.H.


    Practical geologic CO{sub 2} sequestration will require long-term monitoring for detection of possible leakage back into the atmosphere. One potential monitoring method is multi-spectral imaging of vegetation reflectance to detect leakage through CO{sub 2}-induced plant stress. A multi-spectral imaging system was used to simultaneously record green, red, and near-infrared (NIR) images with a real-time reflectance calibration from a 3-m tall platform, viewing vegetation near shallow subsurface CO{sub 2} releases during summers 2007 and 2008 at the Zero Emissions Research and Technology field site in Bozeman, Montana. Regression analysis of the band reflectances and the Normalized Difference Vegetation Index with time shows significant correlation with distance from the CO{sub 2} well, indicating the viability of this method to monitor for CO{sub 2} leakage. The 2007 data show rapid plant vigor degradation at high CO{sub 2} levels next to the well and slight nourishment at lower, but above-background CO{sub 2} concentrations. Results from the second year also show that the stress response of vegetation is strongly linked to the CO{sub 2} sink-source relationship and vegetation density. The data also show short-term effects of rain and hail. The real-time calibrated imaging system successfully obtained data in an autonomous mode during all sky and daytime illumination conditions.

  2. Multi-spectral image enhancement algorithm based on keeping original gray level (United States)

    Wang, Tian; Xu, Linli; Yang, Weiping


    Characteristics of multi-spectral imaging system and the image enhancement algorithm are introduced.Because histogram equalization and some other image enhancement will change the original gray level,a new image enhancement algorithm is proposed to maintain the gray level.For this paper, we have chosen 6 narrow-bands multi-spectral images to compare,the experimental results show that the proposed method is better than those histogram equalization and other algorithm to multi-spectral images.It also insures that histogram information contained in original features is preserved and guarantees to make use of data class information.What's more,on the combination of subjective and objective sharpness evaluation,details of the images are enhanced and noise is weaken.

  3. Multi-spectral light interaction modeling and imaging of skin lesions (United States)

    Patwardhan, Sachin Vidyanand

    Nevoscope as a diagnostic tool for melanoma was evaluated using a white light source with promising results. Information about the lesion depth and its structure will further improve the sensitivity and specificity of melanoma diagnosis. Wavelength-dependent variable penetration power of monochromatic light in the trans-illumination imaging using the Nevoscope can be used to obtain this information. Optimal selection of wavelengths for multi-spectral imaging requires light-tissue interaction modeling. For this, three-dimensional wavelength dependent voxel-based models of skin lesions with different depths are proposed. A Monte Carlo simulation algorithm (MCSVL) is developed in MATLAB and the tissue models are simulated using the Nevoscope optical geometry. 350--700nm optical wavelengths with an interval of 5nm are used in the study. A correlation analysis between the lesion depth and the diffuse reflectance is then used to obtain wavelengths that will produce diffuse reflectance suitable for imaging and give information related to the nevus depth and structure. Using the selected wavelengths, multi-spectral trans-illumination images of the skin lesions are collected and analyzed. An adaptive wavelet transform based tree-structure classification method (ADWAT) is proposed to classify epi-illuminance images of the skin lesions obtained using a white light source into melanoma and dysplastic nevus images classes. In this method, tree-structure models of melanoma and dysplastic nevus are developed and semantically compared with the tree-structure of the unknown image for classification. Development of the tree-structure is dependent on threshold selections obtained from a statistical analysis of the feature set. This makes the classification method adaptive. The true positive value obtained for this classifier is 90% with a false positive of 10%. The Extended ADWAT method and Fuzzy Membership Functions method using combined features from the epi-illuminance and multi-spectral

  4. Distant Determination of Bilirubin Distribution in Skin by Multi-Spectral Imaging (United States)

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


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

  5. Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images (United States)

    Awumah, Anna; Mahanti, Prasun; Robinson, Mark


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

  6. Interventional multi-spectral photoacoustic imaging in laparoscopic surgery (United States)

    Hill, Emma R.; Xia, Wenfeng; Nikitichev, Daniil I.; Gurusamy, Kurinchi; Beard, Paul C.; Hawkes, David J.; Davidson, Brian R.; Desjardins, Adrien E.


    Laparoscopic procedures can be an attractive treatment option for liver resection, with a shortened hospital stay and reduced morbidity compared to open surgery. One of the central challenges of this technique is visualisation of concealed structures within the liver, particularly the vasculature and tumourous tissue. As photoacoustic (PA) imaging can provide contrast for haemoglobin in real time, it may be well suited to guiding laparoscopic procedures in order to avoid inadvertent trauma to vascular structures. In this study, a clinical laparoscopic ultrasound probe was used to receive ultrasound for PA imaging and to obtain co-registered B-mode ultrasound (US) images. Pulsed excitation light was delivered to the tissue via a fibre bundle in dark-field mode. Monte Carlo simulations were performed to optimise the light delivery geometry for imaging targets at depths of 1 cm, 2 cm and 3 cm, and 3D-printed mounts were used to position the fibre bundle relative to the transducer according to the simulation results. The performance of the photoacoustic laparoscope system was evaluated with phantoms and tissue models. The clinical potential of hybrid PA/US imaging to improve the guidance of laparoscopic surgery is discussed.

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

    Directory of Open Access Journals (Sweden)

    Marc Wieland


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

  8. Multi-spectral image fusion method based on two channels non-separable wavelets

    Institute of Scientific and Technical Information of China (English)

    LIU Bin; PENG JiaXiong


    A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1, -1] and its application in the fusion of multi-spectral image are presented. Many 4x4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.

  9. Development and bench testing of a multi-spectral imaging technology built on a smartphone platform (United States)

    Bolton, Frank J.; Weiser, Reuven; Kass, Alex J.; Rose, Donny; Safir, Amit; Levitz, David


    Cervical cancer screening presents a great challenge for clinicians across the developing world. In many countries, cervical cancer screening is done by visualization with the naked eye. Simple brightfield white light imaging with photo documentation has been shown to make a significant impact on cervical cancer care. Adoption of smartphone based cervical imaging devices is increasing across Africa. However, advanced imaging technologies such as multispectral imaging systems, are seldom deployed in low resource settings, where they are needed most. To address this challenge, the optical system of a smartphone-based mobile colposcopy imaging system was refined, integrating components required for low cost, portable multi-spectral imaging of the cervix. This paper describes the refinement of the mobile colposcope to enable it to acquire images of the cervix at multiple illumination wavelengths, including modeling and laboratory testing. Wavelengths were selected to enable quantifying the main absorbers in tissue (oxyand deoxy-hemoglobin, and water), as well as scattering parameters that describe the size distribution of scatterers. The necessary hardware and software modifications are reviewed. Initial testing suggests the multi-spectral mobile device holds promise for use in low-resource settings.

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

    Energy Technology Data Exchange (ETDEWEB)

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


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

  11. Rapid mapping of digital integrated circuit logic gates via multi-spectral backside imaging

    CERN Document Server

    Adato, Ronen; Zangeneh, Mahmoud; Zhou, Boyou; Joshi, Ajay; Goldberg, Bennett; Unlu, M Selim


    Modern semiconductor integrated circuits are increasingly fabricated at untrusted third party foundries. There now exist myriad security threats of malicious tampering at the hardware level and hence a clear and pressing need for new tools that enable rapid, robust and low-cost validation of circuit layouts. Optical backside imaging offers an attractive platform, but its limited resolution and throughput cannot cope with the nanoscale sizes of modern circuitry and the need to image over a large area. We propose and demonstrate a multi-spectral imaging approach to overcome these obstacles by identifying key circuit elements on the basis of their spectral response. This obviates the need to directly image the nanoscale components that define them, thereby relaxing resolution and spatial sampling requirements by 1 and 2 - 4 orders of magnitude respectively. Our results directly address critical security needs in the integrated circuit supply chain and highlight the potential of spectroscopic techniques to addres...

  12. Multi-spectral texture analysis for IED detection (United States)

    Petersson, Henrik; Gustafsson, David


    The use of Improvised Explosive Devices (IEDs) has increased significantly over the world and is a globally widespread phenomenon. Although measures can be taken to anticipate and prevent the opponent's ability to deploy IEDs, detection of IEDs will always be a central activity. There is a wide range of different sensors that are useful but also simple means, such as a pair of binoculars, can be crucial to detect IEDs in time. Disturbed earth (disturbed soil), such as freshly dug areas, dumps of clay on top of smooth sand or depressions in the ground, could be an indication of a buried IED. This paper brie y describes how a field trial was set-up to provide a realistic data set on a road section containing areas with disturbed soil due to buried IEDs. The road section was imaged using a forward looking land-based sensor platform consisting of visual imaging sensors together with long-, mid-, and shortwave infrared imaging sensors. The paper investigates the presence of discriminatory information in surface texture comparing areas with disturbed against undisturbed soil. The investigation is conducted for the different wavelength bands available. To extract features that describe texture, image processing tools such as 'Histogram of Oriented Gradients', 'Local Binary Patterns', 'Lacunarity', 'Gabor Filtering' and 'Co-Occurence' is used. It is found that texture as characterized here may provide discriminatory information to detect disturbed soil, but the signatures we found are weak and can not be used alone in e.g. a detector system.

  13. Development of a technique based on multi-spectral imaging for monitoring the conservation of cultural heritage objects. (United States)

    Marengo, Emilio; Manfredi, Marcello; Zerbinati, Orfeo; Robotti, Elisa; Mazzucco, Eleonora; Gosetti, Fabio; Bearman, Greg; France, Fenella; Shor, Pnina


    A new approach for monitoring the state of conservation of cultural heritage objects surfaces is being developed. The technique utilizes multi-spectral imaging, multivariate analysis and statistical process control theory for the automatic detection of a possible deterioration process, its localization and identification, and the wavelengths most sensitive to detecting this before the human eye can detect the damage or potential degradation changes occur. A series of virtual degradation analyses were performed on images of parchment in order to test the proposed algorithm in controlled conditions. The spectral image of a Dead Sea Scroll (DSS) parchment, IAA (Israel Antiquities Authority) inventory plate # 279, 4Q501 Apocryphal Lamentations B, taken during the 2008 Pilot of the DSS Digitization Project, was chosen for the simulation.

  14. A method for comparison of growth media in objective identification of Penicillium based on multi-spectral imaging

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Hansen, Michael Adsetts Edberg; Frisvad, Jens Christian


    We consider the problems of using excessive growth media for identification and performing objective identification of fungi at the species level. We propose a method for choosing the subset of growth media, which provides the best discrimination between several fungal species. Furthermore, we pr...... to macro-morphological features. The species have been classified using only 3–4 of the spectral bands with a 100% correct classification rate using both leave-one-out cross-validation and test set validation....... propose the use of multi-spectral imaging as a means of objective identification. Three species of the fungal genus Penicillium are subject to classification. To obtain an objective classification we use multi-spectral images. Previously, RGB images have proven useful for the purpose. We use multi-spectral...

  15. Calibration for Relative Interior Orientation Relationship and Band-to-band Registration with High Accuracy of ZY-3 Multi-spectral Image

    Directory of Open Access Journals (Sweden)

    LI Qijun


    Full Text Available Using high accuracy match points extracted between the multi-spectral images that obtained at the same time,a position model of the CCD chips of the ZY-3 multi-spectral camera was proposed. Relative interior orientation relationship parameters were calculated and accurate band-to-band automatic registration of ZY-3 multi-spectral image was achieved based on the position model. The experimental result indicates that the band-to-band automatic registration accuracy of ZY-3 multi-spectral image is better than 0.3 pixels with the proposed method.

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

    Energy Technology Data Exchange (ETDEWEB)

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


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

  17. UAS-based soil carbon mapping using VIS-NIR (480–1000 nm) multi-spectral imaging: Potential and limitations

    DEFF Research Database (Denmark)

    Aldana Jague, Emilien; Heckrath, Goswin; Macdonald, Andy


    Traditional methods to assess the soil organic carbon (SOC) content based on soil sampling and analysis are time consuming and expensive, and the results are influenced by the sampling design. The aim of this study was to investigate the potential of UAS (Unmanned Aerial Systems) multi-spectral i......Traditional methods to assess the soil organic carbon (SOC) content based on soil sampling and analysis are time consuming and expensive, and the results are influenced by the sampling design. The aim of this study was to investigate the potential of UAS (Unmanned Aerial Systems) multi...... practices, provide a valuable resource to evaluate this approach. We acquired images (wavelength: 480–550–670–780–880–1000 nm) at an altitude of 120 m over an area of 2 ha using a multi-spectral camera mounted on an UAS. The high-resolution images captured smallscale variations at the soil surface (e...

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

    Energy Technology Data Exchange (ETDEWEB)

    Henderson, J R


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

  19. Investigation of Image Fusion Between High-Resolution Image and Multi-spectral Image

    Institute of Scientific and Technical Information of China (English)

    LI Pingxiang; WANG Zhijun


    On the basis of a thorough understanding of the physical characteristics of remote sensing image, this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm. The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China. The experimental results show that a perfect image fusion can be built up by using the image analytical solution and re-construction in the image frequency domain based on the physical characteristics of the image formation. The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.

  20. 基于多光谱成像技术的宫颈脱落细胞DNA定量分析研究%Study of Cervical Exfoliated Cell 's DNA Quantitative Analysis Based on Multi-Spectral Imaging Technology

    Institute of Scientific and Technical Information of China (English)

    吴正; 曾立波; 吴琼水


    The conventional cervical cancer screening methods mainly include TBS (the bethesda system ) classification method and cellular DNA quantitative analysis ,however ,by using multiple staining method in one cell slide ,which is staining the cyto-plasm with Papanicolaou reagent and the nucleus with Feulgen reagent ,the study of achieving both two methods in the cervical cancer screening at the same time is still blank .Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA ,so that this paper has set up a multi-spectral imaging system , and established an absorbance unmixing model by using multiple linear regression method based on absorbance 's linear superpo-sition character ,and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis ,and achieved the perfect combination of those two kinds of conventional screening method .Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1% ,also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells ,so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been veri-fied ,therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cer-vical cancer and other cancers .%常用的宫颈癌筛查方法有 TBS(the bethesda system)分类法和细胞DNA定量分析法两种 ,而同时利用多重染色方法在同一张细胞涂片上对细胞质进行巴氏染

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

    Directory of Open Access Journals (Sweden)

    Robert Eckardt


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

  2. The analysis of forest policy using Landsat multi-spectral scanner data and geographic information systems (United States)

    Peterson, D. L.; Brass, J. A.; Norman, S. D.; Tosta-Miller, N.


    The role of Landsat multi-spectral scanner (MSS) data for forest policy analysis in the state of California has been investigated. The combined requirements for physical, socio-economic, and institutional data in policy analysis were studied to explain potential data needs. A statewide MSS data and general land cover classification was created from which country-wide data sets could be extracted for detailed analyses. The potential to combine point sample data with MSS data was examined as a means to improve specificity in estimations. MSS data was incorporated into geographic information systems to demonstrate modeling techniques using abiotic, biotic, and socio-economic data layers. The review of system configurations to help the California Department of Forestry (CDF) acquire the capability demonstrated resulted in a sequence of options for implementation.

  3. Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI Data for Burned Area Discrimination

    Directory of Open Access Journals (Sweden)

    Haiyan Huang


    Full Text Available Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance and atmospherically corrected (surface reflectance images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence and non-parametric (decision tree approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms.

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

    DEFF Research Database (Denmark)

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


    sand types were examined with 20-60 images for each type. To reduce the amount of data, features were extracted from the multi-spectral images; the features were summary statistics on single bands and pairs of bands as well as morphological summaries. The number of features (2,016) is high in relation...... reduction (forward selection and principal components) combined with ordinary least squares and one sophisticated chemometrics algorithm (genetic algorithm-partial least squares) are compared to the recently proposed least angle regression-elastic net (LARS-EN) model selection method....

  5. Multi-resolution Analysis of Multi-spectral Palmprints using Hybrid Wavelets for Identification

    Directory of Open Access Journals (Sweden)

    Dr. H.B. Kekre


    Full Text Available Palmprint is a relatively new physiological biometric used in identification systems due to its stable and unique characteristics. The vivid texture information of palmprint present at different resolutions offers abundant prospects in personal recognition. This paper describes a new method to authenticate individuals based on palmprint identification. In order to analyze the texture information at various resolutions, we introduce a new hybrid wavelet, which is generated using two or more component transforms incorporating both their properties. A unique property of this wavelet is its flexibility to vary the number of components at each level of resolution and hence can be made suitable for various applications. Multi-spectral palmprints have been identified using energy compaction of the hybrid wavelet transform coefficients. The scores generated for each set of palmprint images under red, green and blue illuminations are combined using score-level fusion using AND and OR operators. Comparatively low values of equal error rate and high security index have been obtained for all fusion techniques. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

  6. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite (United States)

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


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

  7. Tokamak-independent software analysis suite for multi-spectral line-polarization MSE diagnostics (United States)

    Scott, S. D.; Mumgaard, R. T.


    A tokamak-independent analysis suite has been developed to process data from Motional Stark Effect (mse) diagnostics. The software supports multi-spectral line-polarization mse diagnostics which simultaneously measure emission at the mse σ and π lines as well as at two "background" wavelengths that are displaced from the mse spectrum by a few nanometers. This analysis accurately estimates the amplitude of partially polarized background light at the σ and π wavelengths even in situations where the background light changes rapidly in time and space, a distinct improvement over traditional "time-interpolation" background estimation. The signal amplitude at many frequencies is computed using a numerical-beat algorithm which allows the retardance of the mse photo-elastic modulators (pem's) to be monitored during routine operation. It also allows the use of summed intensities at multiple frequencies in the calculation of polarization direction, which increases the effective signal strength and reduces sensitivity to pem retardance drift. The software allows the polarization angles to be corrected for calibration drift using a system that illuminates the mse diagnostic with polarized light at four known polarization angles within ten seconds of a plasma discharge. The software suite is modular, parallelized, and portable to other facilities.

  8. Multimodal tissue perfusion imaging using multi-spectral and thermographic imaging systems applied on clinical data (United States)

    Klaessens, John H. G. M.; Nelisse, Martin; Verdaasdonk, Rudolf M.; Noordmans, Herke Jan


    Clinical interventions can cause changes in tissue perfusion, oxygenation or temperature. Real-time imaging of these phenomena could be useful for surgical strategy or understanding of physiological regulation mechanisms. Two noncontact imaging techniques were applied for imaging of large tissue areas: LED based multispectral imaging (MSI, 17 different wavelengths 370 nm-880 nm) and thermal imaging (7.5 to 13.5 μm). Oxygenation concentration changes were calculated using different analyzing methods. The advantages of these methods are presented for stationary and dynamic applications. Concentration calculations of chromophores in tissue require right choices of wavelengths The effects of different wavelength choices for hemoglobin concentration calculations were studied in laboratory conditions and consequently applied in clinical studies. Corrections for interferences during the clinical registrations (ambient light fluctuations, tissue movements) were performed. The wavelength dependency of the algorithms were studied and wavelength sets with the best results will be presented. The multispectral and thermal imaging systems were applied during clinical intervention studies: reperfusion of tissue flap transplantation (ENT), effectiveness of local anesthetic block and during open brain surgery in patients with epileptic seizures. The LED multispectral imaging system successfully imaged the perfusion and oxygenation changes during clinical interventions. The thermal images show local heat distributions over tissue areas as a result of changes in tissue perfusion. Multispectral imaging and thermal imaging provide complementary information and are promising techniques for real-time diagnostics of physiological processes in medicine.

  9. Ziyuan-3 Multi-Spectral and Panchromatic Images Fusion Quality Assessment: Applied to Jiangsu Coastal Area, China (United States)

    Wu, Ruijuan; He, Xiufeng


    A comprehensive fusion quality assessment was proposed, which based on cross entropy and structure similarity with weighted value, it was used to evaluate the fusion effort of Chinese Ziyuan-3 multi-spectral and panchromatic images from coastal areas, Jiangsu province, China. Fusion algorithms were used, Hue-Intensity-Saturation (HIS), àtrous Wavelet Transformation (AWT), NonsubSampled Contourlet Transform (NSCT), and combined NSCT with HIS. According to visual interpretation, the quality of fused imaged based on combined NSCT with HIS is better than another fusion methods, fusion quality results exploring our proposed image fusion quality assessment also illustrated that fused image of combined NSCT with HIS is the best, which is consistent with human- being subjective interpretation.

  10. Ziyuan-2 Multi-Spectral and Panchromatic Images Fusion Quality Assessment: Applied to Jiangsu Coastal Area, China (United States)

    Wu, Ruijuan; He, Xiufeng


    A comprehensive fusion quality assessment was proposed, which based on cross entropy and structure similarity with weighted value, it was used to evaluate the fusion effort of Chinese Ziyuan-3 multi-spectral and panchromatic images from coastal areas, Jiangsu province, China. Fusion algorithms were used, Hue-Intensity-Saturation (HIS), à trous Wavelet Transformation (AWT), Nonsub Sampled Contourlet Transform (NSCT), and combined NSCT with HIS. According to visual interpretation, the quality of fused imaged based on combined NSCT with HIS is better than another fusion methods, fusion quality results exploring our proposed image fusion quality assessment also illustrated that fused image of combined NSCT with HIS is the best, which is consistent with human-being subjective interpretation.

  11. Multi-spectral synthetic image generation for ground vehicle identification training (United States)

    May, Christopher M.; Pinto, Neil A.; Sanders, Jeffrey S.


    There is a ubiquitous and never ending need in the US armed forces for training materials that provide the warfighter with the skills needed to differentiate between friendly and enemy forces on the battlefield. The current state of the art in battlefield identification training is the Recognition of Combat Vehicles (ROC-V) tool created and maintained by the Communications - Electronics Research, Development and Engineering Center Night Vision and Electronic Sensors Directorate (CERDEC NVESD). The ROC-V training package utilizes measured visual and thermal imagery to train soldiers about the critical visual and thermal cues needed to accurately identify modern military vehicles and combatants. This paper presents an approach to augment the existing ROC-V imagery database with synthetically generated multi-spectral imagery that will allow NVESD to provide improved training imagery at significantly lower costs.


    Institute of Scientific and Technical Information of China (English)

    Lu Hao; Liu Tuanjie; Zhao Haiqing


    Band-to-band registration accuracy is an important parameter of multispectral data.A novel band-to-band registration approach with high precision is proposed for the multi-spectral images of HJ-1A/B.Firstly,the main causes resulted in misregistration are analyzed,and a high-order polynomial model is proposed.Secondly,a phase fringe filtering technique is employed to Phase Correlation Method based on Singular Value Decomposition (SVD-PCM) for reducing the noise in phase difference matrix.Then,experiments are carried out to build nonlinear registration models,and images of green band and red band are aligned to blue band with an accuracy of 0.1 pixels,while near infrared band with an accuracy of 0.2 pixels.

  13. Analysis of the relationship between the volumetric soil moisture content and the NDVI from high resolution multi-spectral images for definition of vineyard management zones to improve irrigation (United States)

    Martínez-Casasnovas, J. A.; Ramos, M. C.


    As suggested by previous research in the field of precision viticulture, intra-field yield variability is dependent on the variation of soil properties, and in particular the soil moisture content. Since the mapping in detail of this soil property for precision viticulture applications is highly costly, the objective of the present research is to analyse its relationship with the normalised difference vegetation index from high resolution satellite images to the use it in the definition of vineyard zonal management. The final aim is to improve irrigation in commercial vineyard blocks for better management of inputs and to deliver a more homogeneous fruit to the winery. The study was carried out in a vineyard block located in Raimat (NE Spain, Costers del Segre Designation of Origin). This is a semi-arid area with continental Mediterranean climate and a total annual precipitation between 300-400 mm. The vineyard block (4.5 ha) is planted with Syrah vines in a 3x2 m pattern. The vines are irrigated by means of drips under a partial root drying schedule. Initially, the irrigation sectors had a quadrangular distribution, with a size of about 1 ha each. Yield is highly variable within the block, presenting a coefficient of variation of 24.9%. For the measurement of the soil moisture content a regular sampling grid of 30 x 40 m was defined. This represents a sample density of 8 samples ha-1. At the nodes of the grid, TDR (Time Domain Reflectometer) probe tubes were permanently installed up to the 80 cm or up to reaching a contrasting layer. Multi-temporal measures were taken at different depths (each 20 cm) between November 2006 and December 2007. For each date, a map of the variability of the profile soil moisture content was interpolated by means of geostatistical analysis: from the measured values at the grid points the experimental variograms were computed and modelled and global block kriging (10 m squared blocks) undertaken with a grid spacing of 3 m x 3 m. On the

  14. Multi-spectral camera development

    CSIR Research Space (South Africa)

    Holloway, M


    Full Text Available stream_source_info Holloway_2012.pdf.txt stream_content_type text/plain stream_size 6209 Content-Encoding ISO-8859-1 stream_name Holloway_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Multi-Spectral Camera... Development 4th Biennial Conference Presented by Mark Holloway 10 October 2012 Fused image ? Red, Green and Blue Applications of the Multi-Spectral Camera ? CSIR 2012 Slide 2 Green and Blue, Near Infrared (IR) RED Applications of the Multi...

  15. Final Report on LDRD project 130784 : functional brain imaging by tunable multi-spectral Event-Related Optical Signal (EROS).

    Energy Technology Data Exchange (ETDEWEB)

    Speed, Ann Elizabeth; Spahn, Olga Blum; Hsu, Alan Yuan-Chun


    Functional brain imaging is of great interest for understanding correlations between specific cognitive processes and underlying neural activity. This understanding can provide the foundation for developing enhanced human-machine interfaces, decision aides, and enhanced cognition at the physiological level. The functional near infrared spectroscopy (fNIRS) based event-related optical signal (EROS) technique can provide direct, high-fidelity measures of temporal and spatial characteristics of neural networks underlying cognitive behavior. However, current EROS systems are hampered by poor signal-to-noise-ratio (SNR) and depth of measure, limiting areas of the brain and associated cognitive processes that can be investigated. We propose to investigate a flexible, tunable, multi-spectral fNIRS EROS system which will provide up to 10x greater SNR as well as improved spatial and temporal resolution through significant improvements in electronics, optoelectronics and optics, as well as contribute to the physiological foundation of higher-order cognitive processes and provide the technical foundation for miniaturized portable neuroimaging systems.

  16. Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra

    DEFF Research Database (Denmark)

    Peng, Yi; Xiong, Xiong; Adhikari, Kabindra


    results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l’Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain...

  17. Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra. (United States)

    Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog


    There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l'Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the 'upland model' was able to more accurately predict SOC compared with the 'upland & wetland model'. However, the separately calibrated 'upland and wetland model' did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis

  18. [Hard and soft classification method of multi-spectral remote sensing image based on adaptive thresholds]. (United States)

    Hu, Tan-Gao; Xu, Jun-Feng; Zhang, Deng-Rong; Wang, Jie; Zhang, Yu-Zhou


    Hard and soft classification techniques are the conventional methods of image classification for satellite data, but they have their own advantages and drawbacks. In order to obtain accurate classification results, we took advantages of both traditional hard classification methods (HCM) and soft classification models (SCM), and developed a new method called the hard and soft classification model (HSCM) based on adaptive threshold calculation. The authors tested the new method in land cover mapping applications. According to the results of confusion matrix, the overall accuracy of HCM, SCM, and HSCM is 71.06%, 67.86%, and 71.10%, respectively. And the kappa coefficient is 60.03%, 56.12%, and 60.07%, respectively. Therefore, the HSCM is better than HCM and SCM. Experimental results proved that the new method can obviously improve the land cover and land use classification accuracy.

  19. Inferential multi-spectral image compression based on distributed source coding (United States)

    Wu, Xian-yun; Li, Yun-song; Wu, Cheng-ke; Kong, Fan-qiang


    Based on the analyses of the interferential multispectral imagery(IMI), a new compression algorithm based on distributed source coding is proposed. There are apparent push motions between the IMI sequences, the relative shift between two images is detected by the block match algorithm at the encoder. Our algorithm estimates the rate of each bitplane with the estimated side information frame. then our algorithm adopts a ROI coding algorithm, in which the rate-distortion lifting procedure is carried out in rate allocation stage. Using our algorithm, the FBC can be removed from the traditional scheme. The compression algorithm developed in the paper can obtain up to 3dB's gain comparing with JPEG2000 and significantly reduce the complexity and storage consumption comparing with 3D-SPIHT at the cost of slight degrade in PSNR.

  20. Illumination estimation from specular highlight in a multi-spectral image. (United States)

    An, Dongsheng; Suo, Jinli; Wang, Haoqian; Dai, Qionghai


    The reflection spectrum of an object characterizes its surface material, but for non-Lambertian scenes, the recorded spectrum often deviates owing to specular contamination. To compensate for this deviation, the illumination spectrum is required, and it can be estimated from specularity. However, existing illumination-estimation methods often degenerate in challenging cases, especially when only weak specularity exists. By adopting the dichromatic reflection model, which formulates a specular-influenced image as a linear combination of diffuse and specular components, this paper explores two individual priors and one mutual prior upon these two components: (i) The chromaticity of a specular component is identical over all the pixels. (ii) The diffuse component of a specular-contaminated pixel can be reconstructed using its specular-free counterpart describing the same material. (iii) The spectrum of illumination usually has low correlation with that of diffuse reflection. A general optimization framework is proposed to estimate the illumination spectrum from the specular component robustly and accurately. The results of both simulation and real experiments demonstrate the robustness and accuracy of our method.

  1. Theoretical and Monte Carlo optimization of a stacked three-layer flat-panel x-ray imager for applications in multi-spectral diagnostic medical imaging (United States)

    Lopez Maurino, Sebastian; Badano, Aldo; Cunningham, Ian A.; Karim, Karim S.


    We propose a new design of a stacked three-layer flat-panel x-ray detector for dual-energy (DE) imaging. Each layer consists of its own scintillator of individual thickness and an underlying thin-film-transistor-based flat-panel. Three images are obtained simultaneously in the detector during the same x-ray exposure, thereby eliminating any motion artifacts. The detector operation is two-fold: a conventional radiography image can be obtained by combining all three layers' images, while a DE subtraction image can be obtained from the front and back layers' images, where the middle layer acts as a mid-filter that helps achieve spectral separation. We proceed to optimize the detector parameters for two sample imaging tasks that could particularly benefit from this new detector by obtaining the best possible signal to noise ratio per root entrance exposure using well-established theoretical models adapted to fit our new design. These results are compared to a conventional DE temporal subtraction detector and a single-shot DE subtraction detector with a copper mid-filter, both of which underwent the same theoretical optimization. The findings are then validated using advanced Monte Carlo simulations for all optimized detector setups. Given the performance expected from initial results and the recent decrease in price for digital x-ray detectors, the simplicity of the three-layer stacked imager approach appears promising to usher in a new generation of multi-spectral digital x-ray diagnostics.


    Directory of Open Access Journals (Sweden)

    G. Li


    Full Text Available HJ satellite is the abbreviation of the Small Satellite Constellation of Environment and Disaster Monitoring and Forecasting in China, which plays a very important role in forecasting and monitoring the environment problems and natural disasters. The ortho-rectification of HJ images aided by GCP (Ground Control Point image database is presented in this paper. The GCP image database is constructed from historical LandSat-TM images and the GCP chip consists of image and geographic attribute information. Then auto-searching and matching algorithm is introduced and mis-matching elimination method is presented. The imaging model based on collinearity equation and the polynomial description of the attitude and position of scanning line is utilized for ortho-rectification. Four scene images are experimented and compared, and the result demonstrated the feasibility and high efficiency of the whole work flow.

  3. Correlation Between the Evaluation of Pigmented Lesions by a Multi-spectral Digital Skin Lesion Analysis Device and the Clinical and Histological Features of Melanoma. (United States)

    Winkelmann, Richard R; Rigel, Darrell S; Ferris, Laura; Sober, Arthur; Tucker, Natalie; Cockerell, Clay J


    To correlate Multi-spectral Digital Skin Lesion Analysis classifier scores with histopathological severity of pigmented lesions and clinical features of melanoma. Classifier scores were computed for 1,632 skin lesions. Dermatologists evaluated the same lesions for Asymmetry, Border Irregularity, Color variegation, Diameter >6mm, Evolution, Patient's Concern, Regression, and/or "Ugly Duckling" sign. Classifier scores were correlated to the number of clinical risk features and for six histopathological severity levels of pigmented lesions. Average classifier score, Welch's t-test, and chi-square analysis. Melanomas had higher mean classifier scores (3.5) than high-grade dysplastic nevi (2.7, p=0.002), low-grade dysplastic nevi (1.7, pClassifier score and the number of clinical risk characteristics directly correlated (Pearson coefficient 0.32, pclassifier scores to clinical and histological melanoma features supports the effectiveness of Multi-spectral Digital Skin Lesion Analysis in assessing the risk of pigmented lesions requiring biopsy. Optimizing outcomes of dermatologist decisions to biopsy suspicious pigmented lesions may be enhanced utilizing Multi-spectral Digital Skin Lesion Analysis.

  4. Correlation Between the Evaluation of Pigmented Lesions by a Multi-spectral Digital Skin Lesion Analysis Device and the Clinical and Histological Features of Melanoma


    Winkelmann, Richard R.; Rigel, Darrell S.; Ferris, Laura; Sober, Arthur; Tucker, Natalie; Cockerell, Clay J.


    Objective: To correlate Multi-spectral Digital Skin Lesion Analysis classifier scores with histopathological severity of pigmented lesions and clinical features of melanoma. Design: Classifier scores were computed for 1,632 skin lesions. Dermatologists evaluated the same lesions for Asymmetry, Border Irregularity, Color variegation, Diameter >6mm, Evolution, Patient’s Concern, Regression, and/or “Ugly Duckling” sign. Classifier scores were correlated to the number of clinical risk features an...

  5. Multi-spectral photoacoustic elasticity tomography (United States)

    Liu, Yubin; Yuan, Zhen


    The goal of this work was to develop and validate a spectrally resolved photoacoustic imaging method, namely multi-spectral photoacoustic elasticity tomography (PAET) for quantifying the physiological parameters and elastic modulus of biological tissues. We theoretically and experimentally examined the PAET imaging method using simulations and in vitro experimental tests. Our simulation and in vitro experimental results indicated that the reconstructions were quantitatively accurate in terms of sizes, the physiological and elastic properties of the targets. PMID:27699101

  6. Online Multi-Spectral Meat Inspection

    DEFF Research Database (Denmark)

    Nielsen, Jannik Boll; Larsen, Anders Boesen Lindbo


    We perform an explorative study on multi-spectral image data from a prototype device developed for fast online quality inspection of meat products. Because the camera setup is built for speed, we sacrifice exact pixel correspondences between the different bands of the multi-spectral images. Our...... work is threefold as we 1) investigate the color distributions and construct a model to describe pork loins, 2) classify the different components in pork loins (meat, fat, membrane), and 3) detect foreign objects on the surface of pork loins. Our investigation shows that the color distributions can...... effectively be modeled using the Gaussian mixture model (GMM). For the classification task we build a classifier using a GMM. For detecting foreign objects, we construct a novelty detector using a GMM. We evaluate our method on a small dataset with mixed results. While we are able to provide reasonable...

  7. Image fusion algorithm of multi-spectral and panchromatic images adopting region mutual information%采用区域互信息的多光谱与全色图像融合算法

    Institute of Scientific and Technical Information of China (English)

    王金玲; 贺小军; 宋克非


    For advancing the fusion algorithm quality of multi-spectral and panchromatic images, an image fusion algorithm of multi-spectral and panchromatic images was presented by region mutual information. Firstly the multi-spectral image was turned to HSV color space, and region segmentation was applied to V component by the method of watershed and region combination, and spectral distance was taken as the region combination estimation. Secondly the V component of multi-spectral image and panchromatic image were decomposed multi-resolution by nonsubsample Contourlet transform(NSCT), the region segmentation was mapping to the panchromatic image, and the multi-resolution decomposition coefficient was fused by calculating the mutual information of corresponding region to obtain the decomposition coefficient of fusion image. Lastly the fusion image reconfiguration was realized through NSCT inverse transform. The experimental result shows that the image fusion algorithm presented by this paper retains the spectral information of multi-spectral image adequately, meanwhile injects details information of panchromatic image as much as possible, which advances the edge characteristic of multi-spectral image effectively.%为了提高多光谱与全色图像融合算法质量,提出了一种采用区域互信息的多光谱与全色图像融合算法。首先将多光谱图像变换至 HSV 彩色空间,并采用分水岭与区域合并的方法对 V 分量进行区域分割,得到区域分割映射,欧氏光谱距离作为区域合并的测度。然后采用非下采样 Contourlet变换(Nonsubsample Contourlet Transform,NSCT)对多光谱图像 V 分量和全色图像进行多分辨率分解,将区域分割结果映射至全色图像,通过计算对应区域间的互信息对多分辨率分解系数进行融合,获得融合图像的分解系数,最后通过 NSCT 反变换实现融合图像重构。图像融合算法对比实验表明,文中融合算法在充分保

  8. Enhanced multi-spectral imaging of live breast cancer cells using immunotargeted gold nanoshells and two-photon excitation microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Bickford, Lissett; Sun Jiantang; Fu, Kun; Lewinski, Nastassja; Nammalvar, Vengadesan; Chang, Joseph; Drezek, Rebekah [Department of Bioengineering, Rice University, Houston, TX 77005 (United States)], E-mail:


    We demonstrate the capability of using immunotargeted gold nanoshells as contrast agents for in vitro two-photon microscopy. The two-photon luminescence properties of different-sized gold nanoshells are first validated using near-infrared excitation at 780 nm. The utility of two-photon microscopy as a tool for imaging live HER2-overexpressing breast cancer cells labeled with anti-HER2-conjugated nanoshells is then explored and imaging results are compared to normal breast cells. Five different imaging channels are simultaneously examined within the emission wavelength range of 451-644 nm. Our results indicate that under near-infrared excitation, superior contrast of SK-BR-3 cancer cells labeled with immunotargeted nanoshells occurs at an emission wavelength ranging from 590 to 644 nm. Luminescence from labeled normal breast cells and autofluorescence from unlabeled cancer and normal cells remain imperceptible under the same conditions.

  9. Enhanced multi-spectral imaging of live breast cancer cells using immunotargeted gold nanoshells and two-photon excitation microscopy (United States)

    Bickford, Lissett; Sun, Jiantang; Fu, Kun; Lewinski, Nastassja; Nammalvar, Vengadesan; Chang, Joseph; Drezek, Rebekah


    We demonstrate the capability of using immunotargeted gold nanoshells as contrast agents for in vitro two-photon microscopy. The two-photon luminescence properties of different-sized gold nanoshells are first validated using near-infrared excitation at 780 nm. The utility of two-photon microscopy as a tool for imaging live HER2-overexpressing breast cancer cells labeled with anti-HER2-conjugated nanoshells is then explored and imaging results are compared to normal breast cells. Five different imaging channels are simultaneously examined within the emission wavelength range of 451-644 nm. Our results indicate that under near-infrared excitation, superior contrast of SK-BR-3 cancer cells labeled with immunotargeted nanoshells occurs at an emission wavelength ranging from 590 to 644 nm. Luminescence from labeled normal breast cells and autofluorescence from unlabeled cancer and normal cells remain imperceptible under the same conditions.

  10. Multi-spectral wide-field imaging for PplX PDT dosimetry of skin (Conference Presentation) (United States)

    LaRochelle, Ethan; Chun, Hayden H.; Hasan, Tayyaba; Pogue, Brian W.; Maytin, Edward V.; Chapman, Michael S.; Davis, Scott C.


    Actinic Kertoses (AK) are common pre-cancerous lesions associated with sun-damaged skin. While generally benign, the condition can progress to squamous cell carcinoma (SCC) and is a particular concern for immunosuppressed patients who are susceptible to uncontrolled AK and SCC. Among the FDA-approved treatment options for AK, ALA-based photodynamic therapy is unique in that it is non-scarring and can be repeated on the same area. However, response rates vary widely due to variations in drug and light delivery, PpIX production, and tissue oxygenation. Thus, developing modalities to predict response is critical to enable patient-specific treatment-enhancing interventions. To that end, we have developed a wide-field spectrally-resolved fluorescence imaging system capable of red and blue light excitation. While blue light excites PpIX efficiently, poor photon penetration limits the image content to superficial layers of skin. Red light excitation, on the other hand, can reveal fluorescence information originating from deeper in tissue, which may provide relevant information about PpIX distribution. Our instrument illuminates the skin via a fiber-based ring illuminator, into which is coupled sequentially a white light source, and blue and red laser diodes. Light emitted from the tissue passes through a high-speed filter wheel with filters selected to resolve the PpIX emission spectrum. This configuration enables the use of spectral fitting to decouple PpIX fluorescence from background signal, improving sensitivity to low concentrations of PpIX. Images of tissue-simulating phantoms and animal models confirm a linear response to PpIX, and the ability to image sub-surface PpIX inaccessible with blue light using red excitation.

  11. 3D coaxial out-of-plane metallic antennas for filtering and multi-spectral imaging in the infrared range. (United States)

    Jacassi, Andrea; Bozzola, Angelo; Zilio, Pierfrancesco; Tantussi, Francesco; De Angelis, Francesco


    We fabricated and investigated a new configuration of 3D coaxial metallic antennas working in the infrared which combines the strong lateral light scattering of vertical plasmonic structures with the selective spectral transmission of 2D arrays of coaxial apertures. The coaxial structures are fabricated with a top-down method based on a template of hollow 3D antennas. Each antenna has a multilayer radial structure consisting of dielectric and metallic materials not achievable in a 2D configuration. A planar metallic layer is inserted normally to the antennas. The outer dielectric shell of the antenna defines a nanometric gap between the horizontal plane and the vertical walls. Thanks to this aperture, light can tunnel to the other side of the plane, and be transmitted to the far field in a set of resonances. These are investigated with finite-elements electromagnetic calculations and with Fourier-transform infrared spectroscopy measurements. The spectral position of the resonances can be tuned by changing the lattice period and/or the antenna length. Thanks to the strong scattering provided by the 3D geometry, the transmission peaks possess a high signal-to-noise ratio even when the illuminated area is less than 2 × 2 times the operation wavelength. This opens new possibilities for multispectral imaging in the IR with wavelength-scale spatial resolution.

  12. An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI and Sentinel-2 Multi Spectral Instrument (MSI Imagery

    Directory of Open Access Journals (Sweden)

    Lin Yan


    Full Text Available Moderate spatial resolution satellite data from the Landsat-8 OLI and Sentinel-2A MSI sensors together offer 10 m to 30 m multi-spectral reflective wavelength global coverage, providing the opportunity for improved combined sensor mapping and monitoring of the Earth’s surface. However, the standard geolocated Landsat-8 OLI L1T and Sentinel-2A MSI L1C data products are currently found to be misaligned. An approach for automated registration of Landsat-8 OLI L1T and Sentinel-2A MSI L1C data is presented and demonstrated using contemporaneous sensor data. The approach is computationally efficient because it implements feature point detection across four image pyramid levels to identify a sparse set of tie-points. Area-based least squares matching around the feature points with mismatch detection across the image pyramid levels is undertaken to provide reliable tie-points. The approach was assessed by examination of extracted tie-point spatial distributions and tie-point mapping transformations (translation, affine and second order polynomial, dense-matching prediction-error assessment, and by visual registration assessment. Two test sites over Cape Town and Limpopo province in South Africa that contained cloud and shadows were selected. A Landsat-8 L1T image and two Sentinel-2A L1C images sensed 16 and 26 days later were registered (Cape Town to examine the robustness of the algorithm to surface, atmosphere and cloud changes, in addition to the registration of a Landsat-8 L1T and Sentinel-2A L1C image pair sensed 4 days apart (Limpopo province. The automatically extracted tie-points revealed sensor misregistration greater than one 30 m Landsat-8 pixel dimension for the two Cape Town image pairs, and greater than one 10 m Sentinel-2A pixel dimension for the Limpopo image pair. Transformation fitting assessments showed that the misregistration can be effectively characterized by an affine transformation. Hundreds of automatically located tie

  13. 结合高分辨率多光谱影像和LiDAR数据提取城区建筑%Building Extraction Using High Resolution Multi-spectral Image and LiDAR Data

    Institute of Scientific and Technical Information of China (English)

    谭衢霖; 王今飞


    结合IKONOS影像和LiDAR数据,应用面向对象分类分析方法试验提取高分辨率多光谱卫星影像城区建筑物.处理流程包括如下步骤:(1)影像融合增强;(2)影像分割;(3)影像对象分类;(4)建筑物对象几何形状规则化处理.试验结果表明,面向对象分类分析是一种适于利用高空间分辨率遥感影像数据进行城区建筑物制图的有效方法.该方法对于快速获取城区建筑物分布和辅助制订城区发展规划具有应用价值.%The object-oriented image analysis method was applied to building roof mapping using IKONOS multi-spectral images combined with LiDAR data. The scheme to generate the building vector polygons includes the following steps: (1) image fusion and derivation of ancillary input data; ( 2) segmentation of processed data layers into image objects; ( 3) classification of image objects; (4) geometrical regularization of classified building object polygons. The experimental results show that object-oriented classification analysis is an effective method for urban building mapping using very high-resolution remote sensing images. The procedure may suit overall investigation of urban building distribution and development.

  14. Theoretical design and material growth of Type-II Antimonide-based superlattices for multi-spectral infrared detection and imaging (United States)

    Hoang, Anh Minh

    led to the possibility of incorporating this channel to the multi-spectral detection. By combining with the MWIR channel, dual-band SWIR-MWIR photodiodes and focal plane arrays have been demonstrated, giving the capability of delivering both active and passive imaging in one single camera. Dual-band SWIR-MWIR photodiodes with quantum efficiency more than 50% for each channel has been achieved. Just like visible imaging, besides the available dual-band detection, the prospect of incorporating the third infrared waveband detection is very promising for a wide range of applications. However, the challenges for making such devices are so many that little success has been achieved. In the work, we also propose a new approach in device design to realize bias-selectable three-color shortwave-midwave-longwave infrared photodetector based on InAs/GaSb/AlSb type-II superlattice. The effect of conduction band off-set and different doping levels between two absorption layers are employed to control the turn-on voltage for individual channels. For the first time, we demonstrate experimentally Type-II superlattice based three-color photodiodes without using additional terminal contacts. As the applied bias voltage varies, the photodiodes exhibit sequentially the behavior of three different colors, corresponding to the bandgap of three absorbers. Well defined cut-offs and high quantum efficiency in each channel are achieved. While retaining the simplicity in device fabrication, this demonstration opens the new prospect for three-color infrared imaging. Finally, for further improvement, we are looking toward new type-II material called InAs/InAsSb superlattices. Theoretical design and growth techniques have been developed to investigate the properties of this material. We successfully demonstrated the design and growth of MWIR to VLWIR photodiodes based on Type-II InAs/InAsSb with high performance. Given the fact that these two Type-II material systems share the same GaSb substrate

  15. Identification method of multi-feature weed based on multi-spectral images and data mining%基于多光谱图像和数据挖掘的多特征杂草识别方法

    Institute of Scientific and Technical Information of China (English)

    赵川源; 何东健; 乔永亮


      为满足变量喷洒对杂草识别正确率的要求,提出一种基于多光谱图像和数据挖掘的杂草多特征识别方法.首先对多光谱成像仪获取的玉米与杂草图像从 CIR 转换到 Lab 颜色空间,用 K-means 聚类算法将图像分为土壤和绿色植物,随后用形态学处理提取出植物叶片图像,在此基础上提取叶片形状、纹理及分形维数3类特征,并基于 C4.5算法对杂草分别进行单特征和多特征组合的分类识别.试验结果表明,多特征识别率比单特征识别率高,3类特征组合后的识别率最高达到96.3%.为验证该文提出方法的有效性,将 C4.5算法与 BP 算法以及 SVM 算法进行比较,试验结果表明 C4.5算法的平均识别率高于另2种算法,该文提出的田间杂草快速识别方法是有效可行的.该文为玉米苗期精确喷洒除草剂提供技术依据.%Field weed detection is one of the key problems in realizing the variable precision applying pesticide to take place of the herbicide. Image-based weed classification and spectral information of plants are useful to detect weeds in real-time using multi-spectral features. Aimed to meet the identification accuracy requirements of variable spraying on weed, a new method using decision tree algorithm-C4.5 of data mining was developed to discriminate or classify crop and weeds by the multi-spectral images. The multi-spectral images of weeds and maize were captured by MS4100 Duncan Camera in the test field of Northwest Agriculture and Forestry University on May, 2012, and transformed from CIR color space to Lab systems, which can distinguish different quantized color and measure the Euclidean distance of different colors. Then vegetation was segmented from soil using K-means clustering algorithm. Mathematical morphology was used to fill small holes among the extracted vegetation leaves, and connect the uncompleted contour line of the discontinuous edges which may be caused by noise

  16. Wide-Band Multi-spectral Space for Color Representation

    Institute of Scientific and Technical Information of China (English)

    KONG Lingwang; ZHU Yuanhong; Kurt Muenger; ZHANG Xuliang


    This paper develops a wide-band multi-spectral space for color representation with Aitken PCA algorithm. This novel mathematical space using the broad-band spectra matching method aims at improving the accuracy of color representation as well as reducing costs for processing and storing multi-spectral images. The results show that the space can present our experimental original spectral spaces (i. e. Munsell color matt and DIN-6164 color chips) with high efficiency, and that the spanning space with three eigenvectors can present the original space at more than 98%CSCR, and when 5 eigenvectors are used it can cover almost the whole original spaces.

  17. Investigating the fracture non-linear dynamics through multi-spectral time series analysis of fracture-induced electromagnetic emissions (United States)

    Kalimeris, Anastasios; Potirakis, Stelios M.; Eftaxias, Konstantinos; Antonopoulos, George; Kopanas, John; Nomicos, Constantinos


    Electromagnetic (EM) emissions (EME) in a wide frequency spectrum ranging from kHz to MHz are produced by cracks' opening, considered as fracture precursors. Thus, their study constitutes a nondestructive method for the monitoring of the evolution of damage process at the laboratory scale. Earthquakes (EQs) are large-scale fracture phenomena in the Earth's heterogeneous crust. Accordingly, it has been suggested that fracture induced MHz-kHz EME, emerging from a few days up to a few hours before the main seismic shock permit a monitoring of the damage process during the last stages of EQ preparation. The use of spectral decomposition techniques, namely Singular Spectral Analysis (SSA), Wavelets Analysis (WA) and their Monte Carlo counterparts (MC SSA and MC WA), as well as the revised Multi-Taper Method (MTM) for a reliable discrimination of fracto-EM emissions from the natural geo-EM field is proposed here; the well documented fracture-induced kHz EME time-series associated with the Athens' EQ (M=5.9, 7 September 1999) is employed as a test case. An adequately long time period (> month) prior to the occurrence of the EQ is considered in order to include all different phases of a large-scale fracture, from the "quite" period where only the geo-EM field and its modulation by the ionospheric variations is observed, to the final stages of the EQ preparation process where fracto-EM emissions occur. The examined time series, recorded at the 10 kHz band and at a high temporal resolution (sampling frequency 1 Hz), is first split into three characteristic excerpts (a) the quiet period well (35 to 25 days) before the event, (b) the first epoch of the candidate pre-seismically active time period (8 to 4 days before the event), and (c) the final epoch of the candidate pre-seismically active time period (~3 days before the event until short after the event). The Maximum Entropy and Blackman-Tukey FFT methods are initially used for the preliminary evaluation of the time

  18. Detection of ZY-3 Satellite Platform Jitter Using Multi-spectral Imagery

    Directory of Open Access Journals (Sweden)

    ZHU Ying


    Full Text Available Satellite platform jitter is one of the factors that affect the quality of high resolution imagery, which can cause image blur and internal distortion. Taking ZiYuan-3 (ZY-3 multi-spectral camera as a prototype, this paper proposes a satellite platform jitter detection method by utilizing multi-spectral imagery. First, imaging characteristics of multispectral camera and the main factors affecting band-to-band registration error are introduced. Then the regularity of registration error caused by platform jitter is analyzed by theoretical derivation and simulation. Meanwhile, the platform jitter detection method based on high accuracy dense points matching is presented. Finally, the experiments were conducted by using ZY-3 multi-spectral imagery captured in different time. The result indicates that ZY-3 has a periodic platform jitter about 0.6 Hz in the imaging period of test data, and the jitter amplitude across track is greater than that along track, which causes periodic band-to-band registration error with the same frequency. The result shows the possibility of the improvement in geometric processing accuracy for ZY-3 imagery products and provides an important reference for satellite platform jitter source analysis and satellite platform design optimization.

  19. Multi-Spectral Imaging from an Unmanned Aerial Vehicle Enables the Assessment of Seasonal Leaf Area Dynamics of Sorghum Breeding Lines. (United States)

    Potgieter, Andries B; George-Jaeggli, Barbara; Chapman, Scott C; Laws, Kenneth; Suárez Cadavid, Luz A; Wixted, Jemima; Watson, James; Eldridge, Mark; Jordan, David R; Hammer, Graeme L


    Genetic improvement in sorghum breeding programs requires the assessment of adaptation traits in small-plot breeding trials across multiple environments. Many of these phenotypic assessments are made by manual measurement or visual scoring, both of which are time consuming and expensive. This limits trial size and the potential for genetic gain. In addition, these methods are typically restricted to point estimates of particular traits, such as leaf senescence or flowering and do not capture the dynamic nature of crop growth. In water-limited environments in particular, information on leaf area development over time would provide valuable insight into water use and adaptation to water scarcity during specific phenological stages of crop development. Current methods to estimate plant leaf area index (LAI) involve destructive sampling and are not practical in breeding. Unmanned aerial vehicles (UAV) and proximal-sensing technologies open new opportunities to assess these traits multiple times in large small-plot trials. We analyzed vegetation-specific crop indices obtained from a narrowband multi-spectral camera on board a UAV platform flown over a small pilot trial with 30 plots (10 genotypes randomized within 3 blocks). Due to variable emergence we were able to assess the utility of these vegetation indices to estimate canopy cover and LAI over a large range of plant densities. We found good correlations between the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) with plant number per plot, canopy cover and LAI both during the vegetative growth phase (pre-anthesis) and at maximum canopy cover shortly after anthesis. We also analyzed the utility of time-sequence data to assess the senescence pattern of sorghum genotypes known as fast (senescent) or slow senescing (stay-green) types. The Normalized Difference Red Edge (NDRE) index which estimates leaf chlorophyll content was most useful in characterizing the leaf area dynamics

  20. Multi-spectral remote sensing image true color synthesis technique based on artificial target%基于人工靶标的多光谱遥感图像真彩色合成

    Institute of Scientific and Technical Information of China (English)

    黄红莲; 易维宁; 杜丽丽; 崔文煜; 曾献芳


    Multi-spectral true color synthesized images have the prospects of broad application in the interpretation of remote sensing image, target recognition and information processing etc. The technique of true color synthesis depends on the accuracy of the obtained tristimulus values CIE-XYZ, which is used to establish the right relationship between the system of camera′s RGB and human being′s visual color. So, a method of true color image synthesis based on the information of artificial target was proposed by laying the man-made targets when the satellite passes. And, the transformation matrix between camera′s RGB trichromatic system and human being′s visual color system was estimated from the reflectance spectrum of man-made targets. Eventually, the suitable true color correction model was established in the certain atmospheric conditions. Experiment of true color correction was conducted on the multi-spectral images of GF-1 satellite, and the results show that good color correction effects has been exhibited on even every image with different degrees of color′s richness.%多光谱真彩色合成图像在遥感图像解译判读、 目标识别和信息处理等领域具有广阔的应用前景.真彩色合成技术取决于获得准确的X、Y、Z三刺激值,以建立相机RGB三基色体系与人眼视觉颜色体系之间的关系.为此,提出了基于彩色目标光谱信息的多光谱图像真彩色合成方法,通过在卫星过顶时铺设人工靶标,利用实测的靶标反射率光谱,计算相机三基色体系RGB与人眼视觉颜色体系CIE-XYZ之间的转换矩阵,构建适用于一定大气条件下的真彩色校正模型.利用高分一号卫星多光谱图像进行真彩色校正实验的结果表明,该方法对色彩丰富度不同的图像均具有较好的颜色校正效果.

  1. 大脑组织多参数磁共振影像分割方法研究%The research on tissue segmentation for brain multi-spectral MR image

    Institute of Scientific and Technical Information of China (English)

    周晓东; 包尚联; 李德军


    Segmentation for brain tissue becomes more and more important in clinical diagnosis and treatment for dis-eases as well as for basic research such as for virtual human subjects. In this paper, pattern recognition methods wereused to perform the segmentation for Multi-Spectral MR images. The k Nearest Neighbor (kNN) and the Fuzzy NearestPrototype (FNP) algorithms[1]were adopted. Combination of the consideration on the feature of MR image and the anatomicknowledge, a set of neighborhood rules were established. Generally, kNN and FNP algorithms classify the samples intheir state space, ignoring the information between pixels in the image. The neighborhood rules were added to deter-mine the uncertain results after state space classification. The result from the segmentation was obviously better thenthat from previous kNN or FNP algorithm.%对大脑组织的影像分割,在人脑疾病的诊断和治疗以及人脑的功能研究中有着越来越重要的作用.本文应用最近邻算法(kNN)和模糊最近原型(FNP)算法对Multi-Spectral MR图像进行分割.综合考虑MR图像的特征和解剖学的知识,我们发展了一套邻域规则,用来弥补kNN算法和FNP算法的各自的不足,加快了计算的速度.通常的分类分析只在状态空间,而没有考虑到图像中像素之间的相邻信息,而正是这些由生物学特征决定的相邻信息,可以作为状态空间分类之后,用邻域规则对通常分类中不确定的像素进行进一步分类的依据.通过这样的这步过程,有效地降低了分类的错误,得到的分割结果明显好于文献中单独使用kNN和FNP算法得到的结果.

  2. Multi-spectral pyrometry—a review (United States)

    Araújo, António


    In pyrometry measurements, the unknown target emissivity is a critical source of uncertainty, especially when the emissivity is low. Aiming to overcome this problem, various multi-spectral pyrometry systems and processing techniques have been proposed in the literature. Basically, all multi-spectral systems are based on the same principle: the radiation emitted by the target is measured at different channels having different spectral characteristics, and the emissivity is modelled as a function of wavelength with adjustable parameters to be obtained empirically, resulting in a system of equations whose solution is the target temperature and the parameters of the emissivity function. The present work reviews the most important multi-spectral developments. Concerning the spectral width of the measurement channels, multi-spectral systems are divided into multi-wavelength (monochromatic channels) and multi-band (wide-band channels) systems. Regarding the number of unknowns and equations (one equation per channel), pyrometry systems can either be determined (same number of unknowns and equations, having a unique solution) or overdetermined (more equations than unknowns, to be solved by least-squares). Generally, higher-order multi-spectral systems are overdetermined, since the uncertainty of the solutions obtained from determined systems increases as the number of channels increases, so that determined systems normally have less than four channels. In terms of the spectral characteristics of the measurement channels, narrow bands, far apart from each other and shifted towards lower wavelengths, seem to provide more accurate solutions. Many processing techniques have been proposed, but they strongly rely on the relationship between emissivity and wavelength, which is, in turn, strongly dependent on the characteristics of a particular target. Several accurate temperature and/or emissivity results have been reported, but no universally accepted multi-spectral technique has

  3. Maximizing the Economic Benefits of a Multi-Spectral Mission (United States)

    Kamoun, P.; Martimort, Ph.

    Several multi-spectral Space missions have been proposed worldwide to meet the requirements of various applications with hopes of substantial return on investment. However experience has shown that up till today, with very few exceptions, most have not reached expectations and several multi-spectral projects are even staying only at the prospective stage. In this paper the results of a thorough analysis of the requirements of several key thematic domains will be presented ( in particular vegetation monitoring, geology, oceanography, urbanism, ... ). This analysis will be followed by the identification of optimum system specifications to establish a commercially viable system. A description of the technical characteristcs of the optimum system in terms of mission, satellite, platform, instrument and ground segment will then be given. Finally a treatment of the business case will be shown and its economic benefits will be qualitatively and quantitatively indicated. The relationship between such a program and its counterparts worldwide will be explored to identify redundancies or synergies.

  4. An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling. (United States)

    Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady


    Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: Copyright © 2017 Elsevier Ltd. All rights

  5. In-vivo multi-spectral confocal microscopy (United States)

    Rouse, Andrew R.; Udovich, Joshua A.; Gmitro, Arthur F.


    A multi-spectral confocal microendoscope (MCME) for in-vivo imaging has been developed. The MCME employs a flexible fiber-optic catheter coupled to a slit-scan confocal microscope with an imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The focus mechanism allows for imaging to a maximum tissue depth of 200 microns. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3 micron lateral resolution and 30 micron axial resolution. The system incorporates two laser sources and is therefore capable of simultaneous acquisition of spectra from multiple dyes using dual excitation. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 8nm to 16nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersion characteristics of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. In-vitro, and ex-vivo multi-spectral results are presented.

  6. Improved global high resolution precipitation estimation using multi-satellite multi-spectral information (United States)

    Behrangi, Ali

    from Remotely Sensed Information using Artificial Neural Network -- Multi-Spectral Analysis (PERSIANN-MSA) the effectiveness of using multi-spectral data for precipitation estimation are examined. In comparison to the use of a single thermal infrared channel, using multi-spectral data has a potential to significantly improve rain detection and estimation skills; (3) a method proposed to integrate the previously developed cloud classification system (PERSIANNCCS) with PERSIANN-MSA. Through the integration, PERSIANN-MSA benefits from both cloud-patch classification capability as well as multi-spectral information to culminate the GEO-based precipitation estimation techniques; (4) finally, a new combination technique that incorporates multi-sensor information is developed. The technique is called REFAME, short for Rain Estimation using Forward Adjustedadvection of Microwave Estimates. REFAME allows more consistent integration of MWVIS/ IR information through hybrid advection and adjustment of MW precipitation rate along cloud motion streamlines obtained from a 2D cloud tracking algorithm using successive GEO/IR images. Evaluated over a range of spatial and temporal scales it is demonstrated that REFAME is a robust technique for real-time high resolution precipitation estimation using multi-satellite information.

  7. 基于小波支持向量回归的遥感多光谱图像分辨率增强算法%Resolution Enhance Algorithm for Remote Sensing Multi-spectral Image Based on Wavelet Support Vector Regression

    Institute of Scientific and Technical Information of China (English)

    胡根生; 张为; 梁栋


    利用小波支持向量回归,实现了遥感多光谱图像分辨率的增强。首先采用非下采样Contourlet变换对低分辨率的多光谱图像和高分辨率的全色图像进行多分辨率分解,再利用小波支持向量回归对分解系数进行学习和预测,获得分辨率初步提高的多光谱图像,最后再与传统的插值方法得到的结果进行融合来实现多光谱图像分辨率增强。实验结果表明:此方法借遥感全色图像的辅助获得丰富的高频细节信息,使得分辨率增强结果无论是最小均方误差还是峰值信噪比都要优于仅依靠原图像本身放大的传统方法以及其他的分辨率增强方法。%Wavelet support vector regression is utilized to enhance the resolution for remote sensing multi-spectral image. Firstly, both low resolution multi-spectral image and high resolution panchromatic image are decomposed into multi-resolution by using nonsubsampled contourlet transform. Then, by using wavelet support vector regression, the decomposed coefficients are learned and predicted so as to obtain multi-spectral image with preliminary enhanced resolution. Finally, the above results are further fused with the traditional interpolate one to achieve the resolution enhance of multi-spectral image. Experiment results show that the proposed algorithm utilizes the auxiliary o{ remote sensing panchromatic image to effectively attain a wealth of high-frequency detail information, such that either the minimum mean squared error or the peak signal to noise ratio is superior to these from the traditional methods only depending on the amplification of image itself and other resolution enhance methods.

  8. Optimization of spectral indices and long-term separability analysis for classification of cereal crops using multi-spectral RapidEye imagery (United States)

    Gerstmann, Henning; Möller, Markus; Gläßer, Cornelia


    Crop monitoring using remotely sensed image data provides valuable input for a large variety of applications in environmental and agricultural research. However, method development for discrimination between spectrally highly similar crop species remains a challenge in remote sensing. Calculation of vegetation indices is a frequently applied option to amplify the most distinctive parts of a spectrum. Since no vegetation index exist, that is universally best-performing, a method is presented that finds an index that is optimized for the classification of a specific satellite data set to separate two cereal crop types. The η2 (eta-squared) measure of association - presented as novel spectral separability indicator - was used for the evaluation of the numerous tested indices. The approach is first applied on a RapidEye satellite image for the separation of winter wheat and winter barley in a Central German test site. The determined optimized index allows a more accurate classification (97%) than several well-established vegetation indices like NDVI and EVI (covering the years 2010-2014. The optimized index for the spectral separation of winter barley and winter wheat for each acquisition date was calculated and its ability to distinct the two classes was assessed. The results indicate that the calculated optimized indices perform better than the standard indices for most seasonal parts of the time series. The red edge spectral region proved to be of high significance for crop classification. Additionally, a time frame of best spectral separability of wheat and barley could be detected in early to mid-summer.

  9. Laser- and Multi-Spectral Monitoring of Natural Objects from UAVs (United States)

    Reiterer, Alexander; Frey, Simon; Koch, Barbara; Stemmler, Simon; Weinacker, Holger; Hoffmann, Annemarie; Weiler, Markus; Hergarten, Stefan


    The paper describes the research, development and evaluation of a lightweight sensor system for UAVs. The system is composed of three main components: (1) a laser scanning module, (2) a multi-spectral camera system, and (3) a processing/storage unit. All three components are newly developed. Beside measurement precision and frequency, the low weight has been one of the challenging tasks. The current system has a total weight of about 2.5 kg and is designed as a self-contained unit (incl. storage and battery units). The main features of the system are: laser-based multi-echo 3D measurement by a wavelength of 905 nm (totally eye save), measurement range up to 200 m, measurement frequency of 40 kHz, scanning frequency of 16 Hz, relative distance accuracy of 10 mm. The system is equipped with both GNSS and IMU. Alternatively, a multi-visual-odometry system has been integrated to estimate the trajectory of the UAV by image features (based on this system a calculation of 3D-coordinates without GNSS is possible). The integrated multi-spectral camera system is based on conventional CMOS-image-chips equipped with a special sets of band-pass interference filters with a full width half maximum (FWHM) of 50 nm. Good results for calculating the normalized difference vegetation index (NDVI) and the wide dynamic range vegetation index (WDRVI) have been achieved using the band-pass interference filter-set with a FWHM of 50 nm and an exposure times between 5.000 μs and 7.000 μs. The system is currently used for monitoring of natural objects and surfaces, like forest, as well as for geo-risk analysis (landslides). By measuring 3D-geometric and multi-spectral information a reliable monitoring and interpretation of the data-set is possible. The paper gives an overview about the development steps, the system, the evaluation and first results.

  10. Natural Resource Assessments in Afghanistan Through High Resolution Digital Elevation Modeling and Multi-spectral Image Analysis (United States)

    Chirico, Peter G.


    This viewgraph presentation provides USGS/USAID natural resource assessments in Afghanistan through the mapping of coal, oil and natural gas, minerals, hydrologic resources and earthquake and flood hazards.

  11. A Better Method for SAR Image and Multi-Spectral Image Fusion Based on Nonsubsampled Contourlet Transform (NSCT) and Genetic Algorithm%基于NSCT和遗传算法的SAR图像和多光谱图像融合

    Institute of Scientific and Technical Information of China (English)

    时丕丽; 郭雷; 李晖晖; 杨宁; 陈智慧


    SAR image or multispectral image has big difference in imaging mechanism and spectral characteristics. Sections 1 and 2 of the full paper explain our image fusion method mentioned in the title, which we believe is new and better than previous ones. Their cpre consists of : (1) by using the multi-scale, multi-direction ad spare decomposition capability of the NSCT, we transform the SAR and multispectral source images into NSCT domain; (2) we fuse the low frequencey coefficients by maximizing the regional entropy; then we calculate the values of the high-frequence subband regional correlation coefficients, divide them into different ranges according to the threshold values selected by genetic algorithm and fuse the correlation coefficients in different ranges, ( 3) we take the inverse NSCT transform, thus obtatining the fused images. Section 3 simulates our image fusion method; the simulation results , given in Fig. 4 and Table 1, and their analysis show preliminarily that our image fusion method performs indeed much better than the exsiting regional-based/pixel-based Contourlet/NSCT.%合成孔径雷达(SAR)图像与多光谱图像成像机理和光谱特性差异较大,一般的融合方法很难取得满意的融合结果.文章提出了一种基于Nonsuosampled Contourlet transform(NSCT)和遗传算法的融合算法,首先将经过预处理后的图像进行NSCT分解,低频系数采取区域信息熵最大的准则融合;高频子带计算区域相关性,对相关性在不同阈值范围内的系数进行融合,阈值的选取采用遗传算法进行搜索;最后对融合系数进行NSCT逆变换,得到融合结果.仿真结果表明该算法显著优于基于像素点和基于区域的融合方法.

  12. FUNSTAT and statistical image representations (United States)

    Parzen, E.


    General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

  13. DASC: Robust Dense Descriptor for Multi-Modal and Multi-Spectral Correspondence Estimation. (United States)

    Kim, Seungryong; Min, Dongbo; Ham, Bumsub; Do, Minh N; Sohn, Kwanghoon


    Establishing dense correspondences between multiple images is a fundamental task in many applications. However, finding a reliable correspondence between multi-modal or multi-spectral images still remains unsolved due to their challenging photometric and geometric variations. In this paper, we propose a novel dense descriptor, called dense adaptive self-correlation (DASC), to estimate dense multi-modal and multi-spectral correspondences. Based on an observation that self-similarity existing within images is robust to imaging modality variations, we define the descriptor with a series of an adaptive self-correlation similarity measure between patches sampled by a randomized receptive field pooling, in which a sampling pattern is obtained using a discriminative learning. The computational redundancy of dense descriptors is dramatically reduced by applying fast edge-aware filtering. Furthermore, in order to address geometric variations including scale and rotation, we propose a geometry-invariant DASC (GI-DASC) descriptor that effectively leverages the DASC through a superpixel-based representation. For a quantitative evaluation of the GI-DASC, we build a novel multi-modal benchmark as varying photometric and geometric conditions. Experimental results demonstrate the outstanding performance of the DASC and GI-DASC in many cases of dense multi-modal and multi-spectral correspondences.

  14. Binocular depth acuity research to support the modular multi-spectral stereoscopic night vision goggle (United States)

    Merritt, John O.; CuQlock-Knopp, V. Grayson; Paicopolis, Peter; Smoot, Jennifer; Kregel, Mark; Corona, Bernard


    This paper discusses the depth acuity research conducted in support of the development of a Modular Multi-Spectral Stereoscopic (M2S2) night vision goggle (NVG), a customizable goggle that lets the user select one of five goggle configurations: monocular thermal, monocular image intensifier (I2), binocular I2, binocular thermal, and binocular dual-waveband (thermal imagery to one eye and I2 imagery to the other eye). The motives for the development of this type of customizable goggle were (1) the need for an NVG that allows the simultaneous use of two wavebands, (2) the need for an alternative sensor fusion method to avoid the potential image degradation that may accompany digitally fused images, (3) a requirement to provide the observer with stereoscopic, dual spectrum views of a scene, and (4) the need to handle individual user preferences for sensor types and ocular configurations employed in various military operations. Among the increases in functionality that the user will have with this system is the ability to convert from a binocular I2 device (needed for detailed terrain analysis during off-road mobility) to a monocular thermal device (for increased situational awareness in the unaided eye during nights with full moon illumination). Results of the present research revealed potential depth acuity advantages that may apply to off-road terrain hazard detection for the binocular thermal configuration. The results also indicated that additional studies are needed to address ways to minimize binocular incompatibility for the dual waveband configuration.

  15. Exploiting physical constraints for multi-spectral exo-planet detection (United States)

    Thiébaut, Éric; Devaney, Nicholas; Langlois, Maud; Hanley, Kenneth


    We derive a physical model of the on-axis PSF for a high contrast imaging system such as GPI or SPHERE. This model is based on a multi-spectral Taylor series expansion of the diffraction pattern and predicts that the speckles should be a combination of spatial modes with deterministic chromatic magnification and weighting. We propose to remove most of the residuals by fitting this model on a set of images at multiple wavelengths and times. On simulated data, we demonstrate that our approach achieves very good speckle suppression without additional heuristic parameters. The residual speckles1, 2 set the most serious limitation in the detection of exo-planets in high contrast coronographic images provided by instruments such as SPHERE3 at the VLT, GPI4, 5 at Gemini, or SCExAO6 at Subaru. A number of post-processing methods have been proposed to remove as much as possible of the residual speckles while preserving the signal from the planets. These methods exploit the fact that the speckles and the planetary signal have different temporal and spectral behaviors. Some methods like LOCI7 are based on angular differential imaging8 (ADI), spectral differential imaging9, 10 (SDI), or on a combination of ADI and SDI.11 Instead of working on image differences, we propose to tackle the exo-planet detection as an inverse problem where a model of the residual speckles is fit on the set of multi-spectral images and, possibly, multiple exposures. In order to reduce the number of degrees of freedom, we impose specific constraints on the spatio-spectral distribution of stellar speckles. These constraints are deduced from a multi-spectral Taylor series expansion of the diffraction pattern for an on-axis source which implies that the speckles are a combination of spatial modes with deterministic chromatic magnification and weighting. Using simulated data, the efficiency of speckle removal by fitting the proposed multi-spectral model is compared to the result of using an approximation

  16. Deep multi-spectral ensemble learning for electronic cleansing in dual-energy CT colonography (United States)

    Tachibana, Rie; Näppi, Janne J.; Hironaka, Toru; Kim, Se Hyung; Yoshida, Hiroyuki


    We developed a novel electronic cleansing (EC) method for dual-energy CT colonography (DE-CTC) based on an ensemble deep convolution neural network (DCNN) and multi-spectral multi-slice image patches. In the method, an ensemble DCNN is used to classify each voxel of a DE-CTC image volume into five classes: luminal air, soft tissue, tagged fecal materials, and partial-volume boundaries between air and tagging and those between soft tissue and tagging. Each DCNN acts as a voxel classifier, where an input image patch centered at the voxel is generated as input to the DCNNs. An image patch has three channels that are mapped from a region-of-interest containing the image plane of the voxel and the two adjacent image planes. Six different types of spectral input image datasets were derived using two dual-energy CT images, two virtual monochromatic images, and two material images. An ensemble DCNN was constructed by use of a meta-classifier that combines the output of multiple DCNNs, each of which was trained with a different type of multi-spectral image patches. The electronically cleansed CTC images were calculated by removal of regions classified as other than soft tissue, followed by a colon surface reconstruction. For pilot evaluation, 359 volumes of interest (VOIs) representing sources of subtraction artifacts observed in current EC schemes were sampled from 30 clinical CTC cases. Preliminary results showed that the ensemble DCNN can yield high accuracy in labeling of the VOIs, indicating that deep learning of multi-spectral EC with multi-slice imaging could accurately remove residual fecal materials from CTC images without generating major EC artifacts.

  17. Comparison on fusion algorithms of ZY-3 panchromatic and multi-spectral images%ZY-3卫星全色与多光谱影像融合方法比较

    Institute of Scientific and Technical Information of China (English)

    李霖; 佘梦媛; 罗恒


    ZY-3 (Ziyuan-3) satellite is China's first civil high resolution mapping satellite that can provide services for precision agriculture in our country in real-time and steadily. Based on ZY-3 satellite panchromatic images with 2.1 m spatial resolution and multispectral images with 5.8 m resolution data, the methods of image enhancement on ZY-3 agricultural land data were analyzed, taking agricultural land in the Caidian district of Wuhan, Hubei province as an example. The study used different fusion methods such as HSV transformation, Brovey transformation, Gram-Schmidt spectral sharpening, PC spectral sharpening, Wavelet transformation, and Ehlers transformation, all of which are frequently used. For assessing the performance and effect of these fusion methods, the image quality of the fused image was evaluated by qualitative and quantitative analysis. Qualitative analysis relied on visual contrast. To improve the spatial resolution and keep the original image spectrum information of fusion images, two kinds of statistical aspects: grey scale statistics and texture characteristics of different areas, were analyzed quantificationally. Grey scale statistics included correlation index and spectral angle index. Texture characteristics included entropy index, second moment index, and edge response index. In order to better determine the fusion image’s texture features, three block areas of which the spatial structure’s complexity was different from each other, such as building area, farmland, and water, were chosen to analyze their entropy and second moment indexes. Furthermore, through the object-oriented classification method, fusion images were classified into six classes to evaluate the performance of the fusion method at the information level. The six classes included water, arable land, woodland, buildings, bare land, and unclassified. In order to further verify the accuracy of classification, the study used the same methods and parameters to analyze other

  18. Adaptive on-line classification of multi-spectral scanner data (United States)

    Fromm, F. R.; Northouse, R. A.


    A possible solution to the analysis of the massive amounts of multi-spectral scanner data from the Earth Resource Technical Satellite (ERTS) program is proposed. This solution is offered as an adaptive on-line classification scheme. The classifier is described as well as its controller which is based on ground truth data. Cluster analysis is presented as an alternative approach to the ground truth data. Adaptive feature selection is discussed and possible mini-computer implementations are offered.

  19. Airborne Multi-Spectral Minefield Survey (United States)


    Swedish Defence Research Agency), GEOSPACE (Austria), GTD ( Ingenieria de Sistemas y Software Industrial, Spain), IMEC (Ineruniversity MicroElectronic...Quality Control . An important methodological aspect of the selected approach is the pyramidal information structure, which is reflected in the use of...the image interpreter to manually assign ground control points. After AGM processing for each individual image the results are stored in GEOTIFF file

  20. Calibration of the Multi-Spectral Solar Telescope Array multilayer mirrors and XUV filters (United States)

    Allen, Maxwell J.; Willis, Thomas D.; Kankelborg, Charles C.; O'Neal, Ray H.; Martinez-Galarce, Dennis S.; Deforest, Craig E.; Jackson, Lisa; Lindblom, Joakim; Walker, Arthur B. C., Jr.; Barbee, Troy W., Jr.


    The Multi-Spectral Solar Telescope Array (MSSTA), a rocket-borne solar observatory, was successfully flown in May, 1991, obtaining solar images in eight XUV and FUV bands with 12 compact multilayer telescopes. Extensive measurements have recently been carried out on the multilayer telescopes and thin film filters at the Stanford Synchrotron Radiation Laboratory. These measurements are the first high spectral resolution calibrations of the MSSTA instruments. Previous measurements and/or calculations of telescope throughputs have been confirmed with greater accuracy. Results are presented on Mo/Si multilayer bandpass changes with time and experimental potassium bromide and tellurium filters.

  1. Evaluation of the response and healing effect after laser hair removal using a multi-spectral dermatoscope (United States)

    Noordmans, Herke Jan; Kuijer, Ellen; de Groot, Ilva; de Roode, Rowland; Rem, Alex; de Boorder, Tjeerd; Verdaasdonk, Rudolf


    A multi-spectral dermatoscope was used to investigate the effect of laser hair removal. Ten volunteers underwent three laser treatments, 6 weeks apart. In a subsequent trial, three volunteers received one laser treatment after which the skin region was imaged at short intervals. Practical solutions were developed to re-locate the investigated skin area. After exact matching using rigid and elastic registration software, the images showed acute and delayed effects on the hairs, pigment and vasculature after laser hair removal and subsequent healing response. The multi-spectral dermatoscope provides a perfect tool to study the efficacy and side effects of laser hair removal procedures and can be used to optimize the treatment plan.

  2. MOOSE: A Multi-Spectral Observatory Of Sensitive EMCCDs for innovative research in space physics and aeronomy (United States)

    Samara, M.; Michell, R. G.; Hampton, D. L.; Trondsen, T.


    The Multi-Spectral Observatory Of Sensitive EMCCDs (MOOSE) consists of 5 imaging systems and is the result of an NSF-funded Major Research Instrumentation project. The main objective of MOOSE is to provide a resource to all members of the scientific community that have interests in imaging low-light-level phenomena, such as aurora, airglow, and meteors. Each imager consists of an Andor DU-888 Electron Multiplying CCD (EMCCD), combined with a telecentric optics section, made by Keo Scientific Ltd., with a selection of available angular fields of view. During the northern hemisphere winter the system is typically based and operated at Poker Flat Research Range in Alaska, but any or all imagers can be shipped anywhere in individual stand-alone cases. We will discuss the main components of the MOOSE project, including the imagers, optics, lenses and filters, as well as the Linux-based control software that enables remote operation. We will also discuss the calibration of the imagers along with the initial deployments and testing done. We are requesting community input regarding operational modes, such as filter and field of view combinations, frame rates, and potentially moving some imagers to other locations, either for tomography or for larger spatial coverage. In addition, given the large volume of auroral image data already available, we are encouraging collaborations for which we will freely distribute the data and any analysis tools already developed. Most significantly, initial science highlights relating to aurora, airglow and meteors will be discussed in the context of the creative and innovative ways that the MOOSE observatory can be used in order to address a new realm of science topics, previously unachievable with traditional single imager systems.

  3. Image Analysis

    DEFF Research Database (Denmark)

    The 19th Scandinavian Conference on Image Analysis was held at the IT University of Copenhagen in Denmark during June 15-17, 2015. The SCIA conference series has been an ongoing biannual event for more than 30 years and over the years it has nurtured a world-class regional research and development....... The topics of the accepted papers range from novel applications of vision systems, pattern recognition, machine learning, feature extraction, segmentation, 3D vision, to medical and biomedical image analysis. The papers originate from all the Scandinavian countries and several other European countries...

  4. Applications of multi-spectral imaging: failsafe industrial flame detector (United States)

    Wing Au, Kwong; Larsen, Christopher; Cole, Barry; Venkatesha, Sharath


    Industrial and petrochemical facilities present unique challenges for fire protection and safety. Typical scenarios include detection of an unintended fire in a scene, wherein the scene also includes a flare stack in the background. Maintaining a high level of process and plant safety is a critical concern. In this paper, we present a failsafe industrial flame detector which has significant performance benefits compared to current flame detectors. The design involves use of microbolometer in the MWIR and LWIR spectrum and a dual band filter. This novel flame detector can help industrial facilities to meet their plant safety and critical infrastructure protection requirements while ensuring operational and business readiness at project start-up.

  5. The fabrication of a multi-spectral lens array and its application in assisting color blindness (United States)

    Di, Si; Jin, Jian; Tang, Guanrong; Chen, Xianshuai; Du, Ruxu


    This article presents a compact multi-spectral lens array and describes its application in assisting color-blindness. The lens array consists of 9 microlens, and each microlens is coated with a different color filter. Thus, it can capture different light bands, including red, orange, yellow, green, cyan, blue, violet, near-infrared, and the entire visible band. First, the fabrication process is described in detail. Second, an imaging system is setup and a color blindness testing card is selected as the sample. By the system, the vision results of normal people and color blindness can be captured simultaneously. Based on the imaging results, it is possible to be used for helping color-blindness to recover normal vision.

  6. Retrieval Using Texture Features in High Resolution Multi-spectral Satellite Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Newsam, S D; Kamath, C


    Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region types. Much of the work done thus far has focused on panchromatic imagery at low to moderate spatial resolutions, such as images from Landsat 1-7 which have a resolution of 15-30 m/pixel, and from SPOT 1-5 which have a resolution of 2.5-20 m/pixel. However, it is not clear which texture representation works best for the new classes of high resolution panchromatic (60-100 cm/pixel) and multi-spectral (4 bands for red, green, blue, and near infra-red at 2.4-4 m/pixel) imagery. It is also not clear how the different spectral bands should be combined. In this paper, we investigate the retrieval performance of several different texture representations using multi-spectral satellite images from IKONOS. A query-by-example framework, along with a manually chosen ground truth dataset, allows different combinations of texture representations and spectral bands to be compared. We focus on the specific problem of retrieving inhabited regions from images of urban and rural scenes. Preliminary results show that (1) the use of all spectral bands improves the retrieval performance, and (2) co-occurrence, wavelet and Gabor texture features perform comparably.

  7. [Vegetation water content retrieval and application of drought monitoring using multi-spectral remote sensing]. (United States)

    Wang, Li-Tao; Wang, Shi-Xin; Zhou, Yi; Liu, Wen-Liang; Wang, Fu-Tao


    The vegetation is one of main drying carriers. The change of Vegetation Water Content (VWC) reflects the spatial-temporal distribution of drought situation and the degree of drought. In the present paper, a method of retrieving the VWC based on remote sensing data is introduced and analyzed, including the monitoring theory, vegetation water content indicator and retrieving model. The application was carried out in the region of Southwest China in the spring, 2010. The VWC data was calculated from MODIS data and spatially-temporally analyzed. Combined with the meteorological data from weather stations, the relationship between the EWT and weather data shows that precipitation has impact on the change in vegetation moisture to a certain extent. However, there is a process of delay during the course of vegetation absorbing water. So precipitation has a delaying impact on VWC. Based on the above analysis, the probability of drought monitoring and evaluation based on multi-spectral VWC data was discussed. Through temporal synthesis and combined with auxiliary data (i. e. historical data), it will help overcome the limitation of data itself and enhance the application of drought monitoring and evaluation based on the multi-spectral remote sensing.

  8. The source of multi spectral energy of solar energetic electron

    Energy Technology Data Exchange (ETDEWEB)

    Herdiwijaya, Dhani [Astronomy Division and Bosscha Observatory, Faculty Mathematics and Natural Sciences, Intitute Technology of Bandung, Ganesha 10, Bandung, Indonesia 40132 (Indonesia)


    We study the solar energetic electron distribution obtained from ACE and GOES satellites which have different altitudes and electron spectral energy during the year 1997 to 2011. The electron spectral energies were 0.038–0.315 MeV from EPAM instrument onboard ACE satellite and >2 MeV from GOES satellite. We found that the low electron energy has no correlation with high energy. In spite of we have corrected to the altitude differences. It implied that they originated from time dependent events with different sources and physical processes at the solar atmosphere. The sources of multi spectral energetic electron were related to flare and CME phenomena. However, we also found that high energetic electron comes from coronal hole.

  9. Production of High-Resolution Remote Sensing Images for Navigation Information Infrastructures

    Institute of Scientific and Technical Information of China (English)

    WANG Zhijun; Djemel Ziou; Costas Armenakis


    This paper introduces the image fusion approach of multi-resolution analysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral images from high-resolution panchromatic image and low-resolution multi-spectral images for navigation information infrastructure. The mathematical model of image fusion is derived according to the principle of remote sensing image formation. It shows that the pixel values of a high-resolution multi-spectral images are determined by the pixel values of the approximation of a high-resolution panchromatic image at the resolution level of low-resolution multi-spectral images, and in the pixel valae computation the M-band wavelet theory and the à trous algorithm are then used. In order to evaluate the MRAIM approach, an experiment has been carried out on the basis of the IKONOS 1 m panchromatic image and 4 m multi-spectral images. The result demonstrates that MRAIM image fusion approach gives promising fusion results and it can be used to produce the high-resolution remote sensing images required for navigation information infrastructures.

  10. Correction of multi-spectral MRI intensity non-uniformity via spatially regularized feature condensing (United States)

    Vovk, Uros; Pernus, Franjo; Likar, Bostjan


    In MRI, image intensity non-uniformity is an adverse phenomenon that increases inter-tissue overlapping. The aim of this study was to provide a novel general framework, named regularized feature condensing (RFC), for condensing the distribution of image features and apply it to correct intensity non-uniformity via spatial regularization. The proposed RCF method is an iterative procedure, which consists of four basic steps. First, creation of a feature space, which consists of multi-spectral image intensities and corresponding second derivatives. Second, estimation of the intensity condensing map in feature space, i.e. the estimation of the increase of feature probability densities by a well-established mean shift procedure. Third, regularization of intensity condensing map in image space, which yields the estimation of intensity non-uniformity. Fourth, applying the estimation of non-uniformity correction to the input image. In this way, the intensity distributions of distinct tissues are gradually condensed via spatial regularization. The method was tested on simulated and real MR brain images for which gold standard segmentations were available. The results showed that the method did not induce additional intensity variations in simulated uniform images and efficiently removed intensity non-uniformity in real MR brain images. The proposed RCF method is a powerful fully automated intensity non-uniformity correction method that makes no a prior assumptions on the image intensity distribution and provides non-parametric non-uniformity correction.

  11. On-Line Change Monitoring with Transformed Multi-Spectral Time Series, a Study Case in Tropical Forest (United States)

    Lu, Meng; Hamunyela, Eliakim


    In recent years, the methods for detecting structural changes in time series have been adapted for forest disturbance monitoring using satellite data. The BFAST (Breaks For Additive Season and Trend) Monitor framework, which detects forest cover disturbances from satellite image time series based on empirical fluctuation tests, is particularly used for near real-time deforestation monitoring, and it has been shown to be robust in detecting forest disturbances. Typically, a vegetation index that is transformed from spectral bands into feature space (e.g. normalised difference vegetation index (NDVI)) is used as input for BFAST Monitor. However, using a vegetation index for deforestation monitoring is a major limitation because it is difficult to separate deforestation from multiple seasonality effects, noise, and other forest disturbance. In this study, we address such limitation by exploiting the multi-spectral band of satellite data. To demonstrate our approach, we carried out a case study in a deciduous tropical forest in Bolivia, South America. We reduce the dimensionality from spectral bands, space and time with projective methods particularly the Principal Component Analysis (PCA), resulting in a new index that is more suitable for change monitoring. Our results show significantly improved temporal delay in deforestation detection. With our approach, we achieved a median temporal lag of 6 observations, which was significantly shorter than the temporal lags from conventional approaches (14 to 21 observations).

  12. 基于选权迭代估计与非监督分类的多光谱图像变化检测%Change detection of multi-spectral images based on iterative estimation with weight selection and unsupervised classification

    Institute of Scientific and Technical Information of China (English)

    李莎; 倪维平; 严卫东; 吴俊政; 张晗


    针对多光谱图像的变化检测问题,提出了一种基于选权迭代估计( iterative estimation with weight selection, IEWS)与非监督分类( unsupervised classification,UC)的多光谱图像变化检测方法。借鉴IEWS的思想,并以类似于迭代加权多元变化检测( iteratively reweighted multivariate alteration detection,IRMAD)的迭代模式进行回归估计,得到初步的变化检测结果;并通过对初始变化信息的UC处理,以及对不同类别的IEWS,得到最终的变化检测结果。利用该方法对TM图像进行了实验,结果表明:所得到的变化信息在空间位置上同该区域相应时间段内土地利用/覆盖的变化情况具有很好的一致性;同时与多元变化检测及IRMAD方法变化检测的结果相比较,表明该方法对相对较小的变化信息具有更好的变化检测能力。%To solve the change detection problem of multi-channel remote sensing images, this paper proposes a method based on iterative estimation with weight selection ( IEWS) and unsupervised classification ( UC) . Firstly, the primary change information is obtained according to the concept of IEWS, and the iteration scheme of the estimation is also similar to that of the iteratively re -weighted multivariate alteration detection ( IRMAD ) . And then, the primary change information is classified by the UC and processed by the IEWS, which can get the eventual change information. The experimental results with multi-spectral data indicate that the method proposed in this paper is effective. By using this method, the spatial coherence between the change information and the change of land use/cover in this area is good. As for the detection of change in small regions, the method is especially obviouely better than the commonly-used methods of multivariate alteration detection ( MAD) and IR-MAD.

  13. GPU-Based Volume Rendering of Noisy Multi-Spectral Astronomical Data

    CERN Document Server

    Hassan, Amr H; Barnes, David G


    Traditional analysis techniques may not be sufficient for astronomers to make the best use of the data sets that current and future instruments, such as the Square Kilometre Array and its Pathfinders, will produce. By utilizing the incredible pattern-recognition ability of the human mind, scientific visualization provides an excellent opportunity for astronomers to gain valuable new insight and understanding of their data, particularly when used interactively in 3D. The goal of our work is to establish the feasibility of a real-time 3D monitoring system for data going into the Australian SKA Pathfinder archive. Based on CUDA, an increasingly popular development tool, our work utilizes the massively parallel architecture of modern graphics processing units (GPUs) to provide astronomers with an interactive 3D volume rendering for multi-spectral data sets. Unlike other approaches, we are targeting real time interactive visualization of datasets larger than GPU memory while giving special attention to data with l...

  14. Multi-spectral optical absorption in substrate-free nanowire arrays

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Junpeng; Chia, Andrew; Boulanger, Jonathan; LaPierre, Ray, E-mail: [Department of Engineering Physics, McMaster University, 1280 Main St. West, Hamilton, Ontario L8S 4L7 (Canada); Dhindsa, Navneet; Khodadad, Iman; Saini, Simarjeet [Department of Electrical and Computer Engineering, University of Waterloo, 200 University Ave West, Waterloo, Ontario N2L 3G1 (Canada); Waterloo Institute of Nanotechnology, University of Waterloo, 200 University Ave West, Waterloo, Ontario N2L 3G1 (Canada)


    A method is presented of fabricating gallium arsenide (GaAs) nanowire arrays of controlled diameter and period by reactive ion etching of a GaAs substrate containing an indium gallium arsenide (InGaP) etch stop layer, allowing the precise nanowire length to be controlled. The substrate is subsequently removed by selective etching, using the same InGaP etch stop layer, to create a substrate-free GaAs nanowire array. The optical absorptance of the nanowire array was then directly measured without absorption from a substrate. We directly observe absorptance spectra that can be tuned by the nanowire diameter, as explained with rigorous coupled wave analysis. These results illustrate strong optical absorption suitable for nanowire-based solar cells and multi-spectral absorption for wavelength discriminating photodetectors. The solar-weighted absorptance above the bandgap of GaAs was 94% for a nanowire surface coverage of only 15%.

  15. Frequency position modulation using multi-spectral projections (United States)

    Goodman, Joel; Bertoncini, Crystal; Moore, Michael; Nousain, Bryan; Cowart, Gregory


    In this paper we present an approach to harness multi-spectral projections (MSPs) to carefully shape and locate tones in the spectrum, enabling a new and robust modulation in which a signal's discrete frequency support is used to represent symbols. This method, called Frequency Position Modulation (FPM), is an innovative extension to MT-FSK and OFDM and can be non-uniformly spread over many GHz of instantaneous bandwidth (IBW), resulting in a communications system that is difficult to intercept and jam. The FPM symbols are recovered using adaptive projections that in part employ an analog polynomial nonlinearity paired with an analog-to-digital converter (ADC) sampling at a rate at that is only a fraction of the IBW of the signal. MSPs also facilitate using commercial of-the-shelf (COTS) ADCs with uniform-sampling, standing in sharp contrast to random linear projections by random sampling, which requires a full Nyquist rate sample-and-hold. Our novel communication system concept provides an order of magnitude improvement in processing gain over conventional LPI/LPD communications (e.g., FH- or DS-CDMA) and facilitates the ability to operate in interference laden environments where conventional compressed sensing receivers would fail. We quantitatively analyze the bit error rate (BER) and processing gain (PG) for a maximum likelihood based FPM demodulator and demonstrate its performance in interference laden conditions.

  16. Development of multi-spectral three-dimensional micro particle tracking velocimetry (United States)

    Tien, Wei-Hsin


    The color-coded 3D micro particle tracking velocimetry system (CC3DμPTV) is a volumetric velocimetry technique that uses the defocusing digital particle image velocimetry (DDPIV) approach to reconstruct the 3D location of the particle. It is suited for microscopic flow visualization because of the single camera configuration. However, several factors limit the performance of the system. In this study, the limitation of the CC3DμPTV is discussed in detail and a new concept of a multi-camera 3D μ-PTV system is proposed to improve the performance of the original CC3DμPTV system. The system utilizes two dichroic beam splitters to separate the incoming light into 3 spectral ranges, and image with three monochrome image sensors. The use of a color-matched light source, off-center individual pinhole and monochrome image sensors allow the system to achieve better sensitivity and optical resolution. The use of coherent lasers light sources with high-speed cameras improves the velocity measurement dynamic range. The performance of the proposed multi-spectral system is first evaluated with a simulation model based on the finite element method (FEM). The performance is also compared numerically with the CC3DμPTV system. The test results show significant improvements on the signal to noise ratio and optical resolution. Originally presented in 11th International Symposium on Particle Image Velocimetry, Santa Barbara, California, September 14-16, 2015.

  17. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python. (United States)

    Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri


    In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

  18. Spatiotemporal coherent control of light through a multiply scattering medium with the Multi-Spectral Transmission Matri

    CERN Document Server

    Mounaix, Mickael; Defienne, Hugo; Volpe, Giorgio; Katz, Ori; Grésillon, Samuel; Gigan, Sylvain


    We report broadband characterization of the propagation of light through a multiply scattering medium by means of its Multi-Spectral Transmission Matrix. Using a single spatial light modulator, our approach enables the full control of both spatial and spectral properties of an ultrashort pulse transmitted through the medium. We demonstrate spatiotemporal focusing of the pulse at any arbitrary position and time with any desired spectral shape. Our approach opens new perspectives for fundamental studies of light-matter interaction in disordered media, and has potential applications in sensing, coherent control and imaging.

  19. Multiple directed graph large-class multi-spectral processor (United States)

    Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki


    Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.

  20. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python

    Directory of Open Access Journals (Sweden)

    Nicolas eRey-Villamizar


    Full Text Available In this article, we describe use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis task, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral brain tissue images surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels, 6,000$times$10,000$times$500 voxels with 16 bits/voxel, implying image sizes exceeding 250GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analytics for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment consisting. Our Python script enables efficient data storage and movement between compute and storage servers, logging all processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

  1. Spinal imaging and image analysis

    CERN Document Server

    Yao, Jianhua


    This book is instrumental to building a bridge between scientists and clinicians in the field of spine imaging by introducing state-of-the-art computational methods in the context of clinical applications.  Spine imaging via computed tomography, magnetic resonance imaging, and other radiologic imaging modalities, is essential for noninvasively visualizing and assessing spinal pathology. Computational methods support and enhance the physician’s ability to utilize these imaging techniques for diagnosis, non-invasive treatment, and intervention in clinical practice. Chapters cover a broad range of topics encompassing radiological imaging modalities, clinical imaging applications for common spine diseases, image processing, computer-aided diagnosis, quantitative analysis, data reconstruction and visualization, statistical modeling, image-guided spine intervention, and robotic surgery. This volume serves a broad audience as  contributions were written by both clinicians and researchers, which reflects the inte...

  2. Skin condition measurement by using multispectral imaging system (Conference Presentation) (United States)

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


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

  3. Retinal imaging and image analysis

    NARCIS (Netherlands)

    Abramoff, M.D.; Garvin, Mona K.; Sonka, Milan


    Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindne

  4. A Cost Effective Multi-Spectral Scanner for Natural Gas Detection

    Energy Technology Data Exchange (ETDEWEB)

    Yudaya Sivathanu; Jongmook Lim; Vinoo Narayanan; Seonghyeon Park


    The objective of this project is to design, fabricate and demonstrate a cost effective, multi-spectral scanner for natural gas leak detection in transmission and distribution pipelines. During the first year of the project, a laboratory version of the multi-spectral scanner was designed, fabricated, and tested at EnUrga Inc. The multi-spectral scanner was also evaluated using a blind Department of Energy study at the Rocky Mountain Oilfield Testing Center. The performance of the scanner was inconsistent during the blind study. However, most of the leaks were outside the view of the multi-spectral scanner that was developed during the first year of the project. Therefore, a definite evaluation of the capability of the scanner was not obtained. Despite the results, sufficient number of plumes was detected fully confirming the feasibility of the multi-spectral scanner. During the second year, the optical design of the scanner was changed to improve the sensitivity of the system. Laboratory tests show that the system can reliably detect small leaks (20 SCFH) at 30 to 50 feet. A prototype scanner was built and evaluated during the second year of the project. Only laboratory evaluations were completed during the second year. The laboratory evaluations show the feasibility of using the scanner to determine natural gas pipeline leaks. Further field evaluations and optimization of the scanner are required before commercialization of the scanner can be initiated.

  5. Visir-Sat - a Prospective Micro-Satellite Based Multi-Spectral Thermal Mission for Land Applications (United States)

    Ruecker, G.; Menz, G.; Heinemann, S.; Hartmann, M.; Oertel, D.


    Current space-borne thermal infrared satellite systems aimed at land surface remote sensing retain some significant deficiencies, in particular in terms of spatial resolution, spectral coverage, number of imaging bands and temperature-emissivity separation. The proposed VISible-to-thermal IR micro-SATellite (VISIR-SAT) mission addresses many of these limitations, providing multi-spectral imaging data with medium-to-high spatial resolution (80m GSD from 800 km altitude) in the thermal infrared (up to 6 TIR bands, between 8 and 11μm) and in the mid infrared (1 or 2 MIR bands, at 4μm). These MIR/TIR bands will be co-registered with simultaneously acquired high spatial resolution (less than 30 m GSP) visible and near infrared multi-spectral imaging data. To enhance the spatial resolution of the MIR/TIR multi-spectral imagery during daytime, data fusion methods will be applied, such as the Multi-sensor Multi-resolution Technique (MMT), already successfully tested over agricultural terrain. This image processing technique will make generation of Land Surface Temperature (LST) EO products with a spatial resolution of 30 x 30 m2 possible. For high temperature phenomena such as vegetation- and peat-fires, the Fire Disturbance Essential Climate Variables (ECV) "Active fire location" and "Fire Radiative Power" will be retrieved with less than 100 m spatial resolution. Together with the effective fire temperature and the spatial extent even for small fire events the innovative system characteristics of VISIR-SAT go beyond existing and planned IR missions. The comprehensive and physically high-accuracy products from VISIR-SAT (e.g. for fire monitoring) may synergistically complement the high temperature observations of Sentinel-3 SLSTR in a unique way. Additionally, VISIR-SAT offers a very agile sensor system, which will be able to conduct intelligent and flexible pointing of the sensor's line-of-sight with the aim to provide global coverage of cloud free imagery every 5

  6. Spatially-dense, multi-spectral, frequency-domain diffuse optical tomography of breast cancer (United States)

    Ban, Han Yong

    Diffuse optical tomography (DOT) employs near-infrared light to image the concentration of chromophores and cell organelles in tissue and thereby providing access to functional parameters that can differentiate cancerous from normal tissues. This thesis describes research at the bench and in the clinic that explores and identifies the potential of DOT breast cancer imaging. The bench and clinic instrumentation differ but share important features: they utilize a very large, spatially dense, set of source-detector pairs (10 7) for imaging in the parallel-plate geometry. The bench experiments explored three-dimensional (3D) image resolution and fidelity as a function of numerous parameters and also ascertained the effects of a chest wall phantom. The chest wall is always present but is typically ignored in breast DOT. My experiments clarified chest wall influences and developed schemes to mitigate these effects. Mostly, these schemes involved selective data exclusion, but their efficacy also depended on reconstruction approach. Reconstruction algorithms based on analytic (fast) Fourier inversion and linear algebraic techniques were explored. The clinical experiments centered around a DOT instrument that I designed, constructed, and have begun to test (in-vitro and in-vivo). This instrumentation offers many features new to the field. Specifically, the imager employs spatially-dense, multi-spectral, frequency-domain data; it possesses the world's largest optical source-detector density yet reported, facilitated by highly-parallel CCD-based frequency-domain imaging based on gain-modulation heterodyne detection. The instrument thus measures both phase and amplitude of the diffusive light waves. Other features include both frontal and sagittal breast imaging capabilities, ancillary cameras for measurement of breast boundary profiles, real-time data normalization, and mechanical improvements for patient comfort. The instrument design and construction is my most significant

  7. Characterizing Thermal features in Norris Basin, Yellowstone National Park, Using Multi- spectral Remote Sensing Data and Dynamic Calibration Procedures (United States)

    Hardy, C. C.; Queen, L. P.; Heasler, H. P.; Jaworowski, C.


    A thermal infrared remote sensing project was implemented to develop methods for identifying, classifying, and mapping thermal features. This study is directed at geothermal features, with the expectation that new protocols developed here will apply to the wildland fire thermal environment. Airborne multi-spectral digital imagery were acquired over the geothermally active Norris Basin region of Yellowstone National Park, USA. Two image acquisitions were flown, with one acquisition near solar noon and the other at night. Raw data from the five sensors were uncalibrated, so a vicarious calibration procedure was developed to compute reflectance for the visible and NIR bands using an independently calibrated hyperspectral dataset. Calibration of the thermal sensor band utilized a dynamic, in-scene calibration procedure that exploited natural, pseudo-invariant thermal reference targets instrumented with in situ kinetic temperature recorders. The calibrated reflectance and radiant temperature data from each acquisition were processed and analyzed to develop a suite of thermal attributes, including radiant temperatures, a daytime-nighttime temperature difference (DeltaT), albedo, an albedo derivative (one minus albedo), and apparent thermal inertia (ATI). The albedo terms were computed using a published weighed-average albedo algorithm based on ratios of the narrowband red and near-infrared (NIR) reflectances to total solar irradiance for the respective red and NIR bandpasses. The weighing factors for each band were the proportion of total solar irradiance incident on the surface within each segment represented by a respective bandpass. In the absence of verifiable "truth," a step-wise chain of unsupervised classification and multivariate analysis exercises was performed, drawing heavily on "fuzzy truth" to assess the quality, efficiency, and efficacy of classification procedures and results. A final classification synthesizes a "geothermal phenomenology" comprised of

  8. Self-Organized Quantum Dots for High-Performance Multi-Spectral Infrared Photodetectors (United States)


    31, 2009 Program Managers: Donald Silversmith (AFOSR) PI: Anupam Madhukar University of Southern California Los Angeles, CA 90089-0241 Tel...Quantum Dots for High- Performance Multi-Spectral Infrared Photodetectors” (Jul. 1, 2006- Dec. 31, 2009) Program Managers: Donald Silversmith (AFOSR

  9. Color Medical Image Analysis

    CERN Document Server

    Schaefer, Gerald


    Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.

  10. Multi-spectral black meta-infrared detectors (Conference Presentation) (United States)

    Krishna, Sanjay


    There is an increased emphasis on obtaining imaging systems with on-demand spectro-polarimetric information at the pixel level. Meta-infrared detectors in which infrared detectors are combined with metamaterials are a promising way to realize this. The infrared region is appealing due to the low metallic loss, large penetration depth of the localized field and the larger feature sizes compared to the visible region. I will discuss approaches to realize multispectral detectors including our recent work on double metal meta-material design combined with Type II superlattices that have demonstrated enhanced quantum efficiency (collaboration with Padilla group at Duke University).

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

    Energy Technology Data Exchange (ETDEWEB)

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


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

  12. Morphological image analysis

    NARCIS (Netherlands)

    Michielsen, K.; Raedt, H. De; Kawakatsu, T.


    We describe a morphological image analysis method to characterize images in terms of geometry and topology. We present a method to compute the morphological properties of the objects building up the image and apply the method to triply periodic minimal surfaces and to images taken from polymer chemi

  13. Morphological image analysis

    NARCIS (Netherlands)

    Michielsen, K; De Raedt, H; Kawakatsu, T; Landau, DP; Lewis, SP; Schuttler, HB


    We describe a morphological image analysis method to characterize images in terms of geometry and topology. We present a method to compute the morphological properties of the objects building up the image and apply the method to triply periodic minimal surfaces and to images taken from polymer chemi

  14. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting (United States)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.


    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  15. Distinguishability of Biological Material Using Ultraviolet Multi-Spectral Fluorescence

    Energy Technology Data Exchange (ETDEWEB)

    Gray, P.C.; Heinen, R.J.; Rigdon, L.D.; Rosenthal, S.E.; Shokair, I.R.; Siragusa, G.R.; Tisone, G.C.; Wagner, J.S.


    Recent interest in the detection and analysis of biological samples by spectroscopic methods has led to questions concerning the degree of distinguishability and biological variability of the ultraviolet (W) fluorescent spectra from such complex samples. We show that the degree of distinguishability of such spectra is readily determined numerically.

  16. [Development of multi-target multi-spectral high-speed pyrometer]. (United States)

    Xiao, Peng; Dai, Jing-Min; Wang, Qing-Wei


    The plume temperature of a solid propellant rocket engine (SPRE) is a fundamental parameter in denoting combustion status. It is necessary to measure the temperature along both the axis and the radius of the engine. In order to measure the plume temperature distribution of a solid propellant rocket engine, the multi-spectral thermometry has been approved. Previously the pyrometer was developed in the Harbin Institute of Technology of China in 1999, which completed the measurement of SPRE plume temperature and its distribution with multi-spectral technique in aerospace model development for the first time. Following this experience, a new type of multi-target multi-spectral high-speed pyrometer used in the ground experiments of SPRE plume temperature measurement was developed. The main features of the instrument include the use of a dispersing prism and a photo-diode array to cover the entire spectral band of 0.4 to 1.1 microm. The optic fibers are used in order to collect and transmit the thermal radiation fluxes. The instrument can measure simultaneously the temperature and emissivity of eight spectra for six uniformly distributed points on the target surface, which are well defined by the hole on the field stop lens. A specially designed S/H (Sample/Hold) circuit, with 48 sample and hold units that were triggered with a signal, measures the multi-spectral and multi-target outputs. It can sample 48 signals with a less than 10ns time difference which is most important for the temperature calculation.

  17. Mapeamento do biovolume de plantas aquáticas submersas a partir de dados hidroacústicos e imagem multiespectral de alta resolução Mapping the bio-volume of submerged aquatic vegetation through hydro-acoustic data and high-resolution multi-spectral imaging

    Directory of Open Access Journals (Sweden)

    L. Sabo Boschi


    submerged aquatic plants is a complex task due to the difficulty in volumetrically mapping and quantifying the colonized areas. In these cases, the use of hydro-acoustic data allows mapping and measuring these areas, helping formulate proposals for sustainable management of this type of aquatic vegetation. This study used the kriging technique and acoustic data to perform the spatial inference of the biovolume of submerged aquatic plants. The data was obtained from three echobathimetric surveys conducted in a Paraná River study area, characterized by the proliferation of submerged aquatic vegetation, hindering navigation. High spatial resolution multi-spectral imagery World View-2 was used to delimit the areas with submerged aquatic plants. The mapping of the bio-volume of submerged aquatic plants was conducted through the bio-volume inference using the Kriging technique and slicing of the inferred values at 15% intervals. The map generated allowed identifying the areas of highest concentration of submerged macrophytes, which predominantly presented bio-volume values between 15-30% and 30-45%. This confirms the feasibility of using the kriging technique for biovolume spatial inference through geo-referenced ecobathimetric measurements and the support of high spatial resolution imagery.

  18. Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

    Directory of Open Access Journals (Sweden)

    Mitch Bryson

    Full Text Available Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae and animal (e.g. gastropods assemblages at multiple spatial and temporal scales.

  19. Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes. (United States)

    Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel


    Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

  20. Integrating geometric activity images in ANN classification (United States)

    De Genst, William; Gautama, Sidharta; Bellens, Rik; Canters, Frank


    In this paper we demonstrate how the interaction between innovative methods in the field of computer vision and methods for multi-spectral image classification can help in extracting detailed land-cover / land-use information from Very High Resolution (VHR) satellite imagery. We introduce the novel concept of "geometric activity images", which we define as images encoding the strength of the relationship between a pixel and surrounding features detected through dedicated computer vision methods. These geometric activity images are used as alternatives to more traditional texture images that better describe the geometry of man-made structures and that can be included as additional information in a non-parametric supervised classification framework. We present a number of findings resulting from the integration of geometric activity images and multi-spectral bands in an artificial neural network classification. The geometric activity images we use result from the use of a ridge detector for straight line detection, calculated for different window sizes and for all multi-spectral bands and band-ratio images in a VHR scene. A selection of the most relevant bands to use for classification is carried out using band selection based on a genetic algorithm. Sensitivity analysis is used to assess the importance of each input variable. An application of the proposed methods to part of a Quickbird image taken over the suburban fringe of the city of Ghent (Belgium) shows that we are able to identify roads with much higher accuracy than when using more traditional multi-spectral image classification techniques.

  1. Gabor Analysis for Imaging

    DEFF Research Database (Denmark)

    Christensen, Ole; Feichtinger, Hans G.; Paukner, Stephan


    , it characterizes a function by its transform over phase space, which is the time–frequency plane (TF-plane) in a musical context or the location–wave-number domain in the context of image processing. Since the transition from the signal domain to the phase space domain introduces an enormous amount of data...... of the generalities relevant for an understanding of Gabor analysis of functions on Rd. We pay special attention to the case d = 2, which is the most important case for image processing and image analysis applications. The chapter is organized as follows. Section 2 presents central tools from functional analysis......, the application of Gabor expansions to image representation is considered in Sect. 6....

  2. Text Region Extraction: A Morphological Based Image Analysis Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Dhirendra Pal Singh


    Full Text Available Image analysis belongs to the area of computer vision and pattern recognition. These areas are also a part of digital image processing, where researchers have a great attention in the area of content retrieval information from various types of images having complex background, low contrast background or multi-spectral background etc. These contents may be found in any form like texture data, shape, and objects. Text Region Extraction as a content from an mage is a class of problems in Digital Image Processing Applications that aims to provides necessary information which are widely used in many fields medical imaging, pattern recognition, Robotics, Artificial intelligent Transport systems etc. To extract the text data information has becomes a challenging task. Since, Text extraction are very useful for identifying and analysis the whole information about image, Therefore, In this paper, we propose a unified framework by combining morphological operations and Genetic Algorithms for extracting and analyzing the text data region which may be embedded in an image by means of variety of texts: font, size, skew angle, distortion by slant and tilt, shape of the object which texts are on, etc. We have established our proposed methods on gray level image sets and make qualitative and quantitative comparisons with other existing methods and concluded that proposed method is better than others.

  3. Digital image analysis

    DEFF Research Database (Denmark)

    Riber-Hansen, Rikke; Vainer, Ben; Steiniche, Torben


    Digital image analysis (DIA) is increasingly implemented in histopathological research to facilitate truly quantitative measurements, decrease inter-observer variation and reduce hands-on time. Originally, efforts were made to enable DIA to reproduce manually obtained results on histological slides...... reproducibility, application of stereology-based quantitative measurements, time consumption, optimization of histological slides, regions of interest selection and recent developments in staining and imaging techniques....

  4. Combining multi-spectral proximal sensors and digital cameras for monitoring grazed tropical pastures (United States)

    Handcock, R. N.; Gobbett, D. L.; González, L. A.; Bishop-Hurley, G. J.; McGavin, S. L.


    Timely and accurate monitoring of pasture biomass and ground-cover is necessary in livestock production systems to ensure productive and sustainable management of forage for livestock. Interest in the use of proximal sensors for monitoring pasture status in grazing systems has increased, since such sensors can return data in near real-time, and have the potential to be deployed on large properties where remote sensing may not be suitable due to issues such as spatial scale or cloud cover. However, there are unresolved challenges in developing calibrations to convert raw sensor data to quantitative biophysical values, such as pasture biomass or vegetation ground-cover, to allow meaningful interpretation of sensor data by livestock producers. We assessed the use of multiple proximal sensors for monitoring tropical pastures with a pilot deployment of sensors at two sites on Lansdown Research Station near Townsville, Australia. Each site was monitored by a Skye SKR-four-band multi-spectral sensor (every 1 min), a digital camera (every 30 min), and a soil moisture sensor (every 1 min), each operated over 18 months. Raw data from each sensor were processed to calculate a number of multispectral vegetation indices. Visual observations of pasture characteristics, including above-ground standing biomass and ground cover, were made every 2 weeks. A methodology was developed to manage the sensor deployment and the quality control of the data collected. The data capture from the digital cameras was more reliable than the multi-spectral sensors, which had up to 63 % of data discarded after data cleaning and quality control. We found a strong relationship between sensor and pasture measurements during the wet season period of maximum pasture growth (January to April), especially when data from the multi-spectral sensors were combined with weather data. RatioNS34 (a simple band ratio between the near infrared (NIR) and lower shortwave infrared (SWIR) bands) and rainfall since 1

  5. 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...

  6. Multi-spectral measurements program and guiding a rocket to hover (United States)

    Taylor, W. G.


    The Multi-Spectral Measurement Program (MSMP) was a large and sophisticated sounding rocket endeavor to examine in space the exhaust plume of rocket engines. The MSMP required that the plumes be analyzed at different wavelengths, from various aspects, and from varying distances. The ELF III provided the guidance signals necessary to orient the 'sensor' vehicle. UV, IR, television, and long-focal-length still-camera picture data were taken. Most of the data were telemetered down in real time. Because of the nature of the experiments, the number of data-gathering devices, and the monitoring of the large three-stage missile, the telemetering of data became a very complex subproject in itself.

  7. Study on shallow groundwater information extraction technology based on multi-spectral data and spatial data

    Institute of Scientific and Technical Information of China (English)

    YU DeHao; DENG ZhengDong; LONG Fan; GUAN HongJun; WANG DaQing; GOU YiZheng


    Aimed at solving the difficulties, such as low efficiency and limited exploration range encountered in finding groundwater with the traditional methods, a new method was presented by using remote sensing technology in this paper. Based on multi-spectral data (ETM data) and spatial data (SRTM data),a forecasting model was built to produce a probability rating map for finding shallow groundwater in the arid and semi-arid areas. According to investigations, a conclusion is drawn that the results of the model are satisfied, which have been testified by the later geophysical exploration and drilling. Thus,the model can serve as a guide for finding groundwater in the arid and semi-arid regions.

  8. Study on shallow groundwater information extraction technology based on multi-spectral data and spatial data

    Institute of Scientific and Technical Information of China (English)


    Aimed at solving the difficulties,such as low efficiency and limited exploration range encountered in finding groundwater with the traditional methods,a new method was presented by using remote sensing technology in this paper.Based on multi-spectral data(ETM data) and spatial data(SRTM data),a forecasting model was built to produce a probability rating map for finding shallow groundwater in the arid and semi-arid areas.According to investigations,a conclusion is drawn that the results of the model are satisfied,which have been testified by the later geophysical exploration and drilling.Thus,the model can serve as a guide for finding groundwater in the arid and semi-arid regions.

  9. A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions (United States)

    Selkowitz, David J.; Green, Gordon; Peterson, Birgit E.; Wylie, Bruce


    Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of

  10. Medical Image Analysis Facility (United States)


    To improve the quality of photos sent to Earth by unmanned spacecraft. NASA's Jet Propulsion Laboratory (JPL) developed a computerized image enhancement process that brings out detail not visible in the basic photo. JPL is now applying this technology to biomedical research in its Medical lrnage Analysis Facility, which employs computer enhancement techniques to analyze x-ray films of internal organs, such as the heart and lung. A major objective is study of the effects of I stress on persons with heart disease. In animal tests, computerized image processing is being used to study coronary artery lesions and the degree to which they reduce arterial blood flow when stress is applied. The photos illustrate the enhancement process. The upper picture is an x-ray photo in which the artery (dotted line) is barely discernible; in the post-enhancement photo at right, the whole artery and the lesions along its wall are clearly visible. The Medical lrnage Analysis Facility offers a faster means of studying the effects of complex coronary lesions in humans, and the research now being conducted on animals is expected to have important application to diagnosis and treatment of human coronary disease. Other uses of the facility's image processing capability include analysis of muscle biopsy and pap smear specimens, and study of the microscopic structure of fibroprotein in the human lung. Working with JPL on experiments are NASA's Ames Research Center, the University of Southern California School of Medicine, and Rancho Los Amigos Hospital, Downey, California.

  11. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær


    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  12. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær


    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  13. A linear model to predict with a multi-spectral radiometer the amount of nitrogen in winter wheat

    NARCIS (Netherlands)

    Reyniers, M.; Walvoort, D.J.J.; Baardemaaker, De J.


    The objective was to develop an optimal vegetation index (VIopt) to predict with a multi-spectral radiometer nitrogen in wheat crop (kg[N] ha-1). Optimality means that nitrogen in the crop can be measured accurately in the field during the growing season. It also means that the measurements are

  14. Image sequence analysis

    CERN Document Server


    The processing of image sequences has a broad spectrum of important applica­ tions including target tracking, robot navigation, bandwidth compression of TV conferencing video signals, studying the motion of biological cells using microcinematography, cloud tracking, and highway traffic monitoring. Image sequence processing involves a large amount of data. However, because of the progress in computer, LSI, and VLSI technologies, we have now reached a stage when many useful processing tasks can be done in a reasonable amount of time. As a result, research and development activities in image sequence analysis have recently been growing at a rapid pace. An IEEE Computer Society Workshop on Computer Analysis of Time-Varying Imagery was held in Philadelphia, April 5-6, 1979. A related special issue of the IEEE Transactions on Pattern Anal­ ysis and Machine Intelligence was published in November 1980. The IEEE Com­ puter magazine has also published a special issue on the subject in 1981. The purpose of this book ...

  15. Bio-Inspired Dynamically Tunable Polymer-Based Filters for Multi-Spectral Infrared Imaging (United States)


    Morse. Plastic Transmissive Infrared Electrochromic Devices , Macromolecular Chemistry and Physics, (07 2010): 0. doi: 10.1002/macp.201000096 2011/10/10...Publication: Holt, A.L., J. G. A. Wehner, A. Hammp and D. E. Morse. 2010. Plastic transmissive infrared electrochromic devices ...Level Device Design ( Electrochromic -Based IR Shutter): The first initiative in the device design work consisted of determining a standard device

  16. Autonomous Onboard Science Image Analysis for Future Mars Rover Missions (United States)

    Gulick, V. C.; Morris, R. L.; Ruzon, M. A.; Roush, T. L.


    To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. Output from these algorithms could be used to autonomously obtain rock spectra, determine which images should be

  17. Interaction of the minocycline with extracelluar protein and intracellular protein by multi-spectral techniques and molecular docking (United States)

    Fang, Qing; Wang, Yirun; Hu, Taoying; Liu, Ying


    The interaction of minocyeline (MNC) with extracelluar protein (lysozyme, LYSO) or intracellular protein (bovine hemoglobin, BHb) was investigated using multi-spectral techniques and molecular docking in vitro. Fluorescence studies suggested that MNC quenched LYSO/BHb fluorescence in a static mode with binding constants of 2.01 and 0.26 × 104 L•mol-1 at 298 K, respectively. The LYZO-MNC system was more easily influenced by temperature (298 and 310 K) than the BHb-MNC system. The thermodynamic parameters demonstrated that hydrogen bonds and van der Waals forces played the major role in the binding process. Based on the Förster theory of nonradiative energy transfer, the binding distances between MNC and the inner tryptophan residues of LYSO and BHb were calculated to be 4.34 and 3.49 nm, respectively. Furthermore, circular dichroism spectra (CD), Fourier transforms infrared (FTIR), UV-vis, and three-dimensional fluorescence spectra results indicated the secondary structures of LYSO and BHb were partially destroyed by MNC with the α-helix percentage of LYZO-MNC increased (17.8-28.6%) while that of BHb-MNC was decreased (41.6-39.6%). UV-vis spectral results showed these binding interactions could cause conformational and some micro-environmental changes of LYSO and BHb. In accordance with the results of molecular docking, In LYZO-MNC system, MNC was mainly bound in the active site hinge region where Trp-62 and Trp-63 are located, and in MNC-BHb system, MNC was close to the subunit α 1 of BHb, molecular docking analysis supported the thermodynamic results well. The work contributes to clarify the mechanism of MNC with two proteins at molecular level.

  18. Image based performance analysis of thermal imagers (United States)

    Wegner, D.; Repasi, E.


    Due to advances in technology, modern thermal imagers resemble sophisticated image processing systems in functionality. Advanced signal and image processing tools enclosed into the camera body extend the basic image capturing capability of thermal cameras. This happens in order to enhance the display presentation of the captured scene or specific scene details. Usually, the implemented methods are proprietary company expertise, distributed without extensive documentation. This makes the comparison of thermal imagers especially from different companies a difficult task (or at least a very time consuming/expensive task - e.g. requiring the execution of a field trial and/or an observer trial). For example, a thermal camera equipped with turbulence mitigation capability stands for such a closed system. The Fraunhofer IOSB has started to build up a system for testing thermal imagers by image based methods in the lab environment. This will extend our capability of measuring the classical IR-system parameters (e.g. MTF, MTDP, etc.) in the lab. The system is set up around the IR- scene projector, which is necessary for the thermal display (projection) of an image sequence for the IR-camera under test. The same set of thermal test sequences might be presented to every unit under test. For turbulence mitigation tests, this could be e.g. the same turbulence sequence. During system tests, gradual variation of input parameters (e. g. thermal contrast) can be applied. First ideas of test scenes selection and how to assembly an imaging suite (a set of image sequences) for the analysis of imaging thermal systems containing such black boxes in the image forming path is discussed.

  19. Optimization of the Multi-Spectral Euclidean Distance Calculation for FPGA-based Spaceborne Systems (United States)

    Cristo, Alejandro; Fisher, Kevin; Perez, Rosa M.; Martinez, Pablo; Gualtieri, Anthony J.


    Due to the high quantity of operations that spaceborne processing systems must carry out in space, new methodologies and techniques are being presented as good alternatives in order to free the main processor from work and improve the overall performance. These include the development of ancillary dedicated hardware circuits that carry out the more redundant and computationally expensive operations in a faster way, leaving the main processor free to carry out other tasks while waiting for the result. One of these devices is SpaceCube, a FPGA-based system designed by NASA. The opportunity to use FPGA reconfigurable architectures in space allows not only the optimization of the mission operations with hardware-level solutions, but also the ability to create new and improved versions of the circuits, including error corrections, once the satellite is already in orbit. In this work, we propose the optimization of a common operation in remote sensing: the Multi-Spectral Euclidean Distance calculation. For that, two different hardware architectures have been designed and implemented in a Xilinx Virtex-5 FPGA, the same model of FPGAs used by SpaceCube. Previous results have shown that the communications between the embedded processor and the circuit create a bottleneck that affects the overall performance in a negative way. In order to avoid this, advanced methods including memory sharing, Native Port Interface (NPI) connections and Data Burst Transfers have been used.

  20. The multi-spectral line-polarization MSE system on Alcator C-Mod

    Energy Technology Data Exchange (ETDEWEB)

    Mumgaard, R. T., E-mail:; Khoury, M. [Plasma Science and Fusion Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Scott, S. D. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08540 (United States)


    A multi-spectral line-polarization motional Stark effect (MSE-MSLP) diagnostic has been developed for the Alcator C-Mod tokamak wherein the Stokes vector is measured in multiple wavelength bands simultaneously on the same sightline to enable better polarized background subtraction. A ten-sightline, four wavelength MSE-MSLP detector system was designed, constructed, and qualified. This system consists of a high-throughput polychromator for each sightline designed to provide large étendue and precise spectral filtering in a cost-effective manner. Each polychromator utilizes four narrow bandpass interference filters and four custom large diameter avalanche photodiode detectors. Two filters collect light to the red and blue of the MSE emission spectrum while the remaining two filters collect the beam pi and sigma emission generated at the same viewing volume. The filter wavelengths are temperature tuned using custom ovens in an automated manner. All system functions are remote controllable and the system can be easily retrofitted to existing single-wavelength line-polarization MSE systems.

  1. The multi-spectral line-polarization MSE system on Alcator C-Mod (United States)

    Mumgaard, R. T.; Scott, S. D.; Khoury, M.


    A multi-spectral line-polarization motional Stark effect (MSE-MSLP) diagnostic has been developed for the Alcator C-Mod tokamak wherein the Stokes vector is measured in multiple wavelength bands simultaneously on the same sightline to enable better polarized background subtraction. A ten-sightline, four wavelength MSE-MSLP detector system was designed, constructed, and qualified. This system consists of a high-throughput polychromator for each sightline designed to provide large étendue and precise spectral filtering in a cost-effective manner. Each polychromator utilizes four narrow bandpass interference filters and four custom large diameter avalanche photodiode detectors. Two filters collect light to the red and blue of the MSE emission spectrum while the remaining two filters collect the beam pi and sigma emission generated at the same viewing volume. The filter wavelengths are temperature tuned using custom ovens in an automated manner. All system functions are remote controllable and the system can be easily retrofitted to existing single-wavelength line-polarization MSE systems.

  2. Suppression of edge localized mode crashes by multi-spectral non-axisymmetric fields in KSTAR (United States)

    Kim, Jayhyun; Park, Gunyoung; Bae, Cheonho; Yoon, Siwoo; Han, Hyunsun; Yoo, Min-Gu; Park, Young-Seok; Ko, Won-Ha; Juhn, June-Woo; Na, Yong Su; The KSTAR Team


    Among various edge localized mode (ELM) crash control methods, only non-axisymmetric magnetic perturbations (NAMPs) yield complete suppression of ELM crashes beyond their mitigation, and thus attract more attention than others. No other devices except KSTAR, DIII-D, and recently EAST have successfully achieved complete suppression with NAMPs. The underlying physics mechanisms of these successful ELM crash suppressions in a non-axisymmetric field environment, however, still remain uncertain. In this work, we investigate the ELM crash suppression characteristics of the KSTAR ELMy H-mode discharges in a controlled multi-spectral field environment, created by both n=2 middle reference and n=1 top/bottom proxy in-vessel control coils. Interestingly, the attempts have produced a set of contradictory findings, one expected (ELM crash suppression enhancement with the addition of n  =  1 to the n  =  2 field at relatively low heating discharges) and another unexpected (ELM crash suppression degradation at relatively high heating discharges) from the earlier findings in DIII-D. This contradiction indicates the dependence of the ELM crash suppression characteristics on the heating level and the associated kink-like plasma responses. Preliminary linear resistive MHD plasma response simulation shows the unexpected suppression performance degradation to be likely caused by the dominance of kink-like plasma responses over the island gap-filling effects.

  3. Reflections on ultrasound image analysis. (United States)

    Alison Noble, J


    Ultrasound (US) image analysis has advanced considerably in twenty years. Progress in ultrasound image analysis has always been fundamental to the advancement of image-guided interventions research due to the real-time acquisition capability of ultrasound and this has remained true over the two decades. But in quantitative ultrasound image analysis - which takes US images and turns them into more meaningful clinical information - thinking has perhaps more fundamentally changed. From roots as a poor cousin to Computed Tomography (CT) and Magnetic Resonance (MR) image analysis, both of which have richer anatomical definition and thus were better suited to the earlier eras of medical image analysis which were dominated by model-based methods, ultrasound image analysis has now entered an exciting new era, assisted by advances in machine learning and the growing clinical and commercial interest in employing low-cost portable ultrasound devices outside traditional hospital-based clinical settings. This short article provides a perspective on this change, and highlights some challenges ahead and potential opportunities in ultrasound image analysis which may both have high impact on healthcare delivery worldwide in the future but may also, perhaps, take the subject further away from CT and MR image analysis research with time.

  4. Digital Images Analysis



    International audience; A specific field of image processing focuses on the evaluation of image quality and assessment of their authenticity. A loss of image quality may be due to the various processes by which it passes. In assessing the authenticity of the image we detect forgeries, detection of hidden messages, etc. In this work, we present an overview of these areas; these areas have in common the need to develop theories and techniques to detect changes in the image that it is not detect...

  5. Image Analysis in CT Angiography

    NARCIS (Netherlands)

    Manniesing, R.


    In this thesis we develop and validate novel image processing techniques for the analysis of vascular structures in medical images. First a new type of filter is proposed which is capable of enhancing vascular structures while suppressing noise in the remainder of the image. This filter is based on

  6. Reference image selection for difference imaging analysis

    CERN Document Server

    Huckvale, Leo; Sale, Stuart E


    Difference image analysis (DIA) is an effective technique for obtaining photometry in crowded fields, relative to a chosen reference image. As yet, however, optimal reference image selection is an unsolved problem. We examine how this selection depends on the combination of seeing, background and detector pixel size. Our tests use a combination of simulated data and quality indicators from DIA of well-sampled optical data and under-sampled near-infrared data from the OGLE and VVV surveys, respectively. We search for a figure-of-merit (FoM) which could be used to select reference images for each survey. While we do not find a universally applicable FoM, survey-specific measures indicate that the effect of spatial under-sampling may require a change in strategy from the standard DIA approach, even though seeing remains the primary criterion. We find that background is not an important criterion for reference selection, at least for the dynamic range in the images we test. For our analysis of VVV data in particu...

  7. Satellite-based multi-spectral detection of the Widespread and Persistent Winter Fog over the Indo-Gangetic Plains (United States)

    Gautam, R.; Rizvi, S.


    The Indo-Gangetic Plains (IGP), in the northern parts of south Asia, are subjected to dense haze/fog during winter months, on an annual basis. The thick fog prevalent during December/January months is both persistent and widespread in nature, often covering the entire IGP which stretches over 1500km in length. This study used multi-spectral imagery from MODIS data, to develop algorithms for daytime as well as nighttime detection of fog during winter 2000 to 2014 over the IGP. Specifically, our nighttime detection algorithm employs a bispectral thresholding technique, involving brightness temperature difference (BTD) between two spectral channels- 3.9 and 11.02μm. The theoretical basis for the detection using the 3.9 μm and 11.02 μm channels rely on the particular emissive properties of the two channels for fog droplets (Bendix and Bachmann, 1991). The small droplets found in fog are less emissive at 3.9 μm than at 11.02 μm. Brightness temperatures computed from corresponding radiance data (MODIS Level-1B) of band 22 (3.9 μm) and band 31 (11.02 μm), in conjunction with theoretical calculations from a radiative transfer (RT) model, were utilized to evaluate threshold value of BTD. Using theoretical RT calculations and automated analysis of hundreds of moderately high resolution satellite imagery (pixel resolution of 1km), our threshold cutoff for foggy pixels results in BTD value of 4 (deg) K. Additionally, to minimize contamination, we apply a spatial variability filter to discriminate the uniform texture of fog from other low-level clouds. A similar methodology based on BTD is also tested for daytime fog detection and separation from other cloud types. Furthermore, on the basis of operational multispectral retrievals of cloud properties (cloud effective radius, cloud top pressure, and cloud fraction) from MODIS, we have also processed spatial occurrences of fog climatology from 2000 to 2014. To validate our satellite retrieval algorithm of fog detection from


    DEFF Research Database (Denmark)


    A method classifying objects man image as respective arterial or venous vessels comprising: identifying pixels of the said modified image which are located on a line object, determining which of the said image points is associated with crossing point or a bifurcation of the respective line object......, wherein a crossing point is represented by an image point which is the intersection of four line segments, performing a matching operation on pairs of said line segments for each said crossing point, to determine the path of blood vessels in the image, thereby classifying the line objects in the original...... image into two arbitrary sets, and thereafter designating one of the sets as representing venous structure, the other of the sets as representing arterial structure, depending on one or more of the following criteria: (a) complexity of structure; (b) average density; (c) average width; (d) tortuosity...

  9. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.


    of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  10. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  11. Oncological image analysis: medical and molecular image analysis (United States)

    Brady, Michael


    This paper summarises the work we have been doing on joint projects with GE Healthcare on colorectal and liver cancer, and with Siemens Molecular Imaging on dynamic PET. First, we recall the salient facts about cancer and oncological image analysis. Then we introduce some of the work that we have done on analysing clinical MRI images of colorectal and liver cancer, specifically the detection of lymph nodes and segmentation of the circumferential resection margin. In the second part of the paper, we shift attention to the complementary aspect of molecular image analysis, illustrating our approach with some recent work on: tumour acidosis, tumour hypoxia, and multiply drug resistant tumours.

  12. Oil Palm Tree Detection with High Resolution Multi-Spectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Panu Srestasathiern


    Full Text Available Oil palm tree is an important cash crop in Thailand. To maximize the productivity from planting, oil palm plantation managers need to know the number of oil palm trees in the plantation area. In order to obtain this information, an approach for palm tree detection using high resolution satellite images is proposed. This approach makes it possible to count the number of oil palm trees in a plantation. The process begins with the selection of the vegetation index having the highest discriminating power between oil palm trees and background. The index having highest discriminating power is then used as the primary feature for palm tree detection. We hypothesize that oil palm trees are located at the local peak within the oil palm area. To enhance the separability between oil palm tree crowns and background, the rank transformation is applied to the index image. The local peak on the enhanced index image is then detected by using the non-maximal suppression algorithm. Since both rank transformation and non-maximal suppression are window based, semi-variogram analysis is used to determine the appropriate window size. The performance of the proposed method was tested on high resolution satellite images. In general, our approach uses produced very accurate results, e.g., about 90 percent detection rate when compared with manual labeling.

  13. NEAR MSI Images of Asteroid Eros: New Data Products and Analysis (United States)

    Blewett, David T.; Ernst, Carolyn; Shusterman, Morgan L.; Nguyen, Lillian; Espiritu, Raymond C.; Turner, Russell J.; Barnouin, Olivier S.


    The Near-Earth Asteroid Rendezvous (NEAR) spacecraft orbited asteroid Eros for approximately one year in 2000–2001, returning thousands of images obtained with the MultiSpectral Imager (MSI) camera system. R. Gaskell used ~20,000 of these images to construct a high-resolution shape model of Eros that was archived in the NASA Planetary Data System (PDS) in 2008. We have produced backplanes for this set of images, and are in the process of preparing them for delivery to the PDS. The 16 backplanes contain information of interest for each pixel in an image: 1. Image pixel value. 2. x value of point, body centered coords. 3. y value of point. 4. z value of point. 5. Latitude. 6. Longitude. 7. Distance from center of asteroid. 8. Solar incidence angle. 9. Emergence angle. 10. Phase angle. 11. Horizontal pixel scale (km/pixel). 12. Vertical pixel scale. 13. Slope. 14. Elevation. 15. Gravitational acceleration. 16. Gravitational potential. This set of backplanes will be provided to the PDS Small Bodies Node, with PDS-4 labels. The Gaskell shape model, produced with stereophotoclinometry, has more than 3.1 million plates. Hence this model has more than an order of magnitude better spatial resolution compared with the older shape model (200,700 plates). The high-resolution shape model permits substantial improvements in photometric normalization of images to be made, because the incidence, emergence, and phase angles can be determined at smaller scales. We plan to perform new photometric normalization of color image sets in order to search for mineralogical variations at higher resolution than was previously possible. In addition, we will carry out phase-ratio analysis to extract information on surface texture and scattering behavior for features of special interest.

  14. Hyperspectral image analysis. A tutorial

    DEFF Research Database (Denmark)

    Amigo Rubio, Jose Manuel; Babamoradi, Hamid; Elcoroaristizabal Martin, Saioa


    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processi...... to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case....... will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology...

  15. Hyperspectral image analysis. A tutorial

    Energy Technology Data Exchange (ETDEWEB)

    Amigo, José Manuel, E-mail: [Spectroscopy and Chemometrics Group, Department of Food Sciences, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C DK–1958 (Denmark); Babamoradi, Hamid [Spectroscopy and Chemometrics Group, Department of Food Sciences, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C DK–1958 (Denmark); Elcoroaristizabal, Saioa [Spectroscopy and Chemometrics Group, Department of Food Sciences, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C DK–1958 (Denmark); Chemical and Environmental Engineering Department, School of Engineering, University of the Basque Country, Alameda de Urquijo s/n, E-48013 Bilbao (Spain)


    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares – Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. - Highlights: • Comprehensive tutorial of Hyperspectral Image analysis. • Hierarchical discrimination of six classes of plastics containing flame retardant. • Step by step guidelines to perform class-modeling on hyperspectral images. • Fusion of multivariate data analysis and digital image processing methods. • Promising methodology for real-time detection of plastics containing flame retardant.

  16. Stochastic geometry for image analysis

    CERN Document Server

    Descombes, Xavier


    This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are  described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed.  Numerous applications, covering remote sensing images, biological and medical imaging, are detailed.  This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

  17. Paraxial ghost image analysis (United States)

    Abd El-Maksoud, Rania H.; Sasian, José M.


    This paper develops a methodology to model ghost images that are formed by two reflections between the surfaces of a multi-element lens system in the paraxial regime. An algorithm is presented to generate the ghost layouts from the nominal layout. For each possible ghost layout, paraxial ray tracing is performed to determine the ghost Gaussian cardinal points, the size of the ghost image at the nominal image plane, the location and diameter of the ghost entrance and exit pupils, and the location and diameter for the ghost entrance and exit windows. The paraxial ghost irradiance point spread function is obtained by adding up the irradiance contributions for all ghosts. Ghost simulation results for a simple lens system are provided. This approach provides a quick way to analyze ghost images in the paraxial regime.

  18. Burned area mapping in Mediterranean environment using medium-resolution multi-spectral data and a neuro-fuzzy classifier


    MITRAKIS NIKOLAOS; Mallinis, Giorgos; Koutsias, Nikos; Theocharis, J. B.


    In this study, we assess the performance of a self-organising neuro-fuzzy classifier for burned area mapping using multi-spectral satellite data. The proposed neuro-fuzzy model incorporates a multi-layered structure consisting of two types of nodes. The first type is a generic fuzzy neuron classifier (FNCs), whereas the second is solely a decision fusion operator. The Group Method of Data Handling algorithm is used for structure learning providing the model with self-organising attributes and...

  19. Image Analysis for Tongue Characterization

    Institute of Scientific and Technical Information of China (English)

    SHENLansun; WEIBaoguo; CAIYiheng; ZHANGXinfeng; WANGYanqing; CHENJing; KONGLingbiao


    Tongue diagnosis is one of the essential methods in traditional Chinese medical diagnosis. The ac-curacy of tongue diagnosis can be improved by tongue char-acterization. This paper investigates the use of image anal-ysis techniques for tongue characterization by evaluating visual features obtained from images. A tongue imaging and analysis instrument (TIAI) was developed to acquire digital color tongue images. Several novel approaches are presented for color calibration, tongue area segmentation,quantitative analysis and qualitative description for the colors of tongue and its coating, the thickness and moisture of coating and quantification of the cracks of the toilgue.The overall accuracy of the automatic analysis of the colors of tongue and the thickness of tongue coating exceeds 85%.This work shows the promising future of tongue character-ization.

  20. Compact Micro-Imaging Spectrometer (CMIS): Investigation of Imaging Spectroscopy and Its Application to Mars Geology and Astrobiology (United States)

    Staten, Paul W.


    Future missions to Mars will attempt to answer questions about Mars' geological and biological history. The goal of the CMIS project is to design, construct, and test a capable, multi-spectral micro-imaging spectrometer use in such missions. A breadboard instrument has been constructed with a micro-imaging camera and Several multi-wavelength LED illumination rings. Test samples have been chosen for their interest to spectroscopists, geologists and astrobiologists. Preliminary analysis has demonstrated the advantages of isotropic illumination and micro-imaging spectroscopy over spot spectroscopy.

  1. Flightspeed Integral Image Analysis Toolkit (United States)

    Thompson, David R.


    The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

  2. Automated image analysis to quantify the subnuclear organization of transcriptional coregulatory protein complexes in living cell populations (United States)

    Voss, Ty C.; Demarco, Ignacio A.; Booker, Cynthia F.; Day, Richard N.


    Regulated gene transcription is dependent on the steady-state concentration of DNA-binding and coregulatory proteins assembled in distinct regions of the cell nucleus. For example, several different transcriptional coactivator proteins, such as the Glucocorticoid Receptor Interacting Protein (GRIP), localize to distinct spherical intranuclear bodies that vary from approximately 0.2-1 micron in diameter. We are using multi-spectral wide-field microscopy of cells expressing coregulatory proteins labeled with the fluorescent proteins (FP) to study the mechanisms that control the assembly and distribution of these structures in living cells. However, variability between cells in the population makes an unbiased and consistent approach to this image analysis absolutely critical. To address this challenge, we developed a protocol for rigorous quantification of subnuclear organization in cell populations. Cells transiently co-expressing a green FP (GFP)-GRIP and the monomeric red FP (mRFP) are selected for imaging based only on the signal in the red channel, eliminating bias due to knowledge of coregulator organization. The impartially selected images of the GFP-coregulatory protein are then analyzed using an automated algorithm to objectively identify and measure the intranuclear bodies. By integrating all these features, this combination of unbiased image acquisition and automated analysis facilitates the precise and consistent measurement of thousands of protein bodies from hundreds of individual living cells that represent the population.

  3. Wide-band IR imaging in the NIR-MIR-FIR regions for in situ analysis of frescoes (United States)

    Daffara, C.; Pezzati, L.; Ambrosini, D.; Paoletti, D.; Di Biase, R.; Mariotti, P. I.; Frosinini, C.


    Imaging methods offer several advantages in the field of conservation allowing to perform non-invasive inspection of works of art. In particular, non-invasive techniques based on imaging in different infrared (IR) regions are widely used for the investigation of paintings. Using radiation beyond the visible range, different characteristics of the inspected artwork may be revealed according to the bandwidth acquired. In this paper we present the recent results of a joint project among the two research institutes DIMEG and CNR-INO, and the restoration facility Opificio delle Pietre Dure, concerning the wide-band integration of IR imaging techniques, in the spectral ranges NIR 0.8-2.5 μm, MIR 3-5 μm, and FIR 8-12 μm, for in situ analysis of artworks. A joint, multi-mode use of reflection and thermal bands is proposed for the diagnostics of mural paintings, and it is demonstrated to be an effective tool in inspecting the layered structure. High resolution IR reflectography and, to a greater extent, IR imaging in the 3-5 μm band, are effectively used to characterize the superficial layer of the fresco and to analyze the stratigraphy of different pictorial layers. IR thermography in the 8-12 μm band is used to characterize the support deep structure. The integration of all the data provides a multi- layered and multi-spectral representation of the fresco that yields a comprehensive analysis.

  4. Comparing robust and physics-based sea surface temperature retrievals for high resolution, multi-spectral thermal sensors using one or multiple looks

    Energy Technology Data Exchange (ETDEWEB)

    Borel, C.C.; Clodius, W.B.; Szymanski, J.J.; Theiler, J.P.


    With the advent of multi-spectral thermal imagers such as EOS's ASTER high spatial resolution thermal imagery of the Earth's surface will soon be a reality. Previous high resolution sensors such as Landsat 5 had only one spectral channel in the thermal infrared and its utility to determine absolute sea surface temperatures was limited to 6-8 K for water warmer than 25 deg C. This inaccuracy resulted from insufficient knowledge of the atmospheric temperature and water vapor, inaccurate sensor calibration, and cooling effects of thin high cirrus clouds. The authors will present two studies of algorithms and compare their performance. The first algorithm they call robust since it retrieves sea surface temperatures accurately over a fairly wide range of atmospheric conditions using linear combinations of nadir and off-nadir brightness temperatures. The second they call physics-based because it relies on physics-based models of the atmosphere. It attempts to come up with a unique sea surface temperature which fits one set of atmospheric parameters.


    Directory of Open Access Journals (Sweden)

    Karsten Rodenacker


    Full Text Available Populations of bacteria in sludge flocs and biofilm marked by fluorescence marked with fluorescent probes are digitised with a confocal laser scanning microscope. These data are used to analyse the microbial community structure, to obtain information on the localisation of specific bacterial groups and to examine gene expression. This information is urgently required for an in-depth understanding of the function and, more generally, the microbial ecology of biofilms. Methods derived from quantitative image analysis are applied to digitised data from confocal laser scanning microscopes to obtain quantitative descriptions of volumetric, topological (and topographical properties of different compartments of the components under research. In addition to free-moving flocs, also biofilms attached to a substratum in an experimental environment are analysed. Growth form as well as interaction of components are quantitatively described. Classical measurements of volume and intensity (shape, distribution and distance dependent interaction measurements using methods from mathematical morphology are performed. Mainly image (volume processing methods are outlined. Segmented volumes are globally and individually (in terms of 3Dconnected components measured and used for distance mapping transform as well as for estimation of geodesic distances from the substrate. All transformations are applied on the 3D data set. Resulting distance distributions are quantified and related to information on the identity and activity of the probe-identified bacteria.

  6. Shape analysis in medical image analysis

    CERN Document Server

    Tavares, João


    This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computationa...

  7. Using RPAS Multi-Spectral Imagery to Characterise Vigour, Leaf Development, Yield Components and Berry Composition Variability within a Vineyard

    Directory of Open Access Journals (Sweden)

    Clara Rey-Caramés


    Full Text Available Implementation of precision viticulture techniques requires the use of emerging sensing technologies to assess the vineyard spatial variability. This work shows the capability of multispectral imagery acquired from a remotely piloted aerial system (RPAS, and the derived spectral indices to assess the vegetative, productive, and berry composition spatial variability within a vineyard (Vitis vinifera L.. Multi-spectral imagery of 17 cm spatial resolution was acquired using a RPAS. Classical vegetation spectral indices and two newly defined normalised indices, NVI1 = (R802 − R531/(R802 + R531 and NVI2 = (R802 − R570/(R802 + R570, were computed. Their spatial distribution and relationships with grapevine vegetative, yield, and berry composition parameters were studied. Most of the spectral indices and field data varied spatially within the vineyard, as showed through the variogram parameters. While the correlations were significant but moderate among the spectral indices and the field variables, the kappa index showed that the spatial pattern of the spectral indices agreed with that of the vegetative variables (0.38–0.70 and mean cluster weight (0.40. These results proved the utility of the multi-spectral imagery acquired from a RPAS to delineate homogeneous zones within the vineyard, allowing the grapegrower to carry out a specific management of each subarea.

  8. Errors from Image Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Wood, William Monford [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)


    Presenting a systematic study of the standard analysis of rod-pinch radiographs for obtaining quantitative measurements of areal mass densities, and making suggestions for improving the methodology of obtaining quantitative information from radiographed objects.

  9. Basic image analysis and manipulation in ImageJ. (United States)

    Hartig, Sean M


    Image analysis methods have been developed to provide quantitative assessment of microscopy data. In this unit, basic aspects of image analysis are outlined, including software installation, data import, image processing functions, and analytical tools that can be used to extract information from microscopy data using ImageJ. Step-by-step protocols for analyzing objects in a fluorescence image and extracting information from two-color tissue images collected by bright-field microscopy are included.

  10. Document image analysis: A primer

    Indian Academy of Sciences (India)

    Rangachar Kasturi; Lawrence O’Gorman; Venu Govindaraju


    Document image analysis refers to algorithms and techniques that are applied to images of documents to obtain a computer-readable description from pixel data. A well-known document image analysis product is the Optical Character Recognition (OCR) software that recognizes characters in a scanned document. OCR makes it possible for the user to edit or search the document’s contents. In this paper we briefly describe various components of a document analysis system. Many of these basic building blocks are found in most document analysis systems, irrespective of the particular domain or language to which they are applied. We hope that this paper will help the reader by providing the background necessary to understand the detailed descriptions of specific techniques presented in other papers in this issue.

  11. Pocket pumped image analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kotov, I.V., E-mail: [Brookhaven National Laboratory, Upton, NY 11973 (United States); O' Connor, P. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Murray, N. [Centre for Electronic Imaging, Open University, Milton Keynes, MK7 6AA (United Kingdom)


    The pocket pumping technique is used to detect small electron trap sites. These traps, if present, degrade CCD charge transfer efficiency. To reveal traps in the active area, a CCD is illuminated with a flat field and, before image is read out, accumulated charges are moved back and forth number of times in parallel direction. As charges are moved over a trap, an electron is removed from the original pocket and re-emitted in the following pocket. As process repeats one pocket gets depleted and the neighboring pocket gets excess of charges. As a result a “dipole” signal appears on the otherwise flat background level. The amplitude of the dipole signal depends on the trap pumping efficiency. This paper is focused on trap identification technique and particularly on new methods developed for this purpose. The sensor with bad segments was deliberately chosen for algorithms development and to demonstrate sensitivity and power of new methods in uncovering sensor defects.

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

    Directory of Open Access Journals (Sweden)

    Jana M Kainerstorfer

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

  13. Imaging spectroscopy for scene analysis

    CERN Document Server

    Robles-Kelly, Antonio


    This book presents a detailed analysis of spectral imaging, describing how it can be used for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications. Features: discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation; examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery; describes

  14. Synthetically Evaluation System for Multi-source Image Fusion and Experimental Analysis

    Institute of Scientific and Technical Information of China (English)

    XIAO Gang; JING Zhong-liang; WU Jian-min; LIU Cong-yi


    Study on the evaluation system for multi-source image fusion is an important and necessary part of image fusion. Qualitative evaluation indexes and quantitative evaluation indexes were studied. A series of new concepts,such as independent single evaluation index, union single evaluation index, synthetic evaluation index were proposed. Based on these concepts, synthetic evaluation system for digital image fusion was formed. The experiments with the wavelet fusion method, which was applied to fuse the multi-spectral image and panchromatic remote sensing image, the IR image and visible image, the CT and MRI image, and the multi-focus images show that it is an objective, uniform and effective quantitative method for image fusion evaluation.

  15. Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

    Institute of Scientific and Technical Information of China (English)

    LIU Yongxue; LI Manchun; MAO Liang; XU Feifei; HUANG Shuo


    With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed information classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of methodology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS information classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

  16. Multivariate image analysis in biomedicine. (United States)

    Nattkemper, Tim W


    In recent years, multivariate imaging techniques are developed and applied in biomedical research in an increasing degree. In research projects and in clinical studies as well m-dimensional multivariate images (MVI) are recorded and stored to databases for a subsequent analysis. The complexity of the m-dimensional data and the growing number of high throughput applications call for new strategies for the application of image processing and data mining to support the direct interactive analysis by human experts. This article provides an overview of proposed approaches for MVI analysis in biomedicine. After summarizing the biomedical MVI techniques the two level framework for MVI analysis is illustrated. Following this framework, the state-of-the-art solutions from the fields of image processing and data mining are reviewed and discussed. Motivations for MVI data mining in biology and medicine are characterized, followed by an overview of graphical and auditory approaches for interactive data exploration. The paper concludes with summarizing open problems in MVI analysis and remarks upon the future development of biomedical MVI analysis.

  17. Quantitative histogram analysis of images (United States)

    Holub, Oliver; Ferreira, Sérgio T.


    A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for

  18. A multi-spectral optical system (1.55μm and 8 - 12μm) of GASIR ®1 design and coating aspects (United States)

    Zadravec, Dusan; Franks, John W.; Rogers, Kenneth A.; Hendry, Alec F.; Drach, Patrick


    Small size and low weight are among the main drivers in modern military hand-held applications. Consequently, design-ers of such systems strive for combining multiple optical and electronic functions into the same piece of hardware. Present paper deals with the partial integration of an eye safe laser rangefinder into an optical channel for uncooled thermal imager using UMICORE's GASIR® optics. GASIR® is a chalcogenide glass with a transmission window from 0.8-15 µm, making it an effective material for use in near infrared, mid-wave infrared and far infrared applications. Due to the fact that uncooled sensors in the LWIR spectral band require optics with low f/numbers and that laser range-finders typically need a larger receiver aperture - in order to comply with the maximum range requirement - this ap-proach at first sight promises favorable synergies. However, it soon turns out that such a dual band approach makes life for the rangefinder part of the job difficult - by imposing special surface types required for achieving optical specifica-tions of the thermal channel, which may deteriorate the beam quality of the laser light as well as by introducing special coatings with potentially insufficient transmission at the specific laser wavelength. Several design versions have been developed and evaluated with the purpose of finding optimal balance between image quality of the thermal channel and the laser rangefinder performance. In this paper various optical and coating design aspects will be addressed together with the limitations of such a multi-spectral approach.

  19. 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.

  20. Signal and image multiresolution analysis

    CERN Document Server

    Ouahabi, Abdelialil


    Multiresolution analysis using the wavelet transform has received considerable attention in recent years by researchers in various fields. It is a powerful tool for efficiently representing signals and images at multiple levels of detail with many inherent advantages, including compression, level-of-detail display, progressive transmission, level-of-detail editing, filtering, modeling, fractals and multifractals, etc.This book aims to provide a simple formalization and new clarity on multiresolution analysis, rendering accessible obscure techniques, and merging, unifying or completing

  1. Multi-Source Image Analysis. (United States)


    Laboratories, Fort Belvoir, Virginia. Estes, J. E., and L. W. Senger (eds.), 1974, Remote Sensing: Techniques for environmental analysis, Hamilton, Santa ...E. and W. Senger (eds.), Remote Sensing Techniques in Environmental Analysis, Santa Barbara, California, Hamilton Publishing Co., p. 127-165. Morain...The large body of water labeled "W" on each image represents the Agua Hedionda lagoon. East of the lagoon the area is primarily agricultural with a

  2. Teaching image analysis at DIKU

    DEFF Research Database (Denmark)

    Johansen, Peter


    The early development of computer vision at Department of Computer Science at University of Copenhagen (DIKU) is briefly described. The different disciplines in computer vision are introduced, and the principles for teaching two courses, an image analysis course, and a robot lab class are outlined....

  3. Hyperspectral Imaging of Functional Patterns for Disease Assessment and Treatment Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Demos, S; Hattery, D; Hassan, M; Aleman, K; Little, R; Yarchoan, R; Gandjbakhche, A


    We have designed and built a six-band multi-spectral NIR imaging system used in clinical testing on cancer patients. From our layered tissue model, we create blood volume and blood oxygenation images for patient treatment monitoring.

  4. Lossless, Multi-Spectral Data Compressor for Improved Compression for Pushbroom-Type Instruments (United States)

    Klimesh, Matthew


    A low-complexity lossless algorithm for compression of multispectral data has been developed that takes into account pushbroom-type multispectral imagers properties in order to make the file compression more effective.

  5. Astronomical Image and Data Analysis

    CERN Document Server

    Starck, J.-L


    With information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis using a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field and draw upon decades of experience. They have been playing leading roles in international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools. This second edition of Starck and Murtagh's highly appreciated reference again deals with to...

  6. Ortho-Rectification of Narrow Band Multi-Spectral Imagery Assisted by Dslr RGB Imagery Acquired by a Fixed-Wing Uas (United States)

    Rau, J.-Y.; Jhan, J.-P.; Huang, C.-Y.


    Miniature Multiple Camera Array (MiniMCA-12) is a frame-based multilens/multispectral sensor composed of 12 lenses with narrow band filters. Due to its small size and light weight, it is suitable to mount on an Unmanned Aerial System (UAS) for acquiring high spectral, spatial and temporal resolution imagery used in various remote sensing applications. However, due to its wavelength range is only 10 nm that results in low image resolution and signal-to-noise ratio which are not suitable for image matching and digital surface model (DSM) generation. In the meantime, the spectral correlation among all 12 bands of MiniMCA images are low, it is difficult to perform tie-point matching and aerial triangulation at the same time. In this study, we thus propose the use of a DSLR camera to assist automatic aerial triangulation of MiniMCA-12 imagery and to produce higher spatial resolution DSM for MiniMCA12 ortho-image generation. Depending on the maximum payload weight of the used UAS, these two kinds of sensors could be collected at the same time or individually. In this study, we adopt a fixed-wing UAS to carry a Canon EOS 5D Mark2 DSLR camera and a MiniMCA-12 multi-spectral camera. For the purpose to perform automatic aerial triangulation between a DSLR camera and the MiniMCA-12, we choose one master band from MiniMCA-12 whose spectral range has overlap with the DSLR camera. However, all lenses of MiniMCA-12 have different perspective centers and viewing angles, the original 12 channels have significant band misregistration effect. Thus, the first issue encountered is to reduce the band misregistration effect. Due to all 12 MiniMCA lenses being frame-based, their spatial offsets are smaller than 15 cm and all images are almost 98% overlapped, we thus propose a modified projective transformation (MPT) method together with two systematic error correction procedures to register all 12 bands of imagery on the same image space. It means that those 12 bands of images acquired at

  7. Automated image analysis techniques for cardiovascular magnetic resonance imaging

    NARCIS (Netherlands)

    Geest, Robertus Jacobus van der


    The introductory chapter provides an overview of various aspects related to quantitative analysis of cardiovascular MR (CMR) imaging studies. Subsequently, the thesis describes several automated methods for quantitative assessment of left ventricular function from CMR imaging studies. Several novel

  8. Image analysis in medical imaging: recent advances in selected examples (United States)

    Dougherty, G


    Medical imaging has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerised medical image visualisation and advances in analysis methods and computer-aided diagnosis. Several research applications are selected to illustrate the advances in image analysis algorithms and visualisation. Recent results, including previously unpublished data, are presented to illustrate the challenges and ongoing developments. PMID:21611048

  9. 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....

  10. 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....

  11. Surface temperature measurement of the plasma facing components with the multi-spectral infrared thermography diagnostics in tokamaks (United States)

    Zhang, C.; Gauthier, E.; Pocheau, C.; Balorin, C.; Pascal, J. Y.; Jouve, M.; Aumeunier, M. H.; Courtois, X.; Loarer, Th.; Houry, M.


    For the long-pulse high-confinement discharges in tokamaks, the equilibrium of plasma requires a contact with the first wall materials. The heat flux resulting from this interaction is of the order of 10 MW/m2 for steady state conditions and up to 20 MW/m2 for transient phases. The monitoring on surface temperatures of the plasma facing components (PFCs) is a major concern to ensure safe operation and to optimize performances of experimental operations on large fusion facilities. Furthermore, this measurement is also required to study the physics associated to the plasma material interactions and the heat flux deposition process. In tokamaks, infrared (IR) thermography systems are routinely used to monitor the surface temperature of the PFCs. This measurement requires an accurate knowledge of the surface emissivity. However, and particularly for metallic materials such as tungsten, this emissivity value can vary over a wide range with both the surface condition and the temperature itself, which makes instantaneous measurement challenging. In this context, the multi-spectral infrared method appears as a very promising alternative solution. Indeed, the system has the advantage to carry out a non-intrusive measurement on thermal radiation while evaluating surface temperature without requiring a mandatory surface emissivity measurement. In this paper, a conceptual design for the multi-spectral infrared thermography is proposed. The numerical study of the multi-channel system based on the Levenberg-Marquardt (LM) nonlinear curve fitting is applied. The numerical results presented in this paper demonstrate the design allows for measurements over a large temperature range with a relative error of less than 10%. Furthermore, laboratory experiments have been performed from 200 °C to 740 °C to confirm the feasibility for temperature measurements on stainless steel and tungsten. In these experiments, the unfolding results from the multi-channel detection provide good

  12. Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

    Directory of Open Access Journals (Sweden)

    D. Martynenko


    Full Text Available An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo.

    The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008 there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper.

    The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to

  13. Aerosol Properties from Multi-spectral and Multi-angular Aircraft 4STAR Observations: Expected Advantages and Challenges

    Energy Technology Data Exchange (ETDEWEB)

    Kassianov, Evgueni I.; Flynn, Connor J.; Redemann, Jens; Schmid, Beat; Russell, P. B.; Sinyuk, Alexander


    The airborne Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) is developed to retrieve aerosol microphysical and optical properties from multi-angular and multi-spectral measurements of sky radiance and direct-beam sun transmittance. The necessarily compact design of the 4STAR may cause noticeable apparent enhancement of sky radiance at small scattering angles. We assess the sensitivity of expected 4STAR-based aerosol retrieval to such enhancement by applying the operational AERONET retrieval code and constructed synthetic 4STARlike data. Also, we assess the sensitivity of the broadband fluxes and the direct aerosol radiative forcing to uncertainties in aerosol retrievals associated with the sky radiance enhancement. Our sensitivity study results suggest that the 4STARbased aerosol retrieval has limitations in obtaining detailed information on particle size distribution and scattering phase function. However, these limitations have small impact on the retrieved bulk optical parameters, such as the asymmetry factor (up to 4%, or ±0.02) and single-scattering albedo (up to 2%, or ±0.02), and the calculated direct aerosol radiative forcing (up to 6%, or 2 Wm-2).

  14. Classification of Astaxanthin Colouration of Salmonid Fish using Spectral Imaging and Tricolour Measurement

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Dissing, Bjørn Skovlund; Nielsen, Michael Engelbrecht

    The goal of this study was to investigate if it is possible to differentiate between rainbow trout (Oncorhynchus mykiss) having been fed with natural or synthetic astaxanthin. Three different techniques were used for visual inspection of the surface colour of the fish meat: multi-spectral image...... capturing, tricolour CIELAB measurement, and manual SalmoFan inspection. Furthermore it was tested whether the best predictions come from measurements of the steak or the fillet of the fish. Methods used for classication were linear discriminant analysis (LDA), quadratic discriminant analysis (QDA......), and sparse linear discriminant analysis (SLDA)....

  15. High-resolution image analysis. (United States)

    Preston, K


    In many departments of cytology, cytogenetics, hematology, and pathology, research projects using high-resolution computerized microscopy are now being mounted for computation of morphometric measurements on various structural components, as well as for determination of cellular DNA content. The majority of these measurements are made in a partially automated, computer-assisted mode, wherein there is strong interaction between the user and the computerized microscope. At the same time, full automation has been accomplished for both sample preparation and sample examination for clinical determination of the white blood cell differential count. At the time of writing, approximately 1,000 robot differential counting microscopes are in the field, analyzing images of human white blood cells, red blood cells, and platelets at the overall rate of about 100,000 slides per day. This mammoth through-put represents a major accomplishment in the application of machine vision to automated microscopy for hematology. In other areas of automated high-resolution microscopy, such as cytology and cytogenetics, no commercial instruments are available (although a few metaphase-finding machines are available and other new machines have been announced during the past year). This is a disappointing product, considering the nearly half century of research effort in these areas. This paper provides examples of the state of the art in automation of cell analysis for blood smears, cervical smears, and chromosome preparations. Also treated are new developments in multi-resolution automated microscopy, where images are now being generated and analyzed by a single machine over a range of 64:1 magnification and from 10,000 X 20,000 to 500 X 500 in total picture elements (pixels). Examples of images of human lymph node and liver tissue are presented. Semi-automated systems are not treated, although there is mention of recent research in the automation of tissue analysis.

  16. New, Flexible Applications with the Multi-Spectral Titan Airborne Lidar (United States)

    Swirski, A.; LaRocque, D. P.; Shaker, A.; Smith, B.


    Traditional lidar designs have been restricted to using a single laser channel operating at one particular wavelength. Single-channel systems excel at collecting high-precision spatial (XYZ) data, with accuracies down to a few centimeters. However, target classification is difficult with spatial data alone, and single-wavelength systems are limited to the strengths and weaknesses of the wavelength they use. To resolve these limitations in lidar design, Teledyne Optech developed the Titan, the world's first multispectral lidar system, which uses three independent laser channels operating at 532, 1064, and 1550 nm. Since Titan collects 12 bit intensity returns for each wavelength separately, users can compare how strongly targets in the survey area reflect each wavelength. Materials such as soil, rock and foliage all reflect the wavelengths differently, enabling post-processing algorithms to identify the material of targets easily and automatically. Based on field tests in Canada, automated classification algorithms have combined this with elevation data to classify targets into six basic types with 78% accuracy. Even greater accuracy is possible with further algorithm enhancement and the use of an in-sensor passive imager such as a thermal, multispectral, CIR or RGB camera. Titan therefore presents an important new tool for applications such as land-cover classification and environmental modeling while maintaining lidar's traditional strengths: high 3D accuracy and day/night operation. Multispectral channels also enable a single lidar to handle both topographic and bathymetric surveying efficiently, which previously required separate specialized lidar systems operating at different wavelengths. On land, Titan can survey efficiently from 2000 m AGL with a 900 kHz PRF (300 kHz per channel), or up to 2500 m if only the infrared 1064 and 1550 nm channels are used. Over water, the 532 nm green channel penetrates water to collect seafloor returns while the infrared

  17. A method for comparison of growth media in objective identification of Penicillium based on multi-spectral imaging

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Hansen, Michael Adsetts Edberg; Frisvad, Jens Christian


    We consider the problems of using excessive growth media for identification and performing objective identification of fungi at the species level. We propose a method for choosing the subset of growth media, which provides the best discrimination between several fungal species. Furthermore, we...

  18. Information Retrieval from SAGE II and MFRSR Multi-Spectral Extinction Measurements (United States)

    Lacis, Andrew A.; Hansen, James E. (Technical Monitor)


    Direct beam spectral extinction measurements of solar radiation contain important information on atmospheric composition in a form that is essentially free from multiple scattering contributions that otherwise tend to complicate the data analysis and information retrieval. Such direct beam extinction measurements are available from the solar occultation satellite-based measurements made by the Stratospheric and Aerosol Gas Experiment (SAGE II) instrument and by ground-based Multi-Filter Shadowband Radiometers (MFRSRs). The SAGE II data provide cross-sectional slices of the atmosphere twice per orbit at seven wavelengths between 385 and 1020 nm with approximately 1 km vertical resolution, while the MFRSR data provide atmospheric column measurements at six wavelengths between 415 and 940 nm but at one minute time intervals. We apply the same retrieval technique of simultaneous least-squares fit to the observed spectral extinctions to retrieve aerosol optical depth, effective radius and variance, and ozone, nitrogen dioxide, and water vapor amounts from the SAGE II and MFRSR measurements. The retrieval technique utilizes a physical model approach based on laboratory measurements of ozone and nitrogen dioxide extinction, line-by-line and numerical k-distribution calculations for water vapor absorption, and Mie scattering constraints on aerosol spectral extinction properties. The SAGE II measurements have the advantage of being self-calibrating in that deep space provides an effective zero point for the relative spectral extinctions. The MFRSR measurements require periodic clear-day Langley regression calibration events to maintain accurate knowledge of instrument calibration.

  19. Principles and clinical applications of image analysis. (United States)

    Kisner, H J


    Image processing has traveled to the lunar surface and back, finding its way into the clinical laboratory. Advances in digital computers have improved the technology of image analysis, resulting in a wide variety of medical applications. Offering improvements in turnaround time, standardized systems, increased precision, and walkaway automation, digital image analysis has likely found a permanent home as a diagnostic aid in the interpretation of microscopic as well as macroscopic laboratory images.

  20. A reasoning system for image analysis

    Directory of Open Access Journals (Sweden)

    Gao Jin Sheng


    Full Text Available For image analysis in computer, the traditional approach is extracting and transcoding features after image segmentation. However, in this paper, we present a different way to analyze image. We adopt spatial logic technology to establish a reasoning system with corresponding semantic model, and prove its soundness and completeness, and then realize the image analysis in formal way. And it can be applied in artificial intelligence. This is a new attempt and also a challenging approach.

  1. 基于ICA的遥感图像的色彩分类方法%Classification of Remote Sensing Image Based on Independent Components Analysis

    Institute of Scientific and Technical Information of China (English)

    赵蔷; 刘淑英; 李红


    根据独立成分分析( ICA)方法和多频谱卫星遥感图像的特点,提出了一种基于ICA的遥感图像色彩分类法。方法使用Fast ICA算法提取遥感图像的色彩独立成分,是RGB反转的结合,具有互补的分布,不受照明的影响。使用最大相似度分类算法对像素进行色彩分类,实验结果表明,方法的色彩分类效果较好,对多频谱遥感图像进行色彩分类十分有效。%This article propose a classification algorithm for satellite remote sensing images based on Inde-pendent Components Analysis ( ICA) .The algorithm combines the advantage of ICA and multispectral re-motely sensed images .The algorithm extracts the spectral independent components of multispectral re-motely sensed images by Fast ICA algorithm .It is the combine of reversion about R ,G and B,has comple-mentary distribution and is unacted on illumination .Maximum Likelihood is used to classify the pixels . Experimental results demonstrate that the algorithm is an effective improve method to classify the multi-spectral remotely sensed images .

  2. One Approach to intellectual image analysis

    Directory of Open Access Journals (Sweden)

    Bellustin Nikolai


    Full Text Available This study investigated the method of semantic image analysis by using a set of neuron-like detectors of foreground objects. This method is intended to find different types of foreground objects and to determine properties of these objects. As a result of semantic analysis the semantic descriptor of the image is created. The descriptor is a set of foreground objects of the image and a set of properties for each object. The distance between images is defined as distance between their semantic descriptors. Using the concept of distance between images, “semantically similarity” between images or videos is defined.

  3. Image analysis: a consumer's guide. (United States)

    Meyer, F


    The last years have seen an explosion of systems in image analysis. It is hard for the pathologist or the cytologist to make the right choice of equipment. All machines are stupid, and the only valuable thing is the human work put into it. So make your benefit of the work other people have done for you. Chose a method largely used on many systems and which has proved fertile in many domains and not only for your specific to day's application: Mathematical Morphology, to which are to be added the linear convolutions present on all machines is a strong candidate for becoming such a method. The paper illustrates a working day of an ideal system: research and diagnostic directed work during the working hours, automatic screening of cervical (or other) smears during night.

  4. Clock Scan Protocol for Image Analysis: ImageJ Plugins. (United States)

    Dobretsov, Maxim; Petkau, Georg; Hayar, Abdallah; Petkau, Eugen


    The clock scan protocol for image analysis is an efficient tool to quantify the average pixel intensity within, at the border, and outside (background) a closed or segmented convex-shaped region of interest, leading to the generation of an averaged integral radial pixel-intensity profile. This protocol was originally developed in 2006, as a visual basic 6 script, but as such, it had limited distribution. To address this problem and to join similar recent efforts by others, we converted the original clock scan protocol code into two Java-based plugins compatible with NIH-sponsored and freely available image analysis programs like ImageJ or Fiji ImageJ. Furthermore, these plugins have several new functions, further expanding the range of capabilities of the original protocol, such as analysis of multiple regions of interest and image stacks. The latter feature of the program is especially useful in applications in which it is important to determine changes related to time and location. Thus, the clock scan analysis of stacks of biological images may potentially be applied to spreading of Na(+) or Ca(++) within a single cell, as well as to the analysis of spreading activity (e.g., Ca(++) waves) in populations of synaptically-connected or gap junction-coupled cells. Here, we describe these new clock scan plugins and show some examples of their applications in image analysis.

  5. Analysis of Dynamic Brain Imaging Data

    CERN Document Server

    Mitra, P


    Modern imaging techniques for probing brain function, including functional Magnetic Resonance Imaging, intrinsic and extrinsic contrast optical imaging, and magnetoencephalography, generate large data sets with complex content. In this paper we develop appropriate techniques of analysis and visualization of such imaging data, in order to separate the signal from the noise, as well as to characterize the signal. The techniques developed fall into the general category of multivariate time series analysis, and in particular we extensively use the multitaper framework of spectral analysis. We develop specific protocols for the analysis of fMRI, optical imaging and MEG data, and illustrate the techniques by applications to real data sets generated by these imaging modalities. In general, the analysis protocols involve two distinct stages: `noise' characterization and suppression, and `signal' characterization and visualization. An important general conclusion of our study is the utility of a frequency-based repres...

  6. Image registration with uncertainty analysis (United States)

    Simonson, Katherine M.


    In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

  7. 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.

  8. Retinal image analysis: preprocessing and feature extraction

    Energy Technology Data Exchange (ETDEWEB)

    Marrugo, Andres G; Millan, Maria S, E-mail: [Grup d' Optica Aplicada i Processament d' Imatge, Departament d' Optica i Optometria Univesitat Politecnica de Catalunya (Spain)


    Image processing, analysis and computer vision techniques are found today in all fields of medical science. These techniques are especially relevant to modern ophthalmology, a field heavily dependent on visual data. Retinal images are widely used for diagnostic purposes by ophthalmologists. However, these images often need visual enhancement prior to apply a digital analysis for pathological risk or damage detection. In this work we propose the use of an image enhancement technique for the compensation of non-uniform contrast and luminosity distribution in retinal images. We also explore optic nerve head segmentation by means of color mathematical morphology and the use of active contours.

  9. Hyperspectral image classification using functional data analysis. (United States)

    Li, Hong; Xiao, Guangrun; Xia, Tian; Tang, Y Y; Li, Luoqing


    The large number of spectral bands acquired by hyperspectral imaging sensors allows us to better distinguish many subtle objects and materials. Unlike other classical hyperspectral image classification methods in the multivariate analysis framework, in this paper, a novel method using functional data analysis (FDA) for accurate classification of hyperspectral images has been proposed. The central idea of FDA is to treat multivariate data as continuous functions. From this perspective, the spectral curve of each pixel in the hyperspectral images is naturally viewed as a function. This can be beneficial for making full use of the abundant spectral information. The relevance between adjacent pixel elements in the hyperspectral images can also be utilized reasonably. Functional principal component analysis is applied to solve the classification problem of these functions. Experimental results on three hyperspectral images show that the proposed method can achieve higher classification accuracies in comparison to some state-of-the-art hyperspectral image classification methods.

  10. Fractal methods in image analysis and coding


    Neary, David


    In this thesis we present an overview of image processing techniques which use fractal methods in some way. We show how these fields relate to each other, and examine various aspects of fractal methods in each area. The three principal fields of image processing and analysis th a t we examine are texture classification, image segmentation and image coding. In the area of texture classification, we examine fractal dimension estimators, comparing these methods to other methods in use, a...

  11. Neural Network Based on Rough Sets and Its Application to Remote Sensing Image Classification

    Institute of Scientific and Technical Information of China (English)


    This paper presents a new kind of back propagation neural network (BPNN) based on rough sets,called rough back propagation neural network (RBPNN).The architecture and training method of RBPNN are presented and the survey and analysis of RBPNN for the classification of remote sensing multi-spectral image is discussed.The successful application of RBPNN to a land cover classification illustrates the simple computation and high accuracy of the new neural network and the flexibility and practicality of this new approach.

  12. Merging Panchromatic and Multispectral Images for Enhanced Image Analysis (United States)


    Multispectral Images for Enhanced Image Analysis I, Curtis K. Munechika grant permission to the Wallace Memorial Library of the Rochester Institute of...0.0 ()0 (.0(%C’ trees 3. 5 2.5% 0.0%l 44. 1% 5 (.()0th ,crass .1 ().W 0.0% 0).0% 97. overall classification accuracy: 87.5%( T-able DlIb . Confusion

  13. Solar Image Analysis and Visualization

    CERN Document Server

    Ireland, J


    This volume presents a selection of papers on the state of the art of image enhancement, automated feature detection, machine learning, and visualization tools in support of solar physics that focus on the challenges presented by new ground-based and space-based instrumentation. The articles and topics were inspired by the Third Solar Image Processing Workshop, held at Trinity College Dublin, Ireland but contributions from other experts have been included as well. This book is mainly aimed at researchers and graduate students working on image processing and compter vision in astronomy and solar physics.

  14. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

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


    only with fish oil. In this study, multispectral image analysis of pellets captured reflection in 20 wavelengths (385–1050 nm). Linear discriminant analysis (LDA), principal component analysis, and support vector machine were used as statistical analysis. The features extracted from the multispectral...

  15. Natural user interfaces in medical image analysis cognitive analysis of brain and carotid artery images

    CERN Document Server

    Ogiela, Marek R


    This unique text/reference highlights a selection of practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing and interpreting diagnostic results of sample CT images. The text also presents significant problems related to new approaches and paradigms in image understanding and semantic image analysis. To further engage the reader, example source code is provided for the implemented algorithms in the described solutions. Features: describes the most important methods and algorithms used for image analysis; e

  16. Imaging flow cytometry for phytoplankton analysis. (United States)

    Dashkova, Veronika; Malashenkov, Dmitry; Poulton, Nicole; Vorobjev, Ivan; Barteneva, Natasha S


    This review highlights the concepts and instrumentation of imaging flow cytometry technology and in particular its use for phytoplankton analysis. Imaging flow cytometry, a hybrid technology combining speed and statistical capabilities of flow cytometry with imaging features of microscopy, is rapidly advancing as a cell imaging platform that overcomes many of the limitations of current techniques and contributed significantly to the advancement of phytoplankton analysis in recent years. This review presents the various instrumentation relevant to the field and currently used for assessment of complex phytoplankton communities' composition and abundance, size structure determination, biovolume estimation, detection of harmful algal bloom species, evaluation of viability and metabolic activity and other applications. Also we present our data on viability and metabolic assessment of Aphanizomenon sp. cyanobacteria using Imagestream X Mark II imaging cytometer. Herein, we highlight the immense potential of imaging flow cytometry for microalgal research, but also discuss limitations and future developments.

  17. Digital Image Analysis for Detechip Code Determination

    Directory of Open Access Journals (Sweden)

    Marcus Lyon


    Full Text Available DETECHIP® is a molecular sensing array used for identification of a large variety of substances. Previous methodology for the analysis of DETECHIP® used human vision to distinguish color changes induced by the presence of the analyte of interest. This paper describes several analysis techniques using digital images of DETECHIP® . Both a digital camera and flatbed desktop photo scanner were used to obtain Jpeg images. Color information within these digital images was obtained through the measurement of redgreen-blue (RGB values using software such as GIMP, Photoshop and ImageJ. Several different techniques were used to evaluate these color changes. It was determined that the flatbed scanner produced in the clearest and more reproducible images. Furthermore, codes obtained using a macro written for use within ImageJ showed improved consistency versus pervious methods.

  18. Theory of Image Analysis and Recognition. (United States)


    Narendra Ahuja Image models Ramalingam Chellappa Image models Matti Pietikainen * Texture analysis b David G. Morgenthaler’ 3D digital geometry c Angela Y. Wu...Restoration Parameter Choice A Quantitative Guide," TR-965, October 1980. 70. Matti Pietikainen , "On the Use of Hierarchically Computed ’Mexican Hat...81. Matti Pietikainen and Azriel Rosenfeld, "Image Segmenta- tion by Texture Using Pyramid Node Linking," TR-1008, February 1981. 82. David G. 1

  19. NIH Image to ImageJ: 25 years of image analysis. (United States)

    Schneider, Caroline A; Rasband, Wayne S; Eliceiri, Kevin W


    For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.

  20. Statistical Smoothing Methods and Image Analysis (United States)


    83 - 111. Rosenfeld, A. and Kak, A.C. (1982). Digital Picture Processing. Academic Press,Qrlando. Serra, J. (1982). Image Analysis and Mat hematical ...hypothesis testing. IEEE Trans. Med. Imaging, MI-6, 313-319. Wicksell, S.D. (1925) The corpuscle problem. A mathematical study of a biometric problem

  1. Simulation Analysis of Cylindrical Panoramic Image Mosaic

    Directory of Open Access Journals (Sweden)

    ZHU Ningning


    Full Text Available With the rise of virtual reality (VR technology, panoramic images are used more widely, which obtained by multi-camera stitching and take advantage of homography matrix and image transformation, however, this method will destroy the collinear condition, make it's difficult to 3D reconstruction and other work. This paper proposes a new method for cylindrical panoramic image mosaic, which set the number of mosaic camera, imaging focal length, imaging position and imaging attitude, simulate the mapping process of multi-camera and construct cylindrical imaging equation from 3D points to 2D image based on photogrammetric collinearity equations. This cylindrical imaging equation can not only be used for panoramic stitching, but also be used for precision analysis, test results show: ①this method can be used for panoramic stitching under the condition of multi-camera and incline imaging; ②the accuracy of panoramic stitching is affected by 3 kinds of parameter errors including focus, displacement and rotation angle, in which focus error can be corrected by image resampling, displacement error is closely related to object distance and rotation angle error is affected mainly by the number of cameras.

  2. Malware Analysis Using Visualized Image Matrices

    Directory of Open Access Journals (Sweden)

    KyoungSoo Han


    Full Text Available This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

  3. Scale-Specific Multifractal Medical Image Analysis

    Directory of Open Access Journals (Sweden)

    Boris Braverman


    irregular complex tissue structures that do not lend themselves to straightforward analysis with traditional Euclidean geometry. In this study, we treat the nonfractal behaviour of medical images over large-scale ranges by considering their box-counting fractal dimension as a scale-dependent parameter rather than a single number. We describe this approach in the context of the more generalized Rényi entropy, in which we can also compute the information and correlation dimensions of images. In addition, we describe and validate a computational improvement to box-counting fractal analysis. This improvement is based on integral images, which allows the speedup of any box-counting or similar fractal analysis algorithm, including estimation of scale-dependent dimensions. Finally, we applied our technique to images of invasive breast cancer tissue from 157 patients to show a relationship between the fractal analysis of these images over certain scale ranges and pathologic tumour grade (a standard prognosticator for breast cancer. Our approach is general and can be applied to any medical imaging application in which the complexity of pathological image structures may have clinical value.

  4. Hybrid Expert Systems In Image Analysis (United States)

    Dixon, Mark J.; Gregory, Paul J.


    Vision systems capable of inspecting industrial components and assemblies have a large potential market if they can be easily programmed and produced quickly. Currently, vision application software written in conventional high-level languages such as C or Pascal are produced by experts in program design, image analysis, and process control. Applications written this way are difficult to maintain and modify. Unless other similar inspection problems can be found, the final program is essentially one-off redundant code. A general-purpose vision system targeted for the Visual Machines Ltd. C-VAS 3000 image processing workstation, is described which will make writing image analysis software accessible to the non-expert both in programming computers and image analysis. A significant reduction in the effort required to produce vision systems, will be gained through a graphically-driven interactive application generator. Finally, an Expert System will be layered on top to guide the naive user through the process of generating an application.

  5. EMD Based Multi-scale Model for High Resolution Image Fusion%基于经验模态分解的高分辨率影像融合

    Institute of Scientific and Technical Information of China (English)

    王坚; 张继贤; 刘正军


    High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition (EMD). The intensity hue saturation (IHS) trans- form of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After pre- senting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion tech- nique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function (IMF) for the merger on the basis of EMD analysis on specific row (column) pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms (wavelet, IHS, Brovey). The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience.

  6. Color Standardization Method and System for Whole Slide Imaging Based on Spectral Sensing

    Directory of Open Access Journals (Sweden)

    Shinsuke Tani


    Full Text Available In the field of whole slide imaging, the imaging device or staining process cause color variations for each slide that affect the result of image analysis made by pathologist. In order to stabilize the analysis, we developed a color standardization method and system as described below: 1 Color standardization method based on RGB imaging and multi spectral sensing, which utilize less band (16 bands than conventional method (60 bands, 2 High speed spectral sensing module. As a result, we confirmed the following effect: 1 We confirmed the performance improvement of nucleus detection by the color standardization. And we can conduct without training data set which is needed in conventional method, 2 We can get detection performance of H&E component equivalent to conventional method (60 bands. And measurement process is more than 255 times faster.

  7. Quantitative analysis of qualitative images (United States)

    Hockney, David; Falco, Charles M.


    We show optical evidence that demonstrates artists as early as Jan van Eyck and Robert Campin (c1425) used optical projections as aids for producing their paintings. We also have found optical evidence within works by later artists, including Bermejo (c1475), Lotto (c1525), Caravaggio (c1600), de la Tour (c1650), Chardin (c1750) and Ingres (c1825), demonstrating a continuum in the use of optical projections by artists, along with an evolution in the sophistication of that use. However, even for paintings where we have been able to extract unambiguous, quantitative evidence of the direct use of optical projections for producing certain of the features, this does not mean that paintings are effectively photographs. Because the hand and mind of the artist are intimately involved in the creation process, understanding these complex images requires more than can be obtained from only applying the equations of geometrical optics.

  8. Parallel Computing for the Computed-Tomography Imaging Spectrometer (United States)

    Lee, Seungwon


    This software computes the tomographic reconstruction of spatial-spectral data from raw detector images of the Computed-Tomography Imaging Spectrometer (CTIS), which enables transient-level, multi-spectral imaging by capturing spatial and spectral information in a single snapshot.

  9. Vortex Image Processing (VIP) package for high-contrast direct imaging (United States)

    Gomez Gonzalez, C.; Absil, O.; Wertz, O.


    VIP is a Python instrument-agnostic toolbox featuring a flexible framework for reproducible and robust data reduction. VIP currently supports three high-contrast imaging observational techniques: angular, reference-star and multi-spectral differential imaging. The code can be downloaded from our git repository on Github:

  10. Design Criteria For Networked Image Analysis System (United States)

    Reader, Cliff; Nitteberg, Alan


    Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

  11. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

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


    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. The pellets were divided into two groups: one with pellets coated using synthetic astaxanthin in fish oil and the other with pellets coated...... images were pixel spectral values as well as using summary statistics such as the mean or median value of each pellet. Classification using LDA on pellet mean or median values showed overall good results. Multispectral imaging is a promising technique for noninvasive on-line quality food and feed...... products with optimal use of pigment and minimum amount of waste....

  12. Chromatic Image Analysis For Quantitative Thermal Mapping (United States)

    Buck, Gregory M.


    Chromatic image analysis system (CIAS) developed for use in noncontact measurements of temperatures on aerothermodynamic models in hypersonic wind tunnels. Based on concept of temperature coupled to shift in color spectrum for optical measurement. Video camera images fluorescence emitted by phosphor-coated model at two wavelengths. Temperature map of model then computed from relative brightnesses in video images of model at those wavelengths. Eliminates need for intrusive, time-consuming, contact temperature measurements by gauges, making it possible to map temperatures on complex surfaces in timely manner and at reduced cost.

  13. Cancer detection by quantitative fluorescence image analysis. (United States)

    Parry, W L; Hemstreet, G P


    Quantitative fluorescence image analysis is a rapidly evolving biophysical cytochemical technology with the potential for multiple clinical and basic research applications. We report the application of this technique for bladder cancer detection and discuss its potential usefulness as an adjunct to methods used currently by urologists for the diagnosis and management of bladder cancer. Quantitative fluorescence image analysis is a cytological method that incorporates 2 diagnostic techniques, quantitation of nuclear deoxyribonucleic acid and morphometric analysis, in a single semiautomated system to facilitate the identification of rare events, that is individual cancer cells. When compared to routine cytopathology for detection of bladder cancer in symptomatic patients, quantitative fluorescence image analysis demonstrated greater sensitivity (76 versus 33 per cent) for the detection of low grade transitional cell carcinoma. The specificity of quantitative fluorescence image analysis in a small control group was 94 per cent and with the manual method for quantitation of absolute nuclear fluorescence intensity in the screening of high risk asymptomatic subjects the specificity was 96.7 per cent. The more familiar flow cytometry is another fluorescence technique for measurement of nuclear deoxyribonucleic acid. However, rather than identifying individual cancer cells, flow cytometry identifies cellular pattern distributions, that is the ratio of normal to abnormal cells. Numerous studies by others have shown that flow cytometry is a sensitive method to monitor patients with diagnosed urological disease. Based upon results in separate quantitative fluorescence image analysis and flow cytometry studies, it appears that these 2 fluorescence techniques may be complementary tools for urological screening, diagnosis and management, and that they also may be useful separately or in combination to elucidate the oncogenic process, determine the biological potential of tumors

  14. Image analysis of insulation mineral fibres. (United States)

    Talbot, H; Lee, T; Jeulin, D; Hanton, D; Hobbs, L W


    We present two methods for measuring the diameter and length of man-made vitreous fibres based on the automated image analysis of scanning electron microscopy images. The fibres we want to measure are used in materials such as glass wool, which in turn are used for thermal and acoustic insulation. The measurement of the diameters and lengths of these fibres is used by the glass wool industry for quality control purposes. To obtain reliable quality estimators, the measurement of several hundred images is necessary. These measurements are usually obtained manually by operators. Manual measurements, although reliable when performed by skilled operators, are slow due to the need for the operators to rest often to retain their ability to spot faint fibres on noisy backgrounds. Moreover, the task of measuring thousands of fibres every day, even with the help of semi-automated image analysis systems, is dull and repetitive. The need for an automated procedure which could replace manual measurements is quite real. For each of the two methods that we propose to accomplish this task, we present the sample preparation, the microscope setting and the image analysis algorithms used for the segmentation of the fibres and for their measurement. We also show how a statistical analysis of the results can alleviate most measurement biases, and how we can estimate the true distribution of fibre lengths by diameter class by measuring only the lengths of the fibres visible in the field of view.

  15. An exact formulation of k-distribution methods in non-uniform gaseous media and its approximate treatment within the Multi-Spectral framework (United States)

    ANDRE, Frédéric; HOU, Longfeng; SOLOVJOV, Vladimir P.


    The main restriction of k-distribution approaches for applications in radiative heat transfer in gaseous media arises from the use of a scaling or correlation assumption to treat non-uniform situations. It is shown that those cases can be handled exactly by using a multidimensional k-distribution that addresses the problem of spectral correlations without using any simplifying assumptions. Nevertheless, the approach cannot be suggested for engineering applications due to its computational cost. Accordingly, a more efficient method, based on the so-called Multi-Spectral Framework, is proposed to approximate the previous exact formulation. The model is assessed against reference LBL calculations and shown to outperform usual k-distribution approaches for radiative heat transfer in non-uniform media.

  16. Medical image analysis with artificial neural networks. (United States)

    Jiang, J; Trundle, P; Ren, J


    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. Copyright © 2010 Elsevier Ltd. All rights reserved.

  17. Fourier analysis: from cloaking to imaging (United States)

    Wu, Kedi; Cheng, Qiluan; Wang, Guo Ping


    Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers.

  18. Hyperspectral Image Analysis of Food Quality

    DEFF Research Database (Denmark)

    Arngren, Morten

    Assessing the quality of food is a vital step in any food processing line to ensurethe best food quality and maximum profit for the farmer and food manufacturer.Traditional quality evaluation methods are often destructive and labourintensive procedures relying on wet chemistry or subjective human...... inspection.Near-infrared spectroscopy can address these issues by offering a fast and objectiveanalysis of the food quality. A natural extension to these single spectrumNIR systems is to include image information such that each pixel holds a NIRspectrum. This augmented image information offers several...... extensions to the analysis offood quality. This dissertation is concerned with hyperspectral image analysisused to assess the quality of single grain kernels. The focus is to highlight thebenefits and challenges of using hyperspectral imaging for food quality presentedin two research directions. Initially...

  19. Deep Learning in Medical Image Analysis. (United States)

    Shen, Dinggang; Wu, Guorong; Suk, Heung-Il


    This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement. Expected final online publication date for the Annual Review of Biomedical Engineering Volume 19 is June 4, 2017. Please see for revised estimates.

  20. Principal Components Analysis In Medical Imaging (United States)

    Weaver, J. B.; Huddleston, A. L.


    Principal components analysis, PCA, is basically a data reduction technique. PCA has been used in several problems in diagnostic radiology: processing radioisotope brain scans (Ref.1), automatic alignment of radionuclide images (Ref. 2), processing MRI images (Ref. 3,4), analyzing first-pass cardiac studies (Ref. 5) correcting for attenuation in bone mineral measurements (Ref. 6) and in dual energy x-ray imaging (Ref. 6,7). This paper will progress as follows; a brief introduction to the mathematics of PCA will be followed by two brief examples of how PCA has been used in the literature. Finally my own experience with PCA in dual-energy x-ray imaging will be given.

  1. Measuring toothbrush interproximal penetration using image analysis (United States)

    Hayworth, Mark S.; Lyons, Elizabeth K.


    An image analysis method of measuring the effectiveness of a toothbrush in reaching the interproximal spaces of teeth is described. Artificial teeth are coated with a stain that approximates real plaque and then brushed with a toothbrush on a brushing machine. The teeth are then removed and turned sideways so that the interproximal surfaces can be imaged. The areas of stain that have been removed within masked regions that define the interproximal regions are measured and reported. These areas correspond to the interproximal areas of the tooth reached by the toothbrush bristles. The image analysis method produces more precise results (10-fold decrease in standard deviation) in a fraction (22%) of the time as compared to our prior visual grading method.

  2. Piecewise flat embeddings for hyperspectral image analysis (United States)

    Hayes, Tyler L.; Meinhold, Renee T.; Hamilton, John F.; Cahill, Nathan D.


    Graph-based dimensionality reduction techniques such as Laplacian Eigenmaps (LE), Local Linear Embedding (LLE), Isometric Feature Mapping (ISOMAP), and Kernel Principal Components Analysis (KPCA) have been used in a variety of hyperspectral image analysis applications for generating smooth data embeddings. Recently, Piecewise Flat Embeddings (PFE) were introduced in the computer vision community as a technique for generating piecewise constant embeddings that make data clustering / image segmentation a straightforward process. In this paper, we show how PFE arises by modifying LE, yielding a constrained ℓ1-minimization problem that can be solved iteratively. Using publicly available data, we carry out experiments to illustrate the implications of applying PFE to pixel-based hyperspectral image clustering and classification.

  3. Unsupervised hyperspectral image analysis using independent component analysis (ICA)

    Energy Technology Data Exchange (ETDEWEB)

    S. S. Chiang; I. W. Ginsberg


    In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed as a random version of the commonly used linear spectral mixture analysis, in which the abundance fractions in a linear mixture model are considered to be unknown independent signal sources. It does not require the full rank of the separating matrix or orthogonality as most ICA methods do. More importantly, the learning algorithm is designed based on the independency of the material abundance vector rather than the independency of the separating matrix generally used to constrain the standard ICA. As a result, the designed learning algorithm is able to converge to non-orthogonal independent components. This is particularly useful in hyperspectral image analysis since many materials extracted from a hyperspectral image may have similar spectral signatures and may not be orthogonal. The AVIRIS experiments have demonstrated that the proposed ICA provides an effective unsupervised technique for hyperspectral image classification.

  4. An image processing analysis of skin textures

    CERN Document Server

    Sparavigna, A


    Colour and coarseness of skin are visually different. When image processing is involved in the skin analysis, it is important to quantitatively evaluate such differences using texture features. In this paper, we discuss a texture analysis and measurements based on a statistical approach to the pattern recognition. Grain size and anisotropy are evaluated with proper diagrams. The possibility to determine the presence of pattern defects is also discussed.


    Directory of Open Access Journals (Sweden)

    Izabela Gonçalves Terra


    Full Text Available The common sense knowledge formation is object of study of the Social Representation Theory, which highlights the role of communication in the production of comprehension by the subjects. The visual images favor the socialization of meanings and are active elements in the formation of social representations. Given the expressive role of the images in the formation of representational contents, this paper aims to present a semiotics analysis method for researches on social representations. The semiotic analysis of images was selected as a theoretical and methodological basis, for offering the means required for guidance for an effective research method to identify the social representations of socially shared iconic signs. The analysis method was explored by means of analytical procedures, employed for the apprehension of social representations of the feminine in posters for Brazilian Ministry of Health campaigns, which allowed access to the network of meanings associated with the analyzed visual image. It should be emphasized that the relevance of the use of semiotic analysis to analyze social representations, which presents itself as a fertile perspective for further studies expanding the possibilities of exploitation of visual content.

  6. Scanning transmission electron microscopy imaging and analysis

    CERN Document Server

    Pennycook, Stephen J


    Provides the first comprehensive treatment of the physics and applications of this mainstream technique for imaging and analysis at the atomic level Presents applications of STEM in condensed matter physics, materials science, catalysis, and nanoscience Suitable for graduate students learning microscopy, researchers wishing to utilize STEM, as well as for specialists in other areas of microscopy Edited and written by leading researchers and practitioners

  7. Visualization of Parameter Space for Image Analysis (United States)

    Pretorius, A. Johannes; Bray, Mark-Anthony P.; Carpenter, Anne E.; Ruddle, Roy A.


    Image analysis algorithms are often highly parameterized and much human input is needed to optimize parameter settings. This incurs a time cost of up to several days. We analyze and characterize the conventional parameter optimization process for image analysis and formulate user requirements. With this as input, we propose a change in paradigm by optimizing parameters based on parameter sampling and interactive visual exploration. To save time and reduce memory load, users are only involved in the first step - initialization of sampling - and the last step - visual analysis of output. This helps users to more thoroughly explore the parameter space and produce higher quality results. We describe a custom sampling plug-in we developed for CellProfiler - a popular biomedical image analysis framework. Our main focus is the development of an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. We implemented this in a prototype called Paramorama. It provides users with a visual overview of parameters and their sampled values. User-defined areas of interest are presented in a structured way that includes image-based output and a novel layout algorithm. To find optimal parameter settings, users can tag high- and low-quality results to refine their search. We include two case studies to illustrate the utility of this approach. PMID:22034361

  8. Web Based Distributed Coastal Image Analysis System Project (United States)

    National Aeronautics and Space Administration — This project develops Web based distributed image analysis system processing the Moderate Resolution Imaging Spectroradiometer (MODIS) data to provide decision...

  9. Image analysis for ophthalmological diagnosis image processing of Corvis ST images using Matlab

    CERN Document Server

    Koprowski, Robert


    This monograph focuses on the use of analysis and processing methods for images from the Corvis® ST tonometer. The presented analysis is associated with the quantitative, repeatable and fully automatic evaluation of the response of the eye, eyeball and cornea to an air-puff. All the described algorithms were practically implemented in MATLAB®. The monograph also describes and provides the full source code designed to perform the discussed calculations. As a result, this monograph is intended for scientists, graduate students and students of computer science and bioengineering as well as doctors wishing to expand their knowledge of modern diagnostic methods assisted by various image analysis and processing methods.

  10. Digital image sequence processing, compression, and analysis

    CERN Document Server

    Reed, Todd R



  11. 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...

  12. Use of Mueller polarimetric imaging for the staging of human colon cancer (United States)

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


    In this paper we show the results of multi-spectral Mueller Imaging applied to the analysis of human colon cancer in a backscattering configuration with diffuse light illumination. The analyzed sample behaves as a pure depolarizer. The depolarization power, for both healthy and cancerous zones, is lower for linearly than for circularly polarized incident light for all used wavelengths and increases with increasing wavelength. Based on their visual staging and polarimetric responses, we chose specific zones which we correlated to the histology of the corresponding cuts. The histological examination shows that we see a multilayer interaction in both healthy and abnormal zones, if the light penetration depth is sufficient. The measured depolarization depends on several factors: the presence or absence of tumor, the microscopic structure of cancer (ratio between cellular density and stroma), its exophytic (budding) or endophytic (penetrating) nature, its thickness, the degree of cancer penetration in deeper layers and the nature of healthy tissue left under abnormal layers. These results demonstrate that multi-spectral Mueller imaging can provide useful contrasts for the quick staging of human colon cancer ex-vivo, with additional information about cancerous zones with different microscopic structures.

  13. Quantitative Analysis in Nuclear Medicine Imaging

    CERN Document Server


    This book provides a review of image analysis techniques as they are applied in the field of diagnostic and therapeutic nuclear medicine. Driven in part by the remarkable increase in computing power and its ready and inexpensive availability, this is a relatively new yet rapidly expanding field. Likewise, although the use of radionuclides for diagnosis and therapy has origins dating back almost to the discovery of natural radioactivity itself, radionuclide therapy and, in particular, targeted radionuclide therapy has only recently emerged as a promising approach for therapy of cancer and, to a lesser extent, other diseases. As effort has, therefore, been made to place the reviews provided in this book in a broader context. The effort to do this is reflected by the inclusion of introductory chapters that address basic principles of nuclear medicine imaging, followed by overview of issues that are closely related to quantitative nuclear imaging and its potential role in diagnostic and therapeutic applications. ...

  14. Fast image analysis in polarization SHG microscopy. (United States)

    Amat-Roldan, Ivan; Psilodimitrakopoulos, Sotiris; Loza-Alvarez, Pablo; Artigas, David


    Pixel resolution polarization-sensitive second harmonic generation (PSHG) imaging has been recently shown as a promising imaging modality, by largely enhancing the capabilities of conventional intensity-based SHG microscopy. PSHG is able to obtain structural information from the elementary SHG active structures, which play an important role in many biological processes. Although the technique is of major interest, acquiring such information requires long offline processing, even with current computers. In this paper, we present an approach based on Fourier analysis of the anisotropy signature that allows processing the PSHG images in less than a second in standard single core computers. This represents a temporal improvement of several orders of magnitude compared to conventional fitting algorithms. This opens up the possibility for fast PSHG information with the subsequent benefit of potential use in medical applications.

  15. Image Processing and Analysis for DTMRI

    Directory of Open Access Journals (Sweden)

    Kondapalli Srinivasa Vara Prasad


    Full Text Available This paper describes image processing techniques for Diffusion Tensor Magnetic Resonance. In Diffusion Tensor MRI, a tensor describing local water diffusion is acquired for each voxel. The geometric nature of the diffusion tensors can quantitatively characterize the local structure in tissues such as bone, muscles, and white matter of the brain. The close relationship between local image structure and apparent diffusion makes this image modality very interesting for medical image analysis. We present a decomposition of the diffusion tensor based on its symmetry properties resulting in useful measures describing the geometry of the diffusion ellipsoid. A simple anisotropy measure follows naturally from this analysis. We describe how the geometry, or shape, of the tensor can be visualized using a coloring scheme based on the derived shape measures. We show how filtering of the tensor data of a human brain can provide a description of macro structural diffusion which can be used for measures of fiber-tract organization. We also describe how tracking of white matter tracts can be implemented using the introduced methods. These methods offers unique tools for the in vivo demonstration of neural connectivity in healthy and diseased brain tissue.

  16. Pain related inflammation analysis using infrared images (United States)

    Bhowmik, Mrinal Kanti; Bardhan, Shawli; Das, Kakali; Bhattacharjee, Debotosh; Nath, Satyabrata


    Medical Infrared Thermography (MIT) offers a potential non-invasive, non-contact and radiation free imaging modality for assessment of abnormal inflammation having pain in the human body. The assessment of inflammation mainly depends on the emission of heat from the skin surface. Arthritis is a disease of joint damage that generates inflammation in one or more anatomical joints of the body. Osteoarthritis (OA) is the most frequent appearing form of arthritis, and rheumatoid arthritis (RA) is the most threatening form of them. In this study, the inflammatory analysis has been performed on the infrared images of patients suffering from RA and OA. For the analysis, a dataset of 30 bilateral knee thermograms has been captured from the patient of RA and OA by following a thermogram acquisition standard. The thermograms are pre-processed, and areas of interest are extracted for further processing. The investigation of the spread of inflammation is performed along with the statistical analysis of the pre-processed thermograms. The objectives of the study include: i) Generation of a novel thermogram acquisition standard for inflammatory pain disease ii) Analysis of the spread of the inflammation related to RA and OA using K-means clustering. iii) First and second order statistical analysis of pre-processed thermograms. The conclusion reflects that, in most of the cases, RA oriented inflammation affects bilateral knees whereas inflammation related to OA present in the unilateral knee. Also due to the spread of inflammation in OA, contralateral asymmetries are detected through the statistical analysis.

  17. Quantitative image analysis of celiac disease. (United States)

    Ciaccio, Edward J; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H


    We outline the use of quantitative techniques that are currently used for analysis of celiac disease. Image processing techniques can be useful to statistically analyze the pixular data of endoscopic images that is acquired with standard or videocapsule endoscopy. It is shown how current techniques have evolved to become more useful for gastroenterologists who seek to understand celiac disease and to screen for it in suspected patients. New directions for focus in the development of methodology for diagnosis and treatment of this disease are suggested. It is evident that there are yet broad areas where there is potential to expand the use of quantitative techniques for improved analysis in suspected or known celiac disease patients.

  18. Quantitative image analysis of celiac disease (United States)

    Ciaccio, Edward J; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H


    We outline the use of quantitative techniques that are currently used for analysis of celiac disease. Image processing techniques can be useful to statistically analyze the pixular data of endoscopic images that is acquired with standard or videocapsule endoscopy. It is shown how current techniques have evolved to become more useful for gastroenterologists who seek to understand celiac disease and to screen for it in suspected patients. New directions for focus in the development of methodology for diagnosis and treatment of this disease are suggested. It is evident that there are yet broad areas where there is potential to expand the use of quantitative techniques for improved analysis in suspected or known celiac disease patients. PMID:25759524

  19. Morphometric image analysis of giant vesicles

    DEFF Research Database (Denmark)

    Husen, Peter Rasmussen; Arriaga, Laura; Monroy, Francisco


    We have developed a strategy to determine lengths and orientations of tie lines in the coexistence region of liquid-ordered and liquid-disordered phases of cholesterol containing ternary lipid mixtures. The method combines confocal-fluorescence-microscopy image stacks of giant unilamellar vesicles...... (GUVs), a dedicated 3D-image analysis, and a quantitative analysis based in equilibrium thermodynamic considerations. This approach was tested in GUVs composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine/1,2-palmitoyl-sn-glycero-3-phosphocholine/cholesterol. In general, our results show a reasonable...... agreement with previously reported data obtained by other methods. For example, our computed tie lines were found to be nonhorizontal, indicating a difference in cholesterol content in the coexisting phases. This new, to our knowledge, analytical strategy offers a way to further exploit fluorescence...

  20. 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

  1. Machine learning for medical images analysis. (United States)

    Criminisi, A


    This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods.

  2. Biomedical Image Analysis by Program "Vision Assistant" and "Labview"

    Directory of Open Access Journals (Sweden)

    Peter Izak


    Full Text Available This paper introduces application in image analysis of biomedical images. General task is focused on analysis and diagnosis biomedical images obtained from program ImageJ. There are described methods which can be used for images in biomedical application. The main idea is based on particle analysis, pattern matching techniques. For this task was chosensophistication method by program Vision Assistant, which is a part of program LabVIEW.

  3. Image analysis of blood platelets adhesion. (United States)

    Krízová, P; Rysavá, J; Vanícková, M; Cieslar, P; Dyr, J E


    Adhesion of blood platelets is one of the major events in haemostatic and thrombotic processes. We studied adhesion of blood platelets on fibrinogen and fibrin dimer sorbed on solid support material (glass, polystyrene). Adhesion was carried on under static and dynamic conditions and measured as percentage of the surface covered with platelets. Within a range of platelet counts in normal and in thrombocytopenic blood we observed a very significant decrease in platelet adhesion on fibrin dimer with bounded active thrombin with decreasing platelet count. Our results show the imperative use of platelet poor blood preparations as control samples in experiments with thrombocytopenic blood. Experiments carried on adhesive surfaces sorbed on polystyrene showed lower relative inaccuracy than on glass. Markedly different behaviour of platelets adhered on the same adhesive surface, which differed only in support material (glass or polystyrene) suggest that adhesion and mainly spreading of platelets depends on physical quality of the surface. While on polystyrene there were no significant differences between fibrin dimer and fibrinogen, adhesion measured on glass support material markedly differed between fibrin dimer and fibrinogen. We compared two methods of thresholding in image analysis of adhered platelets. Results obtained by image analysis of spreaded platelets showed higher relative inaccuracy than results obtained by image analysis of platelets centres and aggregates.


    Directory of Open Access Journals (Sweden)

    J. Bohlin


    Full Text Available The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E. Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean, stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean, with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet showed RMSEs (in percent of the surveyed stand mean of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.

  5. Assessment of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Leila Hassan-Esfahani


    Full Text Available Many crop production management decisions can be informed using data from high-resolution aerial images that provide information about crop health as influenced by soil fertility and moisture. Surface soil moisture is a key component of soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface; however, high-resolution remotely sensed data is rarely used to acquire soil moisture values. In this study, an artificial neural network (ANN model was developed to quantify the effectiveness of using spectral images to estimate surface soil moisture. The model produces acceptable estimations of surface soil moisture (root mean square error (RMSE = 2.0, mean absolute error (MAE = 1.8, coefficient of correlation (r = 0.88, coefficient of performance (e = 0.75 and coefficient of determination (R2 = 0.77 by combining field measurements with inexpensive and readily available remotely sensed inputs. The spatial data (visual spectrum, near infrared, infrared/thermal are produced by the AggieAir™ platform, which includes an unmanned aerial vehicle (UAV that enables users to gather aerial imagery at a low price and high spatial and temporal resolutions. This study reports the development of an ANN model that translates AggieAir™ imagery into estimates of surface soil moisture for a large field irrigated by a center pivot sprinkler system.

  6. Image analysis of Renaissance copperplate prints (United States)

    Hedges, S. Blair


    From the fifteenth to the nineteenth centuries, prints were a common form of visual communication, analogous to photographs. Copperplate prints have many finely engraved black lines which were used to create the illusion of continuous tone. Line densities generally are 100-2000 lines per square centimeter and a print can contain more than a million total engraved lines 20-300 micrometers in width. Because hundreds to thousands of prints were made from a single copperplate over decades, variation among prints can have historical value. The largest variation is plate-related, which is the thinning of lines over successive editions as a result of plate polishing to remove time-accumulated corrosion. Thinning can be quantified with image analysis and used to date undated prints and books containing prints. Print-related variation, such as over-inking of the print, is a smaller but significant source. Image-related variation can introduce bias if images were differentially illuminated or not in focus, but improved imaging technology can limit this variation. The Print Index, the percentage of an area composed of lines, is proposed as a primary measure of variation. Statistical methods also are proposed for comparing and identifying prints in the context of a print database.

  7. Automatic dirt trail analysis in dermoscopy images. (United States)

    Cheng, Beibei; Joe Stanley, R; Stoecker, William V; Osterwise, Christopher T P; Stricklin, Sherea M; Hinton, Kristen A; Moss, Randy H; Oliviero, Margaret; Rabinovitz, Harold S


    Basal cell carcinoma (BCC) is the most common cancer in the US. Dermatoscopes are devices used by physicians to facilitate the early detection of these cancers based on the identification of skin lesion structures often specific to BCCs. One new lesion structure, referred to as dirt trails, has the appearance of dark gray, brown or black dots and clods of varying sizes distributed in elongated clusters with indistinct borders, often appearing as curvilinear trails. In this research, we explore a dirt trail detection and analysis algorithm for extracting, measuring, and characterizing dirt trails based on size, distribution, and color in dermoscopic skin lesion images. These dirt trails are then used to automatically discriminate BCC from benign skin lesions. For an experimental data set of 35 BCC images with dirt trails and 79 benign lesion images, a neural network-based classifier achieved a 0.902 are under a receiver operating characteristic curve using a leave-one-out approach. Results obtained from this study show that automatic detection of dirt trails in dermoscopic images of BCC is feasible. This is important because of the large number of these skin cancers seen every year and the challenge of discovering these earlier with instrumentation. © 2011 John Wiley & Sons A/S.

  8. Quantitative color analysis for capillaroscopy image segmentation. (United States)

    Goffredo, Michela; Schmid, Maurizio; Conforto, Silvia; Amorosi, Beatrice; D'Alessio, Tommaso; Palma, Claudio


    This communication introduces a novel approach for quantitatively evaluating the role of color space decomposition in digital nailfold capillaroscopy analysis. It is clinically recognized that any alterations of the capillary pattern, at the periungual skin region, are directly related to dermatologic and rheumatic diseases. The proposed algorithm for the segmentation of digital capillaroscopy images is optimized with respect to the choice of the color space and the contrast variation. Since the color space is a critical factor for segmenting low-contrast images, an exhaustive comparison between different color channels is conducted and a novel color channel combination is presented. Results from images of 15 healthy subjects are compared with annotated data, i.e. selected images approved by clinicians. By comparison, a set of figures of merit, which highlights the algorithm capability to correctly segment capillaries, their shape and their number, is extracted. Experimental tests depict that the optimized procedure for capillaries segmentation, based on a novel color channel combination, presents values of average accuracy higher than 0.8, and extracts capillaries whose shape and granularity are acceptable. The obtained results are particularly encouraging for future developments on the classification of capillary patterns with respect to dermatologic and rheumatic diseases.

  9. Retrieval study of lake water depth by using multi-spectral remote sensing in Bangong Co Lake

    Institute of Scientific and Technical Information of China (English)

    Pu Zheng; ZhengDong Deng; Xin Ye


    This paper reviewed studies on remote sensing of water depth retrieval. Four water depth retrieval models (single-band, dou-ble-ratio-band, multi-band, and BP network models) were evaluated using TM image and water data from Bangong Co Lake, which is located in China’s Tibet Autonomous Region and Indian Kashmir. Tested by independent data, comparison of these four models demonstrates that BP network model performed better than the multi-band model, with the single-band model performing the worst. To sum up, this study demonstrates that first, BP network model performed better than the traditional model;second, precise atmospheric correction and radiation study, affected by different water level sand sediment, could improve the precision of water depth retrieval.

  10. Analysis of 193 Mammographic phantom images

    Energy Technology Data Exchange (ETDEWEB)

    Son, Eun Ju; Kim, Eun Kyung; Ko, Kyung Hee; Kim, Young Ah; Oh, Ki Keun [College of Medicine, Yonsei Univ., Seoul (Korea, Republic of); Chung, Sun Yang [College of Medicine, Pochon CHA Univ., Pochon (Korea, Republic of); Kim, Hyuk Joo; Cha, Seung Hwan [Korea Food and Drug Administration, Seoul (Korea, Republic of)


    To evaluate the actual state of quality control in Korea through analysis of mammographic phantom images obtained from a multicenter, and to determine the proper exposure conditions required in order to obtain satisfactory phantom images. Between April and June, 2002, 193 phantom images were referred to the Korea Food and Drug Administration for evaluation. Two radiologists recorded the number of fibers, specks and masses they contained, and the 'pass' criteria were as follows: checked number of fibers: four or more; specks, three or more; masses, three or more (a total of ten or more features). Images in which optical density was over 1.2 were classified as satisfactory. In addition, changes in the success ratio, and difference between the two groups (i.e. 'pass' and 'fail', with regard to exposure conditions and optical density) were evaluated. Among the 193 images, 116 (60.1%) passed and 77 (39.9%) failed. Among those which passed, 73/100 (73%) involved to use of a grid, 80/117 (68.3%) were obtained within the optimal kVp range, 50/111 (45.0%) involved the use of optimal mAs, and 79/112 (70.5%) were obtained within the optimal range of optical density. Among those which failed, the corresponding figures were 17/52 (32.6%), 33/66 (50.0%), 31/69 (44.9%), and 35/65 (53.8%), There were statistically significant differences between the pass and fail rates, and with regard to kVp, optical density, and the use of a grid, but with regard to mAs, statistical differences were not significant. If only phantom images with an optical density of over 1.2 [as per the rule of the Mammographic Quality Standard Act (MQSA)] was included, the success rate would fall from 60.1% to 43.0%. The pass rate for mammographic phantom images was 60.1%. If such images are to be satisfactory, they should be obtained within the optimal range of optical density, using optimal kVp and a grid.

  11. Image Fusion Based on the \\({\\Delta ^{ - 1}} - T{V_0}\\ Energy Function

    Directory of Open Access Journals (Sweden)

    Qiwei Xie


    Full Text Available This article proposes a \\({\\Delta^{-1}}-T{V_0}\\ energy function to fuse a multi-spectral image with a panchromatic image. The proposed energy function consists of two components, a \\(TV_0\\ component and a \\(\\Delta^{-1}\\ component. The \\(TV_0\\ term uses the sparse priority to increase the detailed spatial information; while the \\({\\Delta ^{ - 1}}\\ term removes the block effect of the multi-spectral image. Furthermore, as the proposed energy function is non-convex, we also adopt an alternative minimization algorithm and the \\(L_0\\ gradient minimization to solve it. Experimental results demonstrate the improved performance of the proposed method over existing methods.

  12. Reticle defect sizing of optical proximity correction defects using SEM imaging and image analysis techniques (United States)

    Zurbrick, Larry S.; Wang, Lantian; Konicek, Paul; Laird, Ellen R.


    Sizing of programmed defects on optical proximity correction (OPC) feature sis addressed using high resolution scanning electron microscope (SEM) images and image analysis techniques. A comparison and analysis of different sizing methods is made. This paper addresses the issues of OPC defect definition and discusses the experimental measurement results obtained by SEM in combination with image analysis techniques.

  13. Remote Sensing Digital Image Analysis An Introduction

    CERN Document Server

    Richards, John A


    Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same.  This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing.  The presentation level is for the mathematical non-specialist.  Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a leve...

  14. Nursing image: an evolutionary concept analysis. (United States)

    Rezaei-Adaryani, Morteza; Salsali, Mahvash; Mohammadi, Eesa


    A long-term challenge to the nursing profession is the concept of image. In this study, we used the Rodgers' evolutionary concept analysis approach to analyze the concept of nursing image (NI). The aim of this concept analysis was to clarify the attributes, antecedents, consequences, and implications associated with the concept. We performed an integrative internet-based literature review to retrieve English literature published from 1980-2011. Findings showed that NI is a multidimensional, all-inclusive, paradoxical, dynamic, and complex concept. The media, invisibility, clothing style, nurses' behaviors, gender issues, and professional organizations are the most important antecedents of the concept. We found that NI is pivotal in staff recruitment and nursing shortage, resource allocation to nursing, nurses' job performance, workload, burnout and job dissatisfaction, violence against nurses, public trust, and salaries available to nurses. An in-depth understanding of the NI concept would assist nurses to eliminate negative stereotypes and build a more professional image for the nurse and the profession.

  15. Simple Low Level Features for Image Analysis (United States)

    Falcoz, Paolo

    As human beings, we perceive the world around us mainly through our eyes, and give what we see the status of “reality”; as such we historically tried to create ways of recording this reality so we could augment or extend our memory. From early attempts in photography like the image produced in 1826 by the French inventor Nicéphore Niépce (Figure 2.1) to the latest high definition camcorders, the number of recorded pieces of reality increased exponentially, posing the problem of managing all that information. Most of the raw video material produced today has lost its memory augmentation function, as it will hardly ever be viewed by any human; pervasive CCTVs are an example. They generate an enormous amount of data each day, but there is not enough “human processing power” to view them. Therefore the need for effective automatic image analysis tools is great, and a lot effort has been put in it, both from the academia and the industry. In this chapter, a review of some of the most important image analysis tools are presented.

  16. Analysis on enhanced depth of field for integral imaging microscope. (United States)

    Lim, Young-Tae; Park, Jae-Hyeung; Kwon, Ki-Chul; Kim, Nam


    Depth of field of the integral imaging microscope is studied. In the integral imaging microscope, 3-D information is encoded as a form of elemental images Distance between intermediate plane and object point decides the number of elemental image and depth of field of integral imaging microscope. From the analysis, it is found that depth of field of the reconstructed depth plane image by computational integral imaging reconstruction is longer than depth of field of optical microscope. From analyzed relationship, experiment using integral imaging microscopy and conventional microscopy is also performed to confirm enhanced depth of field of integral imaging microscopy.

  17. Multispectral texture characterization: application to computer aided diagnosis on prostatic tissue images (United States)

    Khelifi, Riad; Adel, Mouloud; Bourennane, Salah


    Various approaches have been proposed in the literature for texture characterization of images. Some of them are based on statistical properties, others on fractal measures and some more on multi-resolution analysis. Basically, these approaches have been applied on mono-band images. However, most of them have been extended by including the additional information between spectral bands to deal with multi-band texture images. In this article, we investigate the problem of texture characterization for multi-band images. Therefore, we aim to add spectral information to classical texture analysis methods that only treat gray-level spatial variations. To achieve this goal, we propose a spatial and spectral gray level dependence method (SSGLDM) in order to extend the concept of gray level co-occurrence matrix (GLCM) by assuming the presence of texture joint information between spectral bands. Thus, we propose new multi-dimensional functions for estimating the second-order joint conditional probability density of spectral vectors. Theses functions can be represented in structure form which can help us to compute the occurrences while keeping the corresponding components of spectral vectors. In addition, new texture features measurements related to (SSGLDM) which define the multi-spectral image properties are proposed. Extensive experiments have been carried out on 624 textured multi-spectral images for use in prostate cancer diagnosis and quantitative results showed the efficiency of this method compared to the GLCM. The results indicate a significant improvement in terms of global accuracy rate. Thus, the proposed approach can provide clinically useful information for discriminating pathological tissue from healthy tissue.

  18. Machine Learning Interface for Medical Image Analysis. (United States)

    Zhang, Yi C; Kagen, Alexander C


    TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

  19. Geomorphologic Study of Anhui Section of Changjiang River Using Landsat TM Image

    Institute of Scientific and Technical Information of China (English)


    Fluvial landforms in the Anhui section of the Changjiang (Yangtze) River are often considered as the main factors for frequent floods. It is these special landforms that influence the channel changes of the Changjiang River.Using Landsat TM image of 2000, this paper conducted a series of image processing, including principal component analysis, multi-spectral composition, gray value statstics, and spectral analysis of ground objects. Then it got a new interpretation map of different kinds of fluvial landforms of the Changjiang River in the Anhui section. Based on the interpretation mentioned above, the paper analyzes the distribution and characteristics of such typical landforms as terraces, floodplains and battures, and their functions on the changes of river channel. The results show a consistence with the earlier conclusion that the Anhui section of the Changjiang River tends to deflect gradually toward south,which provides more implications for further study on the geomorphologic evolution of the river channel.

  20. [Investigation and assessment of damage in earthquake in Yushu, Qinghai based on multi-spectral remote sensing]. (United States)

    Wang, Fu-Tao; Zhou, Yi; Wang, Shi-Xin; Liu, Wen-Liang; Wei, Cheng-Jie; Han, Yu


    The devastating Yushu Earthquake occurred in Qinghai Province, northwest China, with a magnitude of 7.1 on April 14, 2010, which has caused huge destructive losses. Most buildings along the seismic zone were ruined, especially the old and the basic civil structure houses completely destroyed. The earthquake also triggered geological disasters, such as landslides, collapses, debris flows, etc. In the present study, the remote sensing technique was used to assess and analyze the situation of the earthquake damage. There are four classes of feature which can be interpreted according to the remote sensing imageries: (1) the damage degree of buildings, like civilian homes, temples; (2) the field disasters of earthquake, such as ground fissures, landslides, collapses, debris flows, and earthquake subsidence; (3) the damage degree of structures, such as dam; (4) the damage degree of the lifeline, for example, the highway. The features can be obtained according to high spatial resolution of remote sensing imageries, through image processing and interpretation methods. Post-disaster rehabilitation and reconstruction phase should fully consider the regional seismotectonic background and the carrying capacity of resources and environment. With the assessment results of earthquake disaster remote sensing, at last, preliminary suggestions were proposed for the rehabilitation and reconstruction planning of Yushu earthquake.


    Institute of Scientific and Technical Information of China (English)

    丛大成; 戴景民; 孙晓刚; 褚载祥


    The application of artificial neutral network to data processing of multi-spectral radiation thermometry was presented. By taking advantages of neutral network and various emissivity samples, the emissivity models of the targets were identified and the true temperature and spectral emissivity were available simultaneously. The measurement accuracy was improved further by subdivision. The effects of measurement errors on the measurement accuracy of temperature and emissivity were also analyzed. Computer simulation results proved that the method is an effective way for both temperature and emissivity measurements.%介绍了一种人工神经网络在多光谱测温数据处理中的应用.利用人工神经网络,结合多种发射训练样本模型,可以自动辨识被测目标的发射率模型,从而得到目标的真温和光谱发射率.应用二次细分的方法进一步提高了测量精度,并分析了各种测量误差对测温精度的影响.仿真结果表明此方法是获知真温与发射率的一种较好的方法.

  2. Semi-supervised segmentation of multispectral remote sensing image based on spectral clustering (United States)

    Zhang, Xiangrong; Wang, Ting; Jiao, Licheng; Yang, Chun


    In this paper, a new multi-spectral remote sensing image segmentation method based on multi-parameter semi-supervised spectral clustering (STS3C) is proposed. Two types of instance-level constraints: must-link and cannot-link are incorporated into spectral cluster to construct semi-supervised spectral clustering in which the self-tuning parameter is applied to avoid the selection of the scaling parameter. Further, when STS3C is applied to multi-spectral remote sensing image segmentation, the uniform sampling technique combined with nearest neighbor rule is used to reduce the computation complexity. Segmentation results show that STS3C outperforms the semi-supervised spectral clustering with fixed parameter and the well-known clustering methods including k-means and FCM in multi-spectral remote sensing image segmentation.

  3. 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.

  4. Research on automatic human chromosome image analysis (United States)

    Ming, Delie; Tian, Jinwen; Liu, Jian


    Human chromosome karyotyping is one of the essential tasks in cytogenetics, especially in genetic syndrome diagnoses. In this thesis, an automatic procedure is introduced for human chromosome image analysis. According to different status of touching and overlapping chromosomes, several segmentation methods are proposed to achieve the best results. Medial axis is extracted by the middle point algorithm. Chromosome band is enhanced by the algorithm based on multiscale B-spline wavelets, extracted by average gray profile, gradient profile and shape profile, and calculated by the WDD (Weighted Density Distribution) descriptors. The multilayer classifier is used in classification. Experiment results demonstrate that the algorithms perform well.

  5. Rapid spectral analysis for spectral imaging. (United States)

    Jacques, Steven L; Samatham, Ravikant; Choudhury, Niloy


    Spectral imaging requires rapid analysis of spectra associated with each pixel. A rapid algorithm has been developed that uses iterative matrix inversions to solve for the absorption spectra of a tissue using a lookup table for photon pathlength based on numerical simulations. The algorithm uses tissue water content as an internal standard to specify the strength of optical scattering. An experimental example is presented on the spectroscopy of portwine stain lesions. When implemented in MATLAB, the method is ~100-fold faster than using fminsearch().

  6. ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability. (United States)

    Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W


    ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks.

  7. Etching and image analysis of the microstructure in marble

    DEFF Research Database (Denmark)

    Alm, Ditte; Brix, Susanne; Howe-Rasmussen, Helle


    of grains exposed on that surface are measured on the microscope images using image analysis by the program Adobe Photoshop 7.0 with Image Processing Toolkit 4.0. The parameters measured by the program on microscope images of thin sections of two marble types are used for calculation of the coefficient...

  8. Digital image analysis of palaeoenvironmental records and applications

    Institute of Scientific and Technical Information of China (English)


    Environmental change signals in geological or biological records are commonly reflected on their reflecting or transmitting images. These environmental signals can be extracted through digital image analysis. The analysis principle involves section line selection, color value reading and calculating environmental proxy index along the section lines, layer identification, auto-chronology and investigation of structure evolution of growth bands. On detailed illustrations of the image technique, this note provides image analyzing procedures of coral, tree-ring and stalagmite records. The environmental implications of the proxy index from image analysis are accordingly given through application demonstration of the image technique.

  9. Wavelet Analysis of Space Solar Telescope Images

    Institute of Scientific and Technical Information of China (English)

    Xi-An Zhu; Sheng-Zhen Jin; Jing-Yu Wang; Shu-Nian Ning


    The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day,SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume.Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application.We start with a brief introduction to the essential principles of wavelet analysis,and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.

  10. Analysis of Slewing and Attitude Determination Requirements for CTEx (United States)


    Australia 126 0.45 – 2.50 15 – 20 HYPERION TRW 220 0.40 – 2.5 10 IISRB Infrared Imaging Spectrometer Bomen 1720 3.50 – 5.00 IMSS Image...Technology Sherlock LWIR Pacific Advanced Technology USA Spectral resol. 3 nm at λ = 3.0µm 8.0 – 10.5 IMSS (Image Multi Spectral...Sensing) Sherlock MWIR Pacific Advanced Technology USA Spectral resol. 33 nm at λ = 8.0µm 3.0 – 5.0 IMSS (Image Multi Spectral Sensing

  11. The Scientific Image in Behavior Analysis. (United States)

    Keenan, Mickey


    Throughout the history of science, the scientific image has played a significant role in communication. With recent developments in computing technology, there has been an increase in the kinds of opportunities now available for scientists to communicate in more sophisticated ways. Within behavior analysis, though, we are only just beginning to appreciate the importance of going beyond the printing press to elucidate basic principles of behavior. The aim of this manuscript is to stimulate appreciation of both the role of the scientific image and the opportunities provided by a quick response code (QR code) for enhancing the functionality of the printed page. I discuss the limitations of imagery in behavior analysis ("Introduction"), and I show examples of what can be done with animations and multimedia for teaching philosophical issues that arise when teaching about private events ("Private Events 1 and 2"). Animations are also useful for bypassing ethical issues when showing examples of challenging behavior ("Challenging Behavior"). Each of these topics can be accessed only by scanning the QR code provided. This contingency has been arranged to help the reader embrace this new technology. In so doing, I hope to show its potential for going beyond the limitations of the printing press.

  12. Percent area coverage through image analysis (United States)

    Wong, Chung M.; Hong, Sung M.; Liu, De-Ling


    The notion of percent area coverage (PAC) has been used to characterize surface cleanliness levels in the spacecraft contamination control community. Due to the lack of detailed particle data, PAC has been conventionally calculated by multiplying the particle surface density in predetermined particle size bins by a set of coefficients per MIL-STD-1246C. In deriving the set of coefficients, the surface particle size distribution is assumed to follow a log-normal relation between particle density and particle size, while the cross-sectional area function is given as a combination of regular geometric shapes. For particles with irregular shapes, the cross-sectional area function cannot describe the true particle area and, therefore, may introduce error in the PAC calculation. Other errors may also be introduced by using the lognormal surface particle size distribution function that highly depends on the environmental cleanliness and cleaning process. In this paper, we present PAC measurements from silicon witness wafers that collected fallouts from a fabric material after vibration testing. PAC calculations were performed through analysis of microscope images and compare them to values derived through the MIL-STD-1246C method. Our results showed that the MIL-STD-1246C method does provide a reasonable upper bound to the PAC values determined through image analysis, in particular for PAC values below 0.1.

  13. Comparative Analysis of Various Image Fusion Techniques For Biomedical Images: A Review

    Directory of Open Access Journals (Sweden)

    Nayera Nahvi,


    Full Text Available Image Fusion is a process of combining the relevant information from a set of images, into a single image, wherein the resultant fused image will be more informative and complete than any of the input images. This paper discusses implementation of DWT technique on different images to make a fused image having more information content. As DWT is the latest technique for image fusion as compared to simple image fusion and pyramid based image fusion, so we are going to implement DWT as the image fusion technique in our paper. Other methods such as Principal Component Analysis (PCA based fusion, Intensity hue Saturation (IHS Transform based fusion and high pass filtering methods are also discussed. A new algorithm is proposed using Discrete Wavelet transform and different fusion techniques including pixel averaging, min-max and max-min methods for medical image fusion. KEYWORDS:

  14. From Pixels to Geographic Objects in Remote Sensing Image Analysis

    NARCIS (Netherlands)

    Addink, E.A.; Van Coillie, Frieke M.B.; Jong, Steven M. de


    Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received considerabl

  15. From Pixels to Geographic Objects in Remote Sensing Image Analysis

    NARCIS (Netherlands)

    Addink, E.A.; Van Coillie, Frieke M.B.; Jong, Steven M. de

    Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received

  16. Image analysis and platform development for automated phenotyping in cytomics

    NARCIS (Netherlands)

    Yan, Kuan


    This thesis is dedicated to the empirical study of image analysis in HT/HC screen study. Often a HT/HC screening produces extensive amounts that cannot be manually analyzed. Thus, an automated image analysis solution is prior to an objective understanding of the raw image data. Compared to general a

  17. Detection and Monitoring of E-Waste Contamination through Remote Sensing and Image Analysis (United States)

    Garb, Yaakov; Friedlander, Lonia


    Electronic waste (e-waste) is one of today's fastest growing waste streams, and also one of the more problematic, as this end-of-life product contains precious metals mixed with and embedded in a variety of low value and potentially harmful plastic and other materials. This combination creates a powerful incentive for informal value chains that transport, extract from, and dispose of e-waste materials in far-ranging and unregulated ways, and especially in settings where regulation and livelihood alternatives are sparse, most notably in areas of India, China, and Africa. E-waste processing is known to release a variety of contaminants, such as heavy metals and persistent organic pollutants, including flame retardants, dioxins and furans. In several sites, where the livelihoods of entire communities are dependent on e-waste processing, the resulting contaminants have been demonstrated to enter the hydrological system and food chain and have serious health and ecological effects. In this paper we demonstrate for the first time the usefulness of multi-spectral remote sensing imagery to detect and monitor the release and possibly the dispersal of heavy metal contaminants released in e-waste processing. While similar techniques have been used for prospecting or for studying heavy metal contamination from mining and large industrial facilities, we suggest that these techniques are of particular value in detecting contamination from the more dispersed, shifting, and ad-hoc kinds of release typical of e-waste processing. Given the increased resolution and decreased price of multi-spectral imagery, such techniques may offer a remarkably cost-effective and rapidly responsive means of assessing and monitoring this kind of contamination. We will describe the geochemical and multi-spectral image-processing principles underlying our approach, and show how we have applied these to an area in which we have a detailed, multi-temporal, spatially referenced, and ground

  18. Quantitative Hyperspectral Reflectance Imaging

    Directory of Open Access Journals (Sweden)

    Ted A.G. Steemers


    Full Text Available Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared. By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms.

  19. Blind Analysis of CT Image Noise Using Residual Denoised Images

    CERN Document Server

    Roychowdhury, Sohini; Alessio, Adam


    CT protocol design and quality control would benefit from automated tools to estimate the quality of generated CT images. These tools could be used to identify erroneous CT acquisitions or refine protocols to achieve certain signal to noise characteristics. This paper investigates blind estimation methods to determine global signal strength and noise levels in chest CT images. Methods: We propose novel performance metrics corresponding to the accuracy of noise and signal estimation. We implement and evaluate the noise estimation performance of six spatial- and frequency- based methods, derived from conventional image filtering algorithms. Algorithms were tested on patient data sets from whole-body repeat CT acquisitions performed with a higher and lower dose technique over the same scan region. Results: The proposed performance metrics can evaluate the relative tradeoff of filter parameters and noise estimation performance. The proposed automated methods tend to underestimate CT image noise at low-flux levels...

  20. Automated regional behavioral analysis for human brain images

    National Research Council Canada - National Science Library

    Lancaster, Jack L; Laird, Angela R; Eickhoff, Simon B; Martinez, Michael J; Fox, P Mickle; Fox, Peter T


    Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images...

  1. Direct identification of fungi using image analysis

    DEFF Research Database (Denmark)

    Dørge, Thorsten Carlheim; Carstensen, Jens Michael; Frisvad, Jens Christian


    Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because of the sub......Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because...... of the subjectivity in the visual evaluation and quantification (if any)of such characters and the apparent large variability of the features. We present an image analysis approach for objective identification and classification of fungi. The approach is exemplified by several isolates of nine different species...... of the genus Penicillium, known to be very difficult to identify correctly. The fungi were incubated on YES and CYA for one week at 25 C (3 point inoculation) in 9 cm Petri dishes. The cultures are placed under a camera where a digital image of the front of the colonies is acquired under optimal illumination...


    Directory of Open Access Journals (Sweden)

    Yoganand Balagurunathan


    Full Text Available Sediments are routinely analyzed in terms of the sizing characteristics of the grains of which they are composed. Via sieving methods, the grains are separated and a weight-based size distribution constructed. Various moment parameters are computed from the size distribution and these serve as sediment characteristics. This paper examines the feasibility of a fully electronic granularity analysis using digital image processing. The study uses a random model of three-dimensional grains in conjunction with the morphological method of granulometric size distributions. The random model is constructed to simulate sand, silt, and clay particle distributions. Owing to the impossibility of perfectly sifting small grains so that they do not touch, the model is used in both disjoint and non-disjoint modes, and watershed segmentation is applied in the non-disjoint model. The image-based granulometric size distributions are transformed so that they take into account the necessity to view sediment fractions at different magnifications and in different frames. Gray-scale granulometric moments are then computed using both ordinary and reconstructive granulometries. The resulting moments are then compared to moments found from real grains in seven different sediments using standard weight-based size distributions.

  3. Accuracy of Image Analysis in Quantitative Study of Cement Paste

    Directory of Open Access Journals (Sweden)

    Feng Shu-Xia


    Full Text Available Quantitative study on cement paste especially blended cement paste has been a hot and difficult issue over the years, and the technique of backscattered electron image analysis showed unique advantages in this field. This paper compared the test results of cement hydration degree, Ca(OH2 content and pore size distribution in pure pastes by image analysis and other methods. Then the accuracy of qualitative study by image analysis was analyzed. The results showed that image analysis technique had displayed higher accuracy in quantifying cement hydration degree and Ca(OH2 content than non-evaporable water test and thermal analysis respectively.

  4. Image analysis and microscopy: a useful combination

    Directory of Open Access Journals (Sweden)

    Pinotti L.


    Full Text Available The TSE Roadmap published in 2005 (DG for Health and Consumer Protection, 2005 suggests that short and medium term (2005-2009 amendments to control BSE policy should include “a relaxation of certain measures of the current total feed ban when certain conditions are met”. The same document noted “the starting point when revising the current feed ban provisions should be risk-based but at the same time taking into account the control tools in place to evaluate and ensure the proper implementation of this feed ban”. The clear implication is that adequate analytical methods to detect constituents of animal origin in feedstuffs are required. The official analytical method for the detection of constituents of animal origin in feedstuffs is the microscopic examination technique as described in Commission Directive 2003/126/EC of 23 December 2003 [OJ L 339, 24.12.2003, 78]. Although the microscopic method is usually able to distinguish fish from land animal material, it is often unable to distinguish between different terrestrial animals. Fulfillments of the requirements of Regulation 1774/2002/EC laying down health rules concerning animal by-products not intended for human consumption, clearly implies that it must be possible to identify the origin animal materials, at higher taxonomic levels than in the past. Thus improvements in all methods of detecting constituents of animal origin are required, including the microscopic method. This article will examine the problem of meat and bone meal in animal feeds, and the use of microscopic methods in association with computer image analysis to identify the source species of these feedstuff contaminants. Image processing, integrated with morphometric measurements can provide accurate and reliable results and can be a very useful aid to the analyst in the characterization, analysis and control of feedstuffs.

  5. Image processing and analysis with graphs theory and practice

    CERN Document Server

    Lézoray, Olivier


    Covering the theoretical aspects of image processing and analysis through the use of graphs in the representation and analysis of objects, Image Processing and Analysis with Graphs: Theory and Practice also demonstrates how these concepts are indispensible for the design of cutting-edge solutions for real-world applications. Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imaging With the explosive growth in image production, in everything from digital photographs to medical scans, there has been a drast

  6. Some selected quantitative methods of thermal image analysis in Matlab. (United States)

    Koprowski, Robert


    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image.

  7. High resolution ultraviolet imaging spectrometer for latent image analysis. (United States)

    Lyu, Hang; Liao, Ningfang; Li, Hongsong; Wu, Wenmin


    In this work, we present a close-range ultraviolet imaging spectrometer with high spatial resolution, and reasonably high spectral resolution. As the transmissive optical components cause chromatic aberration in the ultraviolet (UV) spectral range, an all-reflective imaging scheme is introduced to promote the image quality. The proposed instrument consists of an oscillating mirror, a Cassegrain objective, a Michelson structure, an Offner relay, and a UV enhanced CCD. The finished spectrometer has a spatial resolution of 29.30μm on the target plane; the spectral scope covers both near and middle UV band; and can obtain approximately 100 wavelength samples over the range of 240~370nm. The control computer coordinates all the components of the instrument and enables capturing a series of images, which can be reconstructed into an interferogram datacube. The datacube can be converted into a spectrum datacube, which contains spectral information of each pixel with many wavelength samples. A spectral calibration is carried out by using a high pressure mercury discharge lamp. A test run demonstrated that this interferometric configuration can obtain high resolution spectrum datacube. The pattern recognition algorithm is introduced to analyze the datacube and distinguish the latent traces from the base materials. This design is particularly good at identifying the latent traces in the application field of forensic imaging.

  8. Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

    Directory of Open Access Journals (Sweden)

    Kiuru Aaro


    Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

  9. SAR oil spill image segmentation based on a multi-spectral clustering algorithm%多特征-谱聚类的SAR图像溢油分割

    Institute of Scientific and Technical Information of China (English)

    张伟伟; 薄华; 王晓峰


    经典的K聚类算法,并不适合实现任意形状的聚类,而且有容易陷入局部最小值的不足.提出基于多个纹理特征的谱聚类算法,该方法用灰度共生矩阵(GLCM)提取合成孔径雷达 (SAR)图像的多个特征值,构建谱聚类的特征矩阵,并依据规范切准则,用K均值聚类的方法对拉普拉斯矩阵的第二小的特征值对应的特征向量进行聚类,实现基于SAR图像的溢油的分割.新方法与传统的K聚类方法比较,可以减少相干斑噪声对分割结果的影响,较好的保持图像边缘.仿真结果显示,该算法对于相干斑噪声影响较大的图像具有较强的鲁棒性.

  10. 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

  11. Link Graph Analysis for Adult Images Classification

    CERN Document Server

    Kharitonov, Evgeny; Muchnik, Ilya; Romanenko, Fedor; Belyaev, Dmitry; Kotlyarov, Dmitry


    In order to protect an image search engine's users from undesirable results adult images' classifier should be built. The information about links from websites to images is employed to create such a classifier. These links are represented as a bipartite website-image graph. Each vertex is equipped with scores of adultness and decentness. The scores for image vertexes are initialized with zero, those for website vertexes are initialized according to a text-based website classifier. An iterative algorithm that propagates scores within a website-image graph is described. The scores obtained are used to classify images by choosing an appropriate threshold. The experiments on Internet-scale data have shown that the algorithm under consideration increases classification recall by 17% in comparison with a simple algorithm which classifies an image as adult if it is connected with at least one adult site (at the same precision level).

  12. SAR Image Texture Analysis of Oil Spill (United States)

    Ma, Long; Li, Ying; Liu, Yu

    Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they have serious affect on fragile marine and coastal ecosystem. In order to implement an emergency in case of oil spills, it is necessary to monitor oil spill using remote sensing. Spaceborne SAR is considered a promising method to monitor oil spill, which causes attention from many researchers. However, research in SAR image texture analysis of oil spill is rarely reported. On 7 December 2007, a crane-carrying barge hit the Hong Kong-registered tanker "Hebei Spirit", which released an estimated 10,500 metric tons of crude oil into the sea. The texture features on this oil spill were acquired based on extracted GLCM (Grey Level Co-occurrence Matrix) by using SAR as data source. The affected area was extracted successfully after evaluating capabilities of different texture features to monitor the oil spill. The results revealed that the texture is an important feature for oil spill monitoring. Key words: oil spill, texture analysis, SAR

  13. Analysis of physical processes via imaging vectors (United States)

    Volovodenko, V.; Efremova, N.; Efremov, V.


    Practically, all modeling processes in one way or another are random. The foremost formulated theoretical foundation embraces Markov processes, being represented in different forms. Markov processes are characterized as a random process that undergoes transitions from one state to another on a state space, whereas the probability distribution of the next state depends only on the current state and not on the sequence of events that preceded it. In the Markov processes the proposition (model) of the future by no means changes in the event of the expansion and/or strong information progression relative to preceding time. Basically, modeling physical fields involves process changing in time, i.e. non-stationay processes. In this case, the application of Laplace transformation provides unjustified description complications. Transition to other possibilities results in explicit simplification. The method of imaging vectors renders constructive mathematical models and necessary transition in the modeling process and analysis itself. The flexibility of the model itself using polynomial basis leads to the possible rapid transition of the mathematical model and further analysis acceleration. It should be noted that the mathematical description permits operator representation. Conversely, operator representation of the structures, algorithms and data processing procedures significantly improve the flexibility of the modeling process.

  14. Dynamic chest image analysis: model-based pulmonary perfusion analysis with pyramid images (United States)

    Liang, Jianming; Haapanen, Arto; Jaervi, Timo; Kiuru, Aaro J.; Kormano, Martti; Svedstrom, Erkki; Virkki, Raimo


    The aim of the study 'Dynamic Chest Image Analysis' is to develop computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected at different phases of the respiratory/cardiac cycles in a short period of time. We have proposed a framework for ventilation study with an explicit ventilation model based on pyramid images. In this paper, we extend the framework to pulmonary perfusion study. A perfusion model and the truncated pyramid are introduced. The perfusion model aims at extracting accurate, geographic perfusion parameters, and the truncated pyramid helps in understanding perfusion at multiple resolutions and speeding up the convergence process in optimization. Three cases are included to illustrate the experimental results.

  15. Ripening of salami: assessment of colour and aspect evolution using image analysis and multivariate image analysis. (United States)

    Fongaro, Lorenzo; Alamprese, Cristina; Casiraghi, Ernestina


    During ripening of salami, colour changes occur due to oxidation phenomena involving myoglobin. Moreover, shrinkage due to dehydration results in aspect modifications, mainly ascribable to fat aggregation. The aim of this work was the application of image analysis (IA) and multivariate image analysis (MIA) techniques to the study of colour and aspect changes occurring in salami during ripening. IA results showed that red, green, blue, and intensity parameters decreased due to the development of a global darker colour, while Heterogeneity increased due to fat aggregation. By applying MIA, different salami slice areas corresponding to fat and three different degrees of oxidised meat were identified and quantified. It was thus possible to study the trend of these different areas as a function of ripening, making objective an evaluation usually performed by subjective visual inspection. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Three modality image registration of brain SPECT/CT and MR images for quantitative analysis of dopamine transporter imaging (United States)

    Yamaguchi, Yuzuho; Takeda, Yuta; Hara, Takeshi; Zhou, Xiangrong; Matsusako, Masaki; Tanaka, Yuki; Hosoya, Kazuhiko; Nihei, Tsutomu; Katafuchi, Tetsuro; Fujita, Hiroshi


    Important features in Parkinson's disease (PD) are degenerations and losses of dopamine neurons in corpus striatum. 123I-FP-CIT can visualize activities of the dopamine neurons. The activity radio of background to corpus striatum is used for diagnosis of PD and Dementia with Lewy Bodies (DLB). The specific activity can be observed in the corpus striatum on SPECT images, but the location and the shape of the corpus striatum on SPECT images only are often lost because of the low uptake. In contrast, MR images can visualize the locations of the corpus striatum. The purpose of this study was to realize a quantitative image analysis for the SPECT images by using image registration technique with brain MR images that can determine the region of corpus striatum. In this study, the image fusion technique was used to fuse SPECT and MR images by intervening CT image taken by SPECT/CT. The mutual information (MI) for image registration between CT and MR images was used for the registration. Six SPECT/CT and four MR scans of phantom materials are taken by changing the direction. As the results of the image registrations, 16 of 24 combinations were registered within 1.3mm. By applying the approach to 32 clinical SPECT/CT and MR cases, all of the cases were registered within 0.86mm. In conclusions, our registration method has a potential in superimposing MR images on SPECT images.

  17. Machine learning approaches in medical image analysis

    DEFF Research Database (Denmark)

    de Bruijne, Marleen


    Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

  18. Principal component analysis of psoriasis lesions images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær


    A set of RGB images of psoriasis lesions is used. By visual examination of these images, there seem to be no common pattern that could be used to find and align the lesions within and between sessions. It is expected that the principal components of the original images could be useful during future...

  19. Medical Image Analysis by Cognitive Information Systems - a Review. (United States)

    Ogiela, Lidia; Takizawa, Makoto


    This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types of medical images. Cognitive information systems were defined on the basis of methods for the semantic analysis and interpretation of information - medical images - applied to cognitive meaning of medical images contained in analyzed data sets. Semantic analysis was proposed to analyzed the meaning of data. Meaning is included in information, for example in medical images. Medical image analysis will be presented and discussed as they are applied to various types of medical images, presented selected human organs, with different pathologies. Those images were analyzed using different classes of cognitive information systems. Cognitive information systems dedicated to medical image analysis was also defined for the decision supporting tasks. This process is very important for example in diagnostic and therapy processes, in the selection of semantic aspects/features, from analyzed data sets. Those features allow to create a new way of analysis.

  20. Image Retrieval: Theoretical Analysis and Empirical User Studies on Accessing Information in Images. (United States)

    Ornager, Susanne


    Discusses indexing and retrieval for effective searches of digitized images. Reports on an empirical study about criteria for analysis and indexing digitized images, and the different types of user queries done in newspaper image archives in Denmark. Concludes that it is necessary that the indexing represent both a factual and an expressional…

  1. Automatic quantitative analysis of cardiac MR perfusion images

    NARCIS (Netherlands)

    Breeuwer, Marcel; Spreeuwers, Luuk; Quist, Marcel


    Magnetic Resonance Imaging (MRI) is a powerful technique for imaging cardiovascular diseases. The introduction of cardiovascular MRI into clinical practice is however hampered by the lack of efficient and accurate image analysis methods. This paper focuses on the evaluation of blood perfusion in the

  2. Subsurface offset behaviour in velocity analysis with extended reflectivity images

    NARCIS (Netherlands)

    Mulder, W.A.


    Migration velocity analysis with the constant-density acoustic wave equation can be accomplished by the focusing of extended migration images, obtained by introducing a subsurface shift in the imaging condition. A reflector in a wrong velocity model will show up as a curve in the extended image. In

  3. Intrasubject registration for change analysis in medical imaging

    NARCIS (Netherlands)

    Staring, M.


    Image matching is important for the comparison of medical images. Comparison is of clinical relevance for the analysis of differences due to changes in the health of a patient. For example, when a disease is imaged at two time points, then one wants to know if it is stable, has regressed, or

  4. Mesh Processing in Medical-Image Analysis-a Tutorial

    DEFF Research Database (Denmark)

    Levine, Joshua A.; Paulsen, Rasmus Reinhold; Zhang, Yongjie


    Medical-image analysis requires an understanding of sophisticated scanning modalities, constructing geometric models, building meshes to represent domains, and downstream biological applications. These four steps form an image-to-mesh pipeline. For research in this field to progress, the imaging...

  5. 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.

  6. Image analysis for dental bone quality assessment using CBCT imaging (United States)

    Suprijanto; Epsilawati, L.; Hajarini, M. S.; Juliastuti, E.; Susanti, H.


    Cone beam computerized tomography (CBCT) is one of X-ray imaging modalities that are applied in dentistry. Its modality can visualize the oral region in 3D and in a high resolution. CBCT jaw image has potential information for the assessment of bone quality that often used for pre-operative implant planning. We propose comparison method based on normalized histogram (NH) on the region of inter-dental septum and premolar teeth. Furthermore, the NH characteristic from normal and abnormal bone condition are compared and analyzed. Four test parameters are proposed, i.e. the difference between teeth and bone average intensity (s), the ratio between bone and teeth average intensity (n) of NH, the difference between teeth and bone peak value (Δp) of NH, and the ratio between teeth and bone of NH range (r). The results showed that n, s, and Δp have potential to be the classification parameters of dental calcium density.

  7. CMOS Image Sensor with On-Chip Image Compression: A Review and Performance Analysis

    Directory of Open Access Journals (Sweden)

    Milin Zhang


    Full Text Available Demand for high-resolution, low-power sensing devices with integrated image processing capabilities, especially compression capability, is increasing. CMOS technology enables the integration of image sensing and image processing, making it possible to improve the overall system performance. This paper reviews the current state of the art in CMOS image sensors featuring on-chip image compression. Firstly, typical sensing systems consisting of separate image-capturing unit and image-compression processing unit are reviewed, followed by systems that integrate focal-plane compression. The paper also provides a thorough review of a new design paradigm, in which image compression is performed during the image-capture phase prior to storage, referred to as compressive acquisition. High-performance sensor systems reported in recent years are also introduced. Performance analysis and comparison of the reported designs using different design paradigm are presented at the end.

  8. Technique of Hadamard transform microscope fluorescence image analysis

    Institute of Scientific and Technical Information of China (English)

    梅二文; 顾文芳; 曾晓斌; 陈观铨; 曾云鹗


    Hadamard transform spatial multiplexed imaging technique is combined with fluorescence microscope and an instrument of Hadamard transform microscope fluorescence image analysis is developed. Images acquired by this instrument can provide a lot of useful information simultaneously, including three-dimensional Hadamard transform microscope cell fluorescence image, the fluorescence intensity and fluorescence distribution of a cell, the background signal intensity and the signal/noise ratio, etc.

  9. New approaches in intelligent image analysis techniques, methodologies and applications

    CERN Document Server

    Nakamatsu, Kazumi


    This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

  10. Analysis of engineering drawings and raster map images

    CERN Document Server

    Henderson, Thomas C


    Presents up-to-date methods and algorithms for the automated analysis of engineering drawings and digital cartographic maps Discusses automatic engineering drawing and map analysis techniques Covers detailed accounts of the use of unsupervised segmentation algorithms to map images


    Directory of Open Access Journals (Sweden)

    Philippe Lopez


    Full Text Available Through laboratory research performed over the past ten years, many of the critical links between fracture characteristics and hydromechanical and mechanical behaviour have been made for individual fractures. One of the remaining challenges at the laboratory scale is to directly link fracture morphology of shear behaviour with changes in stress and shear direction. A series of laboratory experiments were performed on cement mortar replicas of a granite sample with a natural fracture perpendicular to the axis of the core. Results show that there is a strong relationship between the fracture's geometry and its mechanical behaviour under shear stress and the resulting damage. Image analysis, geostatistical, stereological and directional data techniques are applied in combination to experimental data. The results highlight the role of geometric characteristics of the fracture surfaces (surface roughness, size, shape, locations and orientations of asperities to be damaged in shear behaviour. A notable improvement in shear understanding is that shear behaviour is controlled by the apparent dip in the shear direction of elementary facets forming the fracture.

  12. Slide Set: Reproducible image analysis and batch processing with ImageJ. (United States)

    Nanes, Benjamin A


    Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets common in biology. Here we present the Slide Set plugin for ImageJ, which provides a framework for reproducible image analysis and batch processing. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution.

  13. The use of a multilayer perceptron for detecting new human settlements from a time series of MODIS images

    CSIR Research Space (South Africa)

    Salmon, BP


    Full Text Available This paper presents a novel land cover change detection method that employs a sliding window over hyper-temporal multi-spectral images acquired from the 7 bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance...

  14. Hierarchical manifold learning for regional image analysis. (United States)

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Joseph V; Rueckert, Daniel


    We present a novel method of hierarchical manifold learning which aims to automatically discover regional properties of image datasets. While traditional manifold learning methods have become widely used for dimensionality reduction in medical imaging, they suffer from only being able to consider whole images as single data points. We extend conventional techniques by additionally examining local variations, in order to produce spatially-varying manifold embeddings that characterize a given dataset. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate the utility of our method in two very different settings: 1) to learn the regional correlations in motion within a sequence of time-resolved MR images of the thoracic cavity; 2) to find discriminative regions of 3-D brain MR images associated with neurodegenerative disease.

  15. Some developments in multivariate image analysis

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    and classification. MIA considers all image pixels as objects and their color values (or spectrum in the case of hyperspectral images) as variables. So it gives data matrices with hundreds of thousands samples in the case of laboratory scale images and even more for aerial photos, where the number of pixels could...... subspace have been considered in respect to MIA purposes. First of all, Robust PCA has been applied to several images with and without outliers. Being proposed as a method to deal with high-dimensional data, it suits the needs of MIA very well. Also several non-linear methods have been tried, including...

  16. Geographic Object-Based Image Analysis: Towards a new paradigm

    NARCIS (Netherlands)

    Blaschke, T.; Hay, G.J.; Kelly, M.; Lang, S.; Hofmann, P.; Addink, E.A.; Queiroz Feitosa, R.; van der Meer, F.D.; van der Werff, H.M.A.; van Coillie, F.; Tiede, A.


    The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extr

  17. Facial Image Analysis Based on Local Binary Patterns: A Survey

    NARCIS (Netherlands)

    Huang, D.; Shan, C.; Ardebilian, M.; Chen, L.


    Facial image analysis, including face detection, face recognition,facial expression analysis, facial demographic classification, and so on, is an important and interesting research topic in the computervision and image processing area, which has many important applications such as human-computer

  18. Facial Image Analysis Based on Local Binary Patterns: A Survey

    NARCIS (Netherlands)

    Huang, D.; Shan, C.; Ardebilian, M.; Chen, L.


    Facial image analysis, including face detection, face recognition,facial expression analysis, facial demographic classification, and so on, is an important and interesting research topic in the computervision and image processing area, which has many important applications such as human-computer

  19. Digital image processing and analysis for activated sludge wastewater treatment. (United States)

    Khan, Muhammad Burhan; Lee, Xue Yong; Nisar, Humaira; Ng, Choon Aun; Yeap, Kim Ho; Malik, Aamir Saeed


    Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.

  20. Multimodal digital color imaging system for facial skin lesion analysis (United States)

    Bae, Youngwoo; Lee, Youn-Heum; Jung, Byungjo


    In dermatology, various digital imaging modalities have been used as an important tool to quantitatively evaluate the treatment effect of skin lesions. Cross-polarization color image was used to evaluate skin chromophores (melanin and hemoglobin) information and parallel-polarization image to evaluate skin texture information. In addition, UV-A induced fluorescent image has been widely used to evaluate various skin conditions such as sebum, keratosis, sun damages, and vitiligo. In order to maximize the evaluation efficacy of various skin lesions, it is necessary to integrate various imaging modalities into an imaging system. In this study, we propose a multimodal digital color imaging system, which provides four different digital color images of standard color image, parallel and cross-polarization color image, and UV-A induced fluorescent color image. Herein, we describe the imaging system and present the examples of image analysis. By analyzing the color information and morphological features of facial skin lesions, we are able to comparably and simultaneously evaluate various skin lesions. In conclusion, we are sure that the multimodal color imaging system can be utilized as an important assistant tool in dermatology.

  1. Analysis of Images from Experiments Investigating Fragmentation of Materials

    Energy Technology Data Exchange (ETDEWEB)

    Kamath, C; Hurricane, O


    Image processing techniques have been used extensively to identify objects of interest in image data and extract representative characteristics for these objects. However, this can be a challenge due to the presence of noise in the images and the variation across images in a dataset. When the number of images to be analyzed is large, the algorithms used must also be relatively insensitive to the choice of parameters and lend themselves to partial or full automation. This not only avoids manual analysis which can be time consuming and error-prone, but also makes the analysis reproducible, thus enabling comparisons between images which have been processed in an identical manner. In this paper, we describe our approach to extracting features for objects of interest in experimental images. Focusing on the specific problem of fragmentation of materials, we show how we can extract statistics for the fragments and the gaps between them.

  2. PIZZARO: Forensic analysis and restoration of image and video data. (United States)

    Kamenicky, Jan; Bartos, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozamsky, Adam; Saic, Stanislav; Sroubek, Filip; Sorel, Michal; Zita, Ales; Zitova, Barbara; Sima, Zdenek; Svarc, Petr; Horinek, Jan


    This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences.

  3. An application of image processing techniques in computed tomography image analysis

    DEFF Research Database (Denmark)

    McEvoy, Fintan


    An estimate of the thickness of subcutaneous adipose tissue at differing positions around the body was required in a study examining body composition. To eliminate human error associated with the manual placement of markers for measurements and to facilitate the collection of data from a large...... number of animals and image slices, automation of the process was desirable. The open-source and free image analysis program ImageJ was used. A macro procedure was created that provided the required functionality. The macro performs a number of basic image processing procedures. These include an initial...... process designed to remove the scanning table from the image and to center the animal in the image. This is followed by placement of a vertical line segment from the mid point of the upper border of the image to the image center. Measurements are made between automatically detected outer and inner...

  4. A linear mixture analysis-based compression for hyperspectral image analysis

    Energy Technology Data Exchange (ETDEWEB)

    C. I. Chang; I. W. Ginsberg


    In this paper, the authors present a fully constrained least squares linear spectral mixture analysis-based compression technique for hyperspectral image analysis, particularly, target detection and classification. Unlike most compression techniques that directly deal with image gray levels, the proposed compression approach generates the abundance fractional images of potential targets present in an image scene and then encodes these fractional images so as to achieve data compression. Since the vital information used for image analysis is generally preserved and retained in the abundance fractional images, the loss of information may have very little impact on image analysis. In some occasions, it even improves analysis performance. Airborne visible infrared imaging spectrometer (AVIRIS) data experiments demonstrate that it can effectively detect and classify targets while achieving very high compression ratios.

  5. Dynamic Chest Image Analysis: Evaluation of Model-Based Pulmonary Perfusion Analysis With Pyramid Images (United States)


    Address(es) US Army Research, Development & Standardization Group (UK) PSC 802 Box 15 FPO AE 09499-1500 Sponsor/Monitor’s Acronym(s) Sponsor...6G O D 2 O P " GH I KJML E8 O D 83O P " (8) This naturally implies that as long as O D 2 O P KJ...A method for the solution of certain problems in least squares. Quart. Appl. Math ., 2:164–168, 1944. [8] J. Liang. Dynamic Chest Image Analysis. Turku

  6. Whole-slide imaging and automated image analysis: considerations and opportunities in the practice of pathology. (United States)

    Webster, J D; Dunstan, R W


    Digital pathology, the practice of pathology using digitized images of pathologic specimens, has been transformed in recent years by the development of whole-slide imaging systems, which allow for the evaluation and interpretation of digital images of entire histologic sections. Applications of whole-slide imaging include rapid transmission of pathologic data for consultations and collaborations, standardization and distribution of pathologic materials for education, tissue specimen archiving, and image analysis of histologic specimens. Histologic image analysis allows for the acquisition of objective measurements of histomorphologic, histochemical, and immunohistochemical properties of tissue sections, increasing both the quantity and quality of data obtained from histologic assessments. Currently, numerous histologic image analysis software solutions are commercially available. Choosing the appropriate solution is dependent on considerations of the investigative question, computer programming and image analysis expertise, and cost. However, all studies using histologic image analysis require careful consideration of preanalytical variables, such as tissue collection, fixation, and processing, and experimental design, including sample selection, controls, reference standards, and the variables being measured. The fields of digital pathology and histologic image analysis are continuing to evolve, and their potential impact on pathology is still growing. These methodologies will increasingly transform the practice of pathology, allowing it to mature toward a quantitative science. However, this maturation requires pathologists to be at the forefront of the process, ensuring their appropriate application and the validity of their results. Therefore, histologic image analysis and the field of pathology should co-evolve, creating a symbiotic relationship that results in high-quality reproducible, objective data.


    Institute of Scientific and Technical Information of China (English)

    纳瑟; 刘重庆


    A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K-means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model,gray level l, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.


    Institute of Scientific and Technical Information of China (English)


    In order to enhance the image information from multi-sensor and to improve the abilities of theinformation analysis and the feature extraction, this letter proposed a new fusion approach in pixel level bymeans of the Wavelet Packet Transform (WPT). The WPT is able to decompose an image into low frequencyband and high frequency band in higher scale. It offers a more precise method for image analysis than Wave-let Transform (WT). Firstly, the proposed approach employs HIS (Hue, Intensity, Saturation) transform toobtain the intensity component of CBERS (China-Brazil Earth Resource Satellite) multi-spectral image. ThenWPT transform is employed to decompose the intensity component and SPOT (Systeme Pour I'Observationde la Therre ) image into low frequency band and high frequency band in three levels. Next, two high fre-quency coefficients and low frequency coefficients of the images are combined by linear weighting strategies.Finally, the fused image is obtained with inverse WPT and inverse HIS. The results show the new approachcan fuse details of input image successfully, and thereby can obtain a more satisfactory result than that of HM(Histogram Matched)-based fusion algorithm and WT-based fusion approach.

  9. Electromagnetic Time Reversal Imaging: Analysis and Experimentation (United States)


    Biomedical Imaging: From Nano to Macro, ISBI󈧌, Paris, Friance, May 14-17, 2008 [6] Y. Jin, J. M. F. Moura, N. O’Donoughue, "Adaptive Time Reversal...Zhu, and Q. He, “Breast cancer detection by time reversal imaging,” 5th IEEE International Symposium on Biomedical Imaging: From Nano to (a galvanized steel sheet) is surrounded by a large amount of PVC rods. Our experiments showed that the collected EM data in frequency and

  10. Vision communications based on LED array and imaging sensor (United States)

    Yoo, Jong-Ho; Jung, Sung-Yoon


    In this paper, we propose a brand new communication concept, called as "vision communication" based on LED array and image sensor. This system consists of LED array as a transmitter and digital device which include image sensor such as CCD and CMOS as receiver. In order to transmit data, the proposed communication scheme simultaneously uses the digital image processing and optical wireless communication scheme. Therefore, the cognitive communication scheme is possible with the help of recognition techniques used in vision system. By increasing data rate, our scheme can use LED array consisting of several multi-spectral LEDs. Because arranged each LED can emit multi-spectral optical signal such as visible, infrared and ultraviolet light, the increase of data rate is possible similar to WDM and MIMO skills used in traditional optical and wireless communications. In addition, this multi-spectral capability also makes it possible to avoid the optical noises in communication environment. In our vision communication scheme, the data packet is composed of Sync. data and information data. Sync. data is used to detect the transmitter area and calibrate the distorted image snapshots obtained by image sensor. By making the optical rate of LED array be same with the frame rate (frames per second) of image sensor, we can decode the information data included in each image snapshot based on image processing and optical wireless communication techniques. Through experiment based on practical test bed system, we confirm the feasibility of the proposed vision communications based on LED array and image sensor.

  11. Prototype for Meta-Algorithmic, Content-Aware Image Analysis (United States)


    PROTOTYPE FOR META- ALGORITHMIC , CONTENT-AWARE IMAGE ANALYSIS UNIVERSITY OF VIRGINIA MARCH 2015 FINAL TECHNICAL REPORT...Visual Object Recognition : A Review." IEEE Trans. on Pattern Analysis and Machine Analysis , 2013. [32] Rakotomamonjy A., Bach F., Canu S., Y...Learning a Discriminative Dictionary for Recognition ," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 11, pp. 2651 - 2664

  12. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics. (United States)

    Niessen, Wiro J


    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Adaptive Local Image Registration: Analysis on Filter Size


    Vishnukumar S; M.Wilscy


    Adaptive Local Image Registration is a Local Image Registration based on an Adaptive Filtering frame work. A filter of appropriate size convolves with reference image and gives the pixel values corresponding to the distorted image and the filter is updated in each stage of the convolution. When the filter converges to the system model, it provides the registered image. The filter size plays an important role in this method. The analysis on the filter size is done using Peak Signal-to-Noise Ra...

  14. Image analysis benchmarking methods for high-content screen design. (United States)

    Fuller, C J; Straight, A F


    The recent development of complex chemical and small interfering RNA (siRNA) collections has enabled large-scale cell-based phenotypic screening. High-content and high-throughput imaging are widely used methods to record phenotypic data after chemical and small interfering RNA treatment, and numerous image processing and analysis methods have been used to quantify these phenotypes. Currently, there are no standardized methods for evaluating the effectiveness of new and existing image processing and analysis tools for an arbitrary screening problem. We generated a series of benchmarking images that represent commonly encountered variation in high-throughput screening data and used these image standards to evaluate the robustness of five different image analysis methods to changes in signal-to-noise ratio, focal plane, cell density and phenotype strength. The analysis methods that were most reliable, in the presence of experimental variation, required few cells to accurately distinguish phenotypic changes between control and experimental data sets. We conclude that by applying these simple benchmarking principles an a priori estimate of the image acquisition requirements for phenotypic analysis can be made before initiating an image-based screen. Application of this benchmarking methodology provides a mechanism to significantly reduce data acquisition and analysis burdens and to improve data quality and information content.

  15. Multivariate image analysis for quality inspection in fish feed production

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg

    , or synthesised chemically. Common for both types is that they are relatively expensive in comparison to the other feed ingredients. This thesis investigates multi-variate data collection for visual inspection and optimisation of industrial production in the fish feed industry. Quality parameters focused on here...... are: pellet size, type and concentration level of astaxanthin in pellet coating, as well as astaxanthin type detected in salmonid fish. Methods used are three different devices for multi- and hyper-spectral imaging, together with shape analysis and multi-variate statistical analysis. The results...... of the work demonstrate a high potential of image analysis and spectral imaging for assessing the product quality of fish feed pellets, astaxanthin and fish meat. We show how image analysis can be used to inspect the pellet size, and how spectral imaging can be used to inspect the surface quality...

  16. Quantitative methods for the analysis of electron microscope images

    DEFF Research Database (Denmark)

    Skands, Peter Ulrik Vallø


    The topic of this thesis is an general introduction to quantitative methods for the analysis of digital microscope images. The images presented are primarily been acquired from Scanning Electron Microscopes (SEM) and interfermeter microscopes (IFM). The topic is approached though several examples...... foundation of the thesis fall in the areas of: 1) Mathematical Morphology; 2) Distance transforms and applications; and 3) Fractal geometry. Image analysis opens in general the possibility of a quantitative and statistical well founded measurement of digital microscope images. Herein lies also the conditions...

  17. Theoretical analysis of radiographic images by nonstationary Poisson processes

    Energy Technology Data Exchange (ETDEWEB)

    Tanaka, K.; Uchida, S. (Gifu Univ. (Japan)); Yamada, I.


    This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process.

  18. Theoretical Analysis of Radiographic Images by Nonstationary Poisson Processes (United States)

    Tanaka, Kazuo; Yamada, Isao; Uchida, Suguru


    This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples of the one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process.

  19. Automated thermal mapping techniques using chromatic image analysis (United States)

    Buck, Gregory M.


    Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

  20. Image Harvest: an open-source platform for high-throughput plant image processing and analysis. (United States)

    Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal


    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets.

  1. Introducing PLIA: Planetary Laboratory for Image Analysis (United States)

    Peralta, J.; Hueso, R.; Barrado, N.; Sánchez-Lavega, A.


    We present a graphical software tool developed under IDL software to navigate, process and analyze planetary images. The software has a complete Graphical User Interface and is cross-platform. It can also run under the IDL Virtual Machine without the need to own an IDL license. The set of tools included allow image navigation (orientation, centring and automatic limb determination), dynamical and photometric atmospheric measurements (winds and cloud albedos), cylindrical and polar projections, as well as image treatment under several procedures. Being written in IDL, it is modular and easy to modify and grow for adding new capabilities. We show several examples of the software capabilities with Galileo-Venus observations: Image navigation, photometrical corrections, wind profiles obtained by cloud tracking, cylindrical projections and cloud photometric measurements. Acknowledgements: This work has been funded by Spanish MCYT PNAYA2003-03216, fondos FEDER and Grupos UPV 15946/2004. R. Hueso acknowledges a post-doc fellowship from Gobierno Vasco.


    Institute of Scientific and Technical Information of China (English)


    Remote Sensing image fusion is an effective way to use the large volume of data from multi-source images.This paper introduces a new method of remote sensing image fusion based on support vector machine (SVM), using highspatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4. Firstly, the new method is established bybuilding a model of remote sensing image fusion based on SVM. Then by using SPIN-2 data and SPOT-4 data, image classification fusion is tested. Finally, an evaluation of the fusion result is made in two ways. 1 ) From subjectivity assessment,the spatial resolution of the fused image is improved compared to the SPOT-4. And it is clearly that the texture of thefused image is distinctive. 2) From quantitative analysis, the effect of classification fusion is better. As a whole, the result shows that the accuracy of image fusion based on SVM is high and the SVM algorithm can be recommended for application in remote sensing image fusion processes.


    Institute of Scientific and Technical Information of China (English)

    ZHAOShu-he; FENGXue-zhi; 等


    Remote Sensing image fusion is an effective way to use the large volume of data from multi-source images.This paper introduces a new method of remote sensing image fusion based on support vector machine(SVM),using high spatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4.Firstly,the new method is established by building a model of remote sensing image fusion based on SVM.Then by using SPIN-2 data and SPOT-4 data ,image classify-cation fusion in tested.Finally,and evaluation of the fusion result is made in two ways.1)From subjectivity assessment,the spatial resolution of the fused image is improved compared to the SPOT-4.And it is clearly that the texture of the fused image is distinctive.2)From quantitative analysis,the effect of classification fusion is better.As a whole ,the re-sult shows that the accuracy of image fusion based on SVM is high and the SVM algorithm can be recommended for applica-tion in remote sensing image fusion processes.

  4. Social Media Image Analysis for Public Health



    Several projects have shown the feasibility to use textual social media data to track public health concerns, such as temporal influenza patterns or geographical obesity patterns. In this paper, we look at whether geo-tagged images from Instagram also provide a viable data source. Especially for "lifestyle" diseases, such as obesity, drinking or smoking, images of social gatherings could provide information that is not necessarily shared in, say, tweets. In this study, we explore whether (i) ...

  5. Autonomous image data reduction by analysis and interpretation (United States)

    Eberlein, Susan; Yates, Gigi; Ritter, Niles

    Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision-making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

  6. Exploiting multi-context analysis in semantic image classification

    Institute of Scientific and Technical Information of China (English)

    TIAN Yong-hong; HUANG Tie-jun; GAO Wen


    As the popularity of digital images is rapidly increasing on the Internet, research on technologies for semantic image classification has become an important research topic. However, the well-known content-based image classification methods do not overcome the so-called semantic gap problem in which low-level visual features cannot represent the high-level semantic content of images. Image classification using visual and textual information often performs poorly since the extracted textual features are often too limited to accurately represent the images. In this paper, we propose a semantic image classification approach using multi-context analysis. For a given image, we model the relevant textual information as its multi-modal context, and regard the related images connected by hyperlinks as its link context. Two kinds of context analysis models, i.e., cross-modal correlation analysis and link-based correlation model, are used to capture the correlation among different modals of features and the topical dependency among images induced by the link structure. We propose a new collective classification model called relational support vector classifier (RSVC) based on the well-known Support Vector Machines (SVMs) and the link-based correlation model. Experiments showed that the proposed approach significantly improved classification accuracy over that of SVM classifiers using visual and/or textual features.

  7. Diagnostic imaging analysis of the impacted mesiodens

    Energy Technology Data Exchange (ETDEWEB)

    Noh, Jeong Jun; Choi, Bo Ram; Jeong, Hwan Seok; Huh, Kyung Hoe; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Choi, Soon Chul [School of Dentistry, Seoul National University, Seoul (Korea, Republic of)


    The research was performed to predict the three dimensional relationship between the impacted mesiodens and the maxillary central incisors and the proximity with the anatomic structures by comparing their panoramic images with the CT images. Among the patients visiting Seoul National University Dental Hospital from April 2003 to July 2007, those with mesiodens were selected (154 mesiodens of 120 patients). The numbers, shapes, orientation and positional relationship of mesiodens with maxillary central incisors were investigated in the panoramic images. The proximity with the anatomical structures and complications were investigated in the CT images as well. The sex ratio (M : F) was 2.28 : 1 and the mean number of mesiodens per one patient was 1.28. Conical shape was 84.4% and inverted orientation was 51.9%. There were more cases of anatomical structures encroachment, especially on the nasal floor and nasopalatine duct, when the mesiodens was not superimposed with the central incisor. There were, however, many cases of the nasopalatine duct encroachment when the mesiodens was superimpoised with the apical 1/3 of central incisor (52.6%). Delayed eruption (55.6%), crown rotation (66.7%) and crown resorption (100%) were observed when the mesiodens was superimposed with the crown of the central incisor. It is possible to predict three dimensional relationship between the impacted mesiodens and the maxillary central incisors in the panoramic images, but more details should be confirmed by the CT images when necessary.

  8. Efficiency analysis of color image filtering

    Directory of Open Access Journals (Sweden)

    Egiazarian Karen


    Full Text Available Abstract This article addresses under which conditions filtering can visibly improve the image quality. The key points are the following. First, we analyze filtering efficiency for 25 test images, from the color image database TID2008. This database allows assessing filter efficiency for images corrupted by different noise types for several levels of noise variance. Second, the limit of filtering efficiency is determined for independent and identically distributed (i.i.d. additive noise and compared to the output mean square error of state-of-the-art filters. Third, component-wise and vector denoising is studied, where the latter approach is demonstrated to be more efficient. Fourth, using of modern visual quality metrics, we determine that for which levels of i.i.d. and spatially correlated noise the noise in original images or residual noise and distortions because of filtering in output images are practically invisible. We also demonstrate that it is possible to roughly estimate whether or not the visual quality can clearly be improved by filtering.

  9. Digital image processing and analysis human and computer vision applications with CVIPtools

    CERN Document Server

    Umbaugh, Scott E


    Section I Introduction to Digital Image Processing and AnalysisDigital Image Processing and AnalysisOverviewImage Analysis and Computer VisionImage Processing and Human VisionKey PointsExercisesReferencesFurther ReadingComputer Imaging SystemsImaging Systems OverviewImage Formation and SensingCVIPtools SoftwareImage RepresentationKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingSection II Digital Image Analysis and Computer VisionIntroduction to Digital Image AnalysisIntroductionPreprocessingBinary Image AnalysisKey PointsExercisesSupplementary ExercisesReferencesFurther Read

  10. Comparing methods for analysis of biomedical hyperspectral image data (United States)

    Leavesley, Silas J.; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter F.; Annamdevula, Naga S.; Rich, Thomas C.


    Over the past 2 decades, hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field. Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems. Enabling this growth has been the availability of faster, more effective hyperspectral filtering technologies and more sensitive detectors. Hence, the potential for growth of biomedical hyperspectral imaging is high, and many hyperspectral imaging options are already commercially available. However, despite the growth in hyperspectral technologies for biomedical imaging, little work has been done to aid users of hyperspectral imaging instruments in selecting appropriate analysis algorithms. Here, we present an approach for comparing the effectiveness of spectral analysis algorithms by combining experimental image data with a theoretical "what if" scenario. This approach allows us to quantify several key outcomes that characterize a hyperspectral imaging study: linearity of sensitivity, positive detection cut-off slope, dynamic range, and false positive events. We present results of using this approach for comparing the effectiveness of several common spectral analysis algorithms for detecting weak fluorescent protein emission in the midst of strong tissue autofluorescence. Results indicate that this approach should be applicable to a very wide range of applications, allowing a quantitative assessment of the effectiveness of the combined biology, hardware, and computational analysis for detecting a specific molecular signature.

  11. Pattern recognition software and techniques for biological image analysis.

    Directory of Open Access Journals (Sweden)

    Lior Shamir

    Full Text Available The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.

  12. Pattern recognition software and techniques for biological image analysis. (United States)

    Shamir, Lior; Delaney, John D; Orlov, Nikita; Eckley, D Mark; Goldberg, Ilya G


    The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.

  13. Research of second harmonic generation images based on texture analysis (United States)

    Liu, Yao; Li, Yan; Gong, Haiming; Zhu, Xiaoqin; Huang, Zufang; Chen, Guannan


    Texture analysis plays a crucial role in identifying objects or regions of interest in an image. It has been applied to a variety of medical image processing, ranging from the detection of disease and the segmentation of specific anatomical structures, to differentiation between healthy and pathological tissues. Second harmonic generation (SHG) microscopy as a potential noninvasive tool for imaging biological tissues has been widely used in medicine, with reduced phototoxicity and photobleaching. In this paper, we clarified the principles of texture analysis including statistical, transform, structural and model-based methods and gave examples of its applications, reviewing studies of the technique. Moreover, we tried to apply texture analysis to the SHG images for the differentiation of human skin scar tissues. Texture analysis method based on local binary pattern (LBP) and wavelet transform was used to extract texture features of SHG images from collagen in normal and abnormal scars, and then the scar SHG images were classified into normal or abnormal ones. Compared with other texture analysis methods with respect to the receiver operating characteristic analysis, LBP combined with wavelet transform was demonstrated to achieve higher accuracy. It can provide a new way for clinical diagnosis of scar types. At last, future development of texture analysis in SHG images were discussed.

  14. Evaluation of port-wine stain treatment outcomes using multispectral imaging (United States)

    Samatham, Ravikant; Choudhury, Niloy; Krol, Alfons L.; Jacques, Steven L.


    Port-wine Stain (PWS) is a vascular malformation characterized by ectasia of superficial dermal capillaries. The flash-lamp pumped pulsed dye laser (PDL) treatment has been the mainstay of PWS for the last decade. Despite the success of the PDL in significantly fading the PWS, the overall cure rate is less than 10%. The precise efficacy of an individual PDL treatment is hard to evaluate and the treatment outcome is measured by visual observation of clinical fading. A hand-held multi-spectral imaging system was developed to image PWS before and after PDL treatment. In an NIH-funded pilot study multi-spectral camera was used to image PWS in children (2- 17 years). Oxygen saturation (S) and blood content (B) of PWS before and after the treatment was determined by analysis of the reflectance spectra. The outcome of the treatment was evaluated during follow up visits of the patients. One of the major causes of failure of laser therapy of port-wine stains (PWS) is reperfusion of the lesion after laser treatment. Oxygen saturation and blood content maps of PWS before and after treatment can predict regions of reperfusion and subsequent failure of the treatment. The ability to measure reperfusion and to predict lesions or areas susceptible to reperfusion, will help in selection of patients/lesions for laser treatment and help to optimize laser dosimetry for maximum effect. The current studies also should provide a basis for monitoring of future alternative therapies or enhancers of laser treatment in resistant cases.

  15. Image analysis of moving seeds in an indented cylinder

    DEFF Research Database (Denmark)

    Buus, Ole; Jørgensen, Johannes Ravn


    -Spline surfaces. Using image analysis, the seeds will be tracked using a kalman filter and the 2D trajectory, length, velocity, weight, and rotation will be sampled. We expect a high correspondence between seed length and certain spatially optimal seed trajectories. This work is done in collaboration with Westrup...... work we will seek to understand more about the internal dynamics of the indented cylinder. We will apply image analysis to observe the movement of seeds in the indented cylinder. This work is laying the groundwork for future studies into the application of image analysis as a tool for autonomous...

  16. Applications of Digital Image Analysis in Experimental Mechanics

    DEFF Research Database (Denmark)

    Lyngbye, J. : Ph.D.

    The present thesis "Application of Digital Image Analysis in Experimental Mechanics" has been prepared as a part of Janus Lyngbyes Ph.D. study during the period December 1988 to June 1992 at the Department of Building technology and Structural Engineering, University of Aalborg, Denmark....... In this thesis attention will be focused on optimal use and analysis of the information of digital images. This is realized during investigation and application of parametric methods in digital image analysis. The parametric methods will be implemented in applications representative for the area of experimental...

  17. Uncooled LWIR imaging: applications and market analysis (United States)

    Takasawa, Satomi


    The evolution of infrared (IR) imaging sensor technology for defense market has played an important role in developing commercial market, as dual use of the technology has expanded. In particular, technologies of both reduction in pixel pitch and vacuum package have drastically evolved in the area of uncooled Long-Wave IR (LWIR; 8-14 μm wavelength region) imaging sensor, increasing opportunity to create new applications. From the macroscopic point of view, the uncooled LWIR imaging market is divided into two areas. One is a high-end market where uncooled LWIR imaging sensor with sensitivity as close to that of cooled one as possible is required, while the other is a low-end market which is promoted by miniaturization and reduction in price. Especially, in the latter case, approaches towards consumer market have recently appeared, such as applications of uncooled LWIR imaging sensors to night visions for automobiles and smart phones. The appearance of such a kind of commodity surely changes existing business models. Further technological innovation is necessary for creating consumer market, and there will be a room for other companies treating components and materials such as lens materials and getter materials and so on to enter into the consumer market.

  18. Analysis of filtering techniques and image quality in pixel duplicated images (United States)

    Mehrubeoglu, Mehrube; McLauchlan, Lifford


    When images undergo filtering operations, valuable information can be lost besides the intended noise or frequencies due to averaging of neighboring pixels. When the image is enlarged by duplicating pixels, such filtering effects can be reduced and more information retained, which could be critical when analyzing image content automatically. Analysis of retinal images could reveal many diseases at early stage as long as minor changes that depart from a normal retinal scan can be identified and enhanced. In this paper, typical filtering techniques are applied to an early stage diabetic retinopathy image which has undergone digital pixel duplication. The same techniques are applied to the original images for comparison. The effects of filtering are then demonstrated for both pixel duplicated and original images to show the information retention capability of pixel duplication. Image quality is computed based on published metrics. Our analysis shows that pixel duplication is effective in retaining information on smoothing operations such as mean filtering in the spatial domain, as well as lowpass and highpass filtering in the frequency domain, based on the filter window size. Blocking effects due to image compression and pixel duplication become apparent in frequency analysis.

  19. Basic research planning in mathematical pattern recognition and image analysis (United States)

    Bryant, J.; Guseman, L. F., Jr.


    Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

  20. An Analysis of the Magneto-Optic Imaging System (United States)

    Nath, Shridhar


    The Magneto-Optic Imaging system is being used for the detection of defects in airframes and other aircraft structures. The system has been successfully applied to detecting surface cracks, but has difficulty in the detection of sub-surface defects such as corrosion. The intent of the grant was to understand the physics of the MOI better, in order to use it effectively for detecting corrosion and for classifying surface defects. Finite element analysis, image classification, and image processing are addressed.

  1. Computer Vision-Based Image Analysis of Bacteria. (United States)

    Danielsen, Jonas; Nordenfelt, Pontus


    Microscopy is an essential tool for studying bacteria, but is today mostly used in a qualitative or possibly semi-quantitative manner often involving time-consuming manual analysis. It also makes it difficult to assess the importance of individual bacterial phenotypes, especially when there are only subtle differences in features such as shape, size, or signal intensity, which is typically very difficult for the human eye to discern. With computer vision-based image analysis - where computer algorithms interpret image data - it is possible to achieve an objective and reproducible quantification of images in an automated fashion. Besides being a much more efficient and consistent way to analyze images, this can also reveal important information that was previously hard to extract with traditional methods. Here, we present basic concepts of automated image processing, segmentation and analysis that can be relatively easy implemented for use with bacterial research.


    Directory of Open Access Journals (Sweden)

    Chen Chongjie


    Full Text Available Mulan is an ancient Chinese heroine. The story shows that she is the same as other women,having personal life, but also has a heart that loves her country and her parents. She always thinksabout her family, society, dan country. This article was based on library research, using Mulan poemdan a folklore entitled Mulan Pergi Berperang as media to analyze Mulan’s image. It can be said thateventhough at that time there was no gender perspective concept, Mulan had been able to replace herfather to go to war. She gave a lot of contributions for her country, society, and family. Analysisrepresents that Mulan has three images, as a heroine, as a daughter for her family, and self-image orleader for the women. Having good character and spirit to love country, people, and family make herequal to men. And, it makes her respected by people in each generation.

  3. SLAR image interpretation keys for geographic analysis (United States)

    Coiner, J. C.


    A means for side-looking airborne radar (SLAR) imagery to become a more widely used data source in geoscience and agriculture is suggested by providing interpretation keys as an easily implemented interpretation model. Interpretation problems faced by the researcher wishing to employ SLAR are specifically described, and the use of various types of image interpretation keys to overcome these problems is suggested. With examples drawn from agriculture and vegetation mapping, direct and associate dichotomous image interpretation keys are discussed and methods of constructing keys are outlined. Initial testing of the keys, key-based automated decision rules, and the role of the keys in an information system for agriculture are developed.

  4. Automated analysis of protein subcellular location in time series images. (United States)

    Hu, Yanhua; Osuna-Highley, Elvira; Hua, Juchang; Nowicki, Theodore Scott; Stolz, Robert; McKayle, Camille; Murphy, Robert F


    Image analysis, machine learning and statistical modeling have become well established for the automatic recognition and comparison of the subcellular locations of proteins in microscope images. By using a comprehensive set of features describing static images, major subcellular patterns can be distinguished with near perfect accuracy. We now extend this work to time series images, which contain both spatial and temporal information. The goal is to use temporal features to improve recognition of protein patterns that are not fully distinguishable by their static features alone. We have adopted and designed five sets of features for capturing temporal behavior in 2D time series images, based on object tracking, temporal texture, normal flow, Fourier transforms and autoregression. Classification accuracy on an image collection for 12 fluorescently tagged proteins was increased when temporal features were used in addition to static features. Temporal texture, normal flow and Fourier transform features were most effective at increasing classification accuracy. We therefore extended these three feature sets to 3D time series images, but observed no significant improvement over results for 2D images. The methods for 2D and 3D temporal pattern analysis do not require segmentation of images into single cell regions, and are suitable for automated high-throughput microscopy applications. Images, source code and results will be available upon publication at

  5. A Survey on Deep Learning in Medical Image Analysis

    NARCIS (Netherlands)

    Litjens, G.J.; Kooi, T.; Ehteshami Bejnordi, B.; Setio, A.A.A.; Ciompi, F.; Ghafoorian, M.; Laak, J.A.W.M. van der; Ginneken, B. van; Sanchez, C.I.


    Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared

  6. Higher Education Institution Image: A Correspondence Analysis Approach. (United States)

    Ivy, Jonathan


    Investigated how marketing is used to convey higher education institution type image in the United Kingdom and South Africa. Using correspondence analysis, revealed the unique positionings created by old and new universities and technikons in these countries. Also identified which marketing tools they use in conveying their image. (EV)

  7. Spinal X-ray image analysis in scoliosis

    NARCIS (Netherlands)

    Sardjono, Tri Arief


    In this thesis new image analysis methods are discussed to determine the curvature of scoliotic patients characterised by the Cobb angle and to enhance the vertebral parts based on features from a frontal X-ray image. Chapter 1 provides some background information on scoliosis, how to diagnose it, t

  8. Subsurface offset behaviour in velocity analysis with extended reflectivity images

    NARCIS (Netherlands)

    Mulder, W.A.


    Migration velocity analysis with the wave equation can be accomplished by focusing of extended migration images, obtained by introducing a subsurface offset or shift. A reflector in the wrong velocity model will show up as a curve in the extended image. In the correct model, it should collapse to a

  9. Four challenges in medical image analysis from an industrial perspective. (United States)

    Weese, Jürgen; Lorenz, Cristian


    Today's medical imaging systems produce a huge amount of images containing a wealth of information. However, the information is hidden in the data and image analysis algorithms are needed to extract it, to make it readily available for medical decisions and to enable an efficient work flow. Advances in medical image analysis over the past 20 years mean there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. At the same time new challenges have arisen. Firstly, there is a need for more generic image analysis technologies that can be efficiently adapted for a specific clinical task. Secondly, efficient approaches for ground truth generation are needed to match the increasing demands regarding validation and machine learning. Thirdly, algorithms for analyzing heterogeneous image data are needed. Finally, anatomical and organ models play a crucial role in many applications, and algorithms to construct patient-specific models from medical images with a minimum of user interaction are needed. These challenges are complementary to the on-going need for more accurate, more reliable and faster algorithms, and dedicated algorithmic solutions for specific applications.

  10. Disability in Physical Education Textbooks: An Analysis of Image Content (United States)

    Taboas-Pais, Maria Ines; Rey-Cao, Ana


    The aim of this paper is to show how images of disability are portrayed in physical education textbooks for secondary schools in Spain. The sample was composed of 3,316 images published in 36 textbooks by 10 publishing houses. A content analysis was carried out using a coding scheme based on categories employed in other similar studies and adapted…

  11. Principal component analysis of image gradient orientations for face recognition

    NARCIS (Netherlands)

    Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data

  12. 3-dimensional terahertz imaging and analysis of historical art pieces

    DEFF Research Database (Denmark)

    Dandolo, Corinna Ludovica Koch; Jepsen, Peter Uhd

    Imaging with terahertz (THz) waves offers the capability of seeing through traditionally opaque materials, with maintaining a spatial resolution comparable to that of the naked eye. The use of ultrashort THz pulses allow for depth resolved imaging by time-of-flight analysis of reflected signals...

  13. Computerized comprehensive data analysis of Lung Imaging Database Consortium (LIDC)


    Tan, Jun; Pu, Jiantao; Zheng, Bin; Wang, Xingwei; Leader, Joseph K.


    Purpose: Lung Image Database Consortium (LIDC) is the largest public CT image database of lung nodules. In this study, the authors present a comprehensive and the most updated analysis of this dynamically growing database under the help of a computerized tool, aiming to assist researchers to optimally use this database for lung cancer related investigations.

  14. VIDA: an environment for multidimensional image display and analysis (United States)

    Hoffman, Eric A.; Gnanaprakasam, Daniel; Gupta, Krishanu B.; Hoford, John D.; Kugelmass, Steven D.; Kulawiec, Richard S.


    Since the first dynamic volumetric studies were done in the early 1980s on the dynamic spatial reconstructor (DSR), there has been a surge of interest in volumetric and dynamic imaging using a number of tomographic techniques. Knowledge gained in handling DSR image data has readily transferred to the current use of a number of other volumetric and dynamic imaging modalities including cine and spiral CT, MR, and PET. This in turn has lead to our development of a new image display and quantitation package which we have named VIDATM (volumetric image display and analysis). VIDA is written in C, runs under the UNIXTM operating system, and uses the XView toolkit to conform to the Open LookTM graphical user interface specification. A shared memory structure has been designed which allows for the manipulation of multiple volumes simultaneously. VIDA utilizes a windowing environment and allows execution of multiple processes simultaneously. Available programs include: oblique sectioning, volume rendering, region of interest analysis, interactive image segmentation/editing, algebraic image manipulation, conventional cardiac mechanics analysis, homogeneous strain analysis, tissue blood flow evaluation, etc. VIDA is a built modularly, allowing new programs to be developed and integrated easily. An emphasis has been placed upon image quantitation for the purpose of physiological evaluation.

  15. The ImageJ ecosystem: An open platform for biomedical image analysis. (United States)

    Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C; Eliceiri, Kevin W


    Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem.

  16. Survey of Hyperspectral and Multispectral Imaging Technologies (Etude sur les technologies d’imagerie hyperspectrale et multispectrale) (United States)


    Prism-Grating-Prism Imaging Spectrograph 3-4 Figure 5 Basic Principle of the IMSS 3-5 Figure 6 Optical Scheme of Sagnac and Michelson Imaging...the dispersive techniques in imaging spectrometers applications is the Image Multi- Spectral Sensing ( IMSS ) technology, developed and patented by...Pacific Advanced Technology since 1992.The IMSS is based on the principle of diffractive optics; as such it is a combination of a diffractive imaging

  17. On two methods of statistical image analysis

    NARCIS (Netherlands)

    Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, KL


    The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition, smooth

  18. Exploratory matrix factorization for PET image analysis. (United States)

    Kodewitz, A; Keck, I R; Tomé, A M; Lang, E W


    Features are extracted from PET images employing exploratory matrix factorization techniques such as nonnegative matrix factorization (NMF). Appropriate features are fed into classifiers such as a support vector machine or a random forest tree classifier. An automatic feature extraction and classification is achieved with high classification rate which is robust and reliable and can help in an early diagnosis of Alzheimer's disease.

  19. Wound Image Analysis Using Contour Evolution

    Directory of Open Access Journals (Sweden)

    K. Sundeep Kumar


    Full Text Available The aim of the algorithm described in this paper is to segment wound images from the normal and classify them according to the types of the wound. The segmentation of wounds extravagates color representation, which has been followed by an algorithm of grayscale segmentation based on the stack mathematical approach. Accurate classification of wounds and analyzing wound healing process is a critical task for patient care and health cost reduction at hospital. The tissue uniformity and flatness leads to a simplified approach but requires multispectral imaging for enhanced wound delineation. Contour Evolution method which uses multispectral imaging replaces more complex tools such as, SVM supervised classification, as no training step is required. In Contour Evolution, classification can be done by clustering color information, with differential quantization algorithm, the color centroids of small squares taken from segmented part of the wound image in (C1,C2 plane. Where C1, C2 are two chrominance components. Wound healing is identified by measuring the size of the wound through various means like contact and noncontact methods of wound. The wound tissues proportion is also estimated by a qualitative visual assessment based on the red-yellow-black code. Moreover, involving all the spectral response of the tissue and not only RGB components provides a higher discrimination for separating healed epithelial tissue from granulation tissue.

  20. Enhanced Image Analysis Using Cached Mobile Robots

    Directory of Open Access Journals (Sweden)

    Kabeer Mohammed


    Full Text Available In the field of Artificial intelligence Image processing plays a vital role in Decision making .Now a day’s Mobile robots work as a Network sharing Centralized Data base.All Image inputs are compared against this database and decision is made.In some cases the Centralized database is in other side of the globe and Mobile robots compare Input image through satellite link this sometime results in delays in decision making which may result in castrophe.This Research paper is about how to make image processing in mobile robots less time consuming and fast decision making.This research paper compares search techniques employed currently and optimum search method which we are going to state.Now a days Mobile robots are extensively used in environments which are dangerous to human beings.In this dangerous situations quick Decision making makes the difference between Hit and Miss this can also results in Day to day tasks performed by Mobile robots Successful or Failure.

  1. Electron Microscopy and Image Analysis for Selected Materials (United States)

    Williams, George


    This particular project was completed in collaboration with the metallurgical diagnostics facility. The objective of this research had four major components. First, we required training in the operation of the environmental scanning electron microscope (ESEM) for imaging of selected materials including biological specimens. The types of materials range from cyanobacteria and diatoms to cloth, metals, sand, composites and other materials. Second, to obtain training in surface elemental analysis technology using energy dispersive x-ray (EDX) analysis, and in the preparation of x-ray maps of these same materials. Third, to provide training for the staff of the metallurgical diagnostics and failure analysis team in the area of image processing and image analysis technology using NIH Image software. Finally, we were to assist in the sample preparation, observing, imaging, and elemental analysis for Mr. Richard Hoover, one of NASA MSFC's solar physicists and Marshall's principal scientist for the agency-wide virtual Astrobiology Institute. These materials have been collected from various places around the world including the Fox Tunnel in Alaska, Siberia, Antarctica, ice core samples from near Lake Vostoc, thermal vents in the ocean floor, hot springs and many others. We were successful in our efforts to obtain high quality, high resolution images of various materials including selected biological ones. Surface analyses (EDX) and x-ray maps were easily prepared with this technology. We also discovered and used some applications for NIH Image software in the metallurgical diagnostics facility.

  2. Segmentation and learning in the quantitative analysis of microscopy images (United States)

    Ruggiero, Christy; Ross, Amy; Porter, Reid


    In material science and bio-medical domains the quantity and quality of microscopy images is rapidly increasing and there is a great need to automatically detect, delineate and quantify particles, grains, cells, neurons and other functional "objects" within these images. These are challenging problems for image processing because of the variability in object appearance that inevitably arises in real world image acquisition and analysis. One of the most promising (and practical) ways to address these challenges is interactive image segmentation. These algorithms are designed to incorporate input from a human operator to tailor the segmentation method to the image at hand. Interactive image segmentation is now a key tool in a wide range of applications in microscopy and elsewhere. Historically, interactive image segmentation algorithms have tailored segmentation on an image-by-image basis, and information derived from operator input is not transferred between images. But recently there has been increasing interest to use machine learning in segmentation to provide interactive tools that accumulate and learn from the operator input over longer periods of time. These new learning algorithms reduce the need for operator input over time, and can potentially provide a more dynamic balance between customization and automation for different applications. This paper reviews the state of the art in this area, provides a unified view of these algorithms, and compares the segmentation performance of various design choices.

  3. An Improved Algorithm Research on VIS-IR Multi-spectral Thermometry%一种改进的可见-红外多光谱辐射测温反演算法

    Institute of Scientific and Technical Information of China (English)

    张志林; 孙伟民; 邢键; 崔双龙


      在基于参考温度的二次测量法数学模型的基础上,提出了无需假设光谱发射率模型的可见-红外多光谱辐射测温迭代递推算法,并对4种发射率假设模型进行了仿真计算。结果表明:新算法的温度绝对误差小于20 K,发射率趋势也与假设模型的发射率趋势吻合较好。进一步完善了可见-红外多光谱辐射测温理论。%A new iterative algorithm for VIS-IR multi-spectral thermometry is proposed,which has no need to assume the spectral emissivity on the basis of the mathematical model of the secondary measurement method. Four kinds of emissivity assumption model are carried on by the simulation calculation. The simulation results show that the absolute error is within 20K. And the inversion curves of the spectral emissivity are in good agreement with the setting curve of spectral emissivity in the two different cases. The improved novel algorithm moves forward a single step for VIS-IR multi-spectral thermometry.

  4. Determination of fish gender using fractal analysis of ultrasound images

    DEFF Research Database (Denmark)

    McEvoy, Fintan J.; Tomkiewicz, Jonna; Støttrup, Josianne;


    The gender of cod Gadus morhua can be determined by considering the complexity in their gonadal ultrasonographic appearance. The fractal dimension (DB) can be used to describe this feature in images. B-mode gonadal ultrasound images in 32 cod, where gender was known, were collected. Fractal...... by subjective analysis alone. The mean (and standard deviation) of the fractal dimension DB for male fish was 1.554 (0.073) while for female fish it was 1.468 (0.061); the difference was statistically significant (P=0.001). The area under the ROC curve was 0.84 indicating the value of fractal analysis in gender...... result. Fractal analysis is useful for gender determination in cod. This or a similar form of analysis may have wide application in veterinary imaging as a tool for quantification of complexity in images...

  5. A performance analysis system for MEMS using automated imaging methods

    Energy Technology Data Exchange (ETDEWEB)

    LaVigne, G.F.; Miller, S.L.


    The ability to make in-situ performance measurements of MEMS operating at high speeds has been demonstrated using a new image analysis system. Significant improvements in performance and reliability have directly resulted from the use of this system.

  6. Analysis Operator Learning and Its Application to Image Reconstruction

    CERN Document Server

    Hawe, Simon; Diepold, Klaus


    Exploiting a priori known structural information lies at the core of many image reconstruction methods that can be stated as inverse problems. The synthesis model, which assumes that images can be decomposed into a linear combination of very few atoms of some dictionary, is now a well established tool for the design of image reconstruction algorithms. An interesting alternative is the analysis model, where the signal is multiplied by an analysis operator and the outcome is assumed to be the sparse. This approach has only recently gained increasing interest. The quality of reconstruction methods based on an analysis model severely depends on the right choice of the suitable operator. In this work, we present an algorithm for learning an analysis operator from training images. Our method is based on an $\\ell_p$-norm minimization on the set of full rank matrices with normalized columns. We carefully introduce the employed conjugate gradient method on manifolds, and explain the underlying geometry of the constrai...


    Directory of Open Access Journals (Sweden)

    J. W. Zhao


    Full Text Available As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings and the physical parameters of the surface (roughness, correlation length, permittivitywhich determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  8. Multimode optical imaging of small animals: development and applications (United States)

    Hwang, J. Y.; Moffatt-Blue, C.; Equils, O.; Fujita, M.; Jeong, J.; Khazenzon, N. M.; Lindsley, E.; Ljubimova, J.; Nowatzyk, A. G.; Farkas, D. L.; Wachsmann-Hogiu, S.


    We present an optical system for small animal imaging that can combine various in vivo imaging modalities, including fluorescence (intensity and lifetime), spectral, and trans-illumination imaging. This system consists of light-tight box with ultrafast pulsed or cw laser light excitation, motorized translational and rotational stages, a telecentric lens for detection, and a cooled CCD camera that can be coupled to an ultrafast time-gated intensifier. All components are modular, making possible laser excitation at various wavelengths and pulse lengths, and signal detection in a variety of ways (multimode). Results of drug nanoconjugate carrier delivery studies in mice are presented. Conventional and spectrally-resolved fluorescence images reveal details of in vivo drug nanoconjugate carrier accumulation within the tumor region and several organs in real time. By multi-spectral image analysis of ex vivo specimens from the same mice, we were able to evaluate the extent and topology of drug nanoconjugate carrier distribution into specific organs and the tumor itself.

  9. Image Segmentation Analysis for NASA Earth Science Applications (United States)

    Tilton, James C.


    NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

  10. Image analysis of self-organized multicellular patterns

    Directory of Open Access Journals (Sweden)

    Thies Christian


    Full Text Available Analysis of multicellular patterns is required to understand tissue organizational processes. By using a multi-scale object oriented image processing method, the spatial information of cells can be extracted automatically. Instead of manual segmentation or indirect measurements, such as general distribution of contrast or flow, the orientation and distribution of individual cells is extracted for quantitative analysis. Relevant objects are identified by feature queries and no low-level knowledge of image processing is required.

  11. Imaging Heat and Mass Transfer Processes Visualization and Analysis

    CERN Document Server

    Panigrahi, Pradipta Kumar


    Imaging Heat and Mass Transfer Processes: Visualization and Analysis applies Schlieren and shadowgraph techniques to complex heat and mass transfer processes. Several applications are considered where thermal and concentration fields play a central role. These include vortex shedding and suppression from stationary and oscillating bluff bodies such as cylinders, convection around crystals growing from solution, and buoyant jets. Many of these processes are unsteady and three dimensional. The interpretation and analysis of images recorded are discussed in the text.

  12. Independent component analysis applications on THz sensing and imaging (United States)

    Balci, Soner; Maleski, Alexander; Nascimento, Matheus Mello; Philip, Elizabath; Kim, Ju-Hyung; Kung, Patrick; Kim, Seongsin M.


    We report Independent Component Analysis (ICA) technique applied to THz spectroscopy and imaging to achieve a blind source separation. A reference water vapor absorption spectrum was extracted via ICA, then ICA was utilized on a THz spectroscopic image in order to clean the absorption of water molecules from each pixel. For this purpose, silica gel was chosen as the material of interest for its strong water absorption. The resulting image clearly showed that ICA effectively removed the water content in the detected signal allowing us to image the silica gel beads distinctively even though it was totally embedded in water before ICA was applied.

  13. Image registration based on matrix perturbation analysis using spectral graph

    Institute of Scientific and Technical Information of China (English)

    Chengcai Leng; Zheng Tian; Jing Li; Mingtao Ding


    @@ We present a novel perspective on characterizing the spectral correspondence between nodes of the weighted graph with application to image registration.It is based on matrix perturbation analysis on the spectral graph.The contribution may be divided into three parts.Firstly, the perturbation matrix is obtained by perturbing the matrix of graph model.Secondly, an orthogonal matrix is obtained based on an optimal parameter, which can better capture correspondence features.Thirdly, the optimal matching matrix is proposed by adjusting signs of orthogonal matrix for image registration.Experiments on both synthetic images and real-world images demonstrate the effectiveness and accuracy of the proposed method.

  14. A collaborative biomedical image mining framework: application on the image analysis of microscopic kidney biopsies. (United States)

    Goudas, T; Doukas, C; Chatziioannou, A; Maglogiannis, I


    The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, like data acquisition, preprocessing, segmentation, feature extraction and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image data set and experiment type. They may thus necessitate advanced image processing and classification knowledge and skills from the side of the biomedical expert. In this work, an application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of image mining workflows. The described tool can be directly integrated to the RapidMiner, Taverna or similar workflow management platforms. A case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented to demonstrate the functionality of the proposed framework.

  15. Chemical imaging and solid state analysis at compact surfaces using UV imaging

    DEFF Research Database (Denmark)

    Wu, Jian X.; Rehder, Sönke; van den Berg, Frans


    Fast non-destructive multi-wavelength UV imaging together with multivariate image analysis was utilized to visualize distribution of chemical components and their solid state form at compact surfaces. Amorphous and crystalline solid forms of the antidiabetic compound glibenclamide...... and excipients in a non-invasive way, as well as mapping the glibenclamide solid state form. An exploratory data analysis supported the critical evaluation of the mapping results and the selection of model parameters for the chemical mapping. The present study demonstrated that the multi-wavelength UV imaging...

  16. Diagnostic support for glaucoma using retinal images: a hybrid image analysis and data mining approach. (United States)

    Yu, Jin; Abidi, Syed Sibte Raza; Artes, Paul; McIntyre, Andy; Heywood, Malcolm


    The availability of modern imaging techniques such as Confocal Scanning Laser Tomography (CSLT) for capturing high-quality optic nerve images offer the potential for developing automatic and objective methods for diagnosing glaucoma. We present a hybrid approach that features the analysis of CSLT images using moment methods to derive abstract image defining features. The features are then used to train classifers for automatically distinguishing CSLT images of normal and glaucoma patient. As a first, in this paper, we present investigations in feature subset selction methods for reducing the relatively large input space produced by the moment methods. We use neural networks and support vector machines to determine a sub-set of moments that offer high classification accuracy. We demonstratee the efficacy of our methods to discriminate between healthy and glaucomatous optic disks based on shape information automatically derived from optic disk topography and reflectance images.

  17. Digital pathology and image analysis in tissue biomarker research. (United States)

    Hamilton, Peter W; Bankhead, Peter; Wang, Yinhai; Hutchinson, Ryan; Kieran, Declan; McArt, Darragh G; James, Jacqueline; Salto-Tellez, Manuel


    Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

  18. User image mismatch in anaesthesia alarms: a cognitive systems analysis. (United States)

    Raymer, Karen E; Bergström, Johan


    In this study, principles of Cognitive Systems Engineering are used to better understand the human-machine interaction manifesting in the use of anaesthesia alarms. The hypothesis is that the design of the machine incorporates built-in assumptions of the user that are discrepant with the anaesthesiologist's self-assessment, creating 'user image mismatch'. Mismatch was interpreted by focusing on the 'user image' as described from the perspectives of both machine and user. The machine-embedded image was interpreted through document analysis. The user-described image was interpreted through user (anaesthesiologist) interviews. Finally, an analysis was conducted in which the machine-embedded and user-described images were contrasted to identify user image mismatch. It is concluded that analysing user image mismatch expands the focus of attention towards macro-elements in the interaction between man and machine. User image mismatch is interpreted to arise from complexity of algorithm design and incongruity between alarm design and tenets of anaesthesia practice. Cognitive system engineering principles are applied to enhance the understanding of the interaction between anaesthesiologist and alarm. The 'user image' is interpreted and contrasted from the perspectives of machine as well as the user. Apparent machine-user mismatch is explored pertaining to specific design features.

  19. Cardiac nonrigid motion analysis from image sequences

    Institute of Scientific and Technical Information of China (English)

    LIU Huafeng


    Noninvasive estimation of the soft tissue kinematics properties from medical image sequences has many important clinical and physiological implications, such as the diagnosis of heart diseases and the understanding of cardiac mechanics. In this paper, we present a biomechanics based strategy, framed as a priori constraints for the ill-posed motion recovery problema, to realize estimation of the cardiac motion and deformation parameters. By constructing the heart dynamics system equations from biomechanics principles, we use the finite element method to generate smooth estimates.of heart kinematics throughout the cardiac cycle. We present the application of the strategy to the estimation of displacements and strains from in vivo left ventricular magnetic resonance image sequence.

  20. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong


    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  1. Quantitative and qualitative analysis and interpretation of CT perfusion imaging. (United States)

    Valdiviezo, Carolina; Ambrose, Marietta; Mehra, Vishal; Lardo, Albert C; Lima, Joao A C; George, Richard T


    Coronary artery disease (CAD) remains the leading cause of death in the United States. Rest and stress myocardial perfusion imaging has an important role in the non-invasive risk stratification of patients with CAD. However, diagnostic accuracies have been limited, which has led to the development of several myocardial perfusion imaging techniques. Among them, myocardial computed tomography perfusion imaging (CTP) is especially interesting as it has the unique capability of providing anatomic- as well as coronary stenosis-related functional data when combined with computed tomography angiography (CTA). The primary aim of this article is to review the qualitative, semi-quantitative, and quantitative analysis approaches to CTP imaging. In doing so, we will describe the image data required for each analysis and discuss the advantages and disadvantages of each approach.

  2. Analysis and Management System of Digital Ultrasonic Image

    Institute of Scientific and Technical Information of China (English)

    TAO Qiang; ZHANG Hai-yan; LI Xia; WANG Ke


    This paper presents the analysis and management system of digital ultrasonic image. The system can manage medical ultrasonic image by collecting, saving and transferring, and realize that section offices of ultrasonic image in hospital network manage. The system use network technology in transferring image between ultrasonic equipments to share patient data in ultrasonic equipments. And doctors can input patient diagnostic report,saved by text file and case history, digitally managed. The system can be realized by Visual C++ which make windows applied. The system can be brought forward because PACS prevail with various hospitals,but PACS is expensive. In view of this status, we put forward to the analysis and management system of digital ultrasonic image,which is similar to PACS.

  3. 3D Images of Materials Structures Processing and Analysis

    CERN Document Server

    Ohser, Joachim


    Taking and analyzing images of materials' microstructures is essential for quality control, choice and design of all kind of products. Today, the standard method still is to analyze 2D microscopy images. But, insight into the 3D geometry of the microstructure of materials and measuring its characteristics become more and more prerequisites in order to choose and design advanced materials according to desired product properties. This first book on processing and analysis of 3D images of materials structures describes how to develop and apply efficient and versatile tools for geometric analysis

  4. Visualization and Analysis of 3D Microscopic Images (United States)

    Long, Fuhui; Zhou, Jianlong; Peng, Hanchuan


    In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain. PMID:22719236

  5. Micro imaging analysis for osteoporosis assessment

    Energy Technology Data Exchange (ETDEWEB)

    Lima, I., E-mail: inaya@lin.ufrj.b [Nuclear Instrumentation Laboratory, COPPE, UFRJ (Brazil); Polytechnic Institute of Rio de Janeiro State/UERJ/Brazil (Brazil); Farias, M.L.F. [University Hospital, UFRJ, RJ (Brazil); Percegoni, N. [Biophysics Institute, CCS, UFRJ, RJ (Brazil); Rosenthal, D. [Physics Institute, UERJ, RJ (Brazil); Assis, J.T. de [Polytechnic Institute of Rio de Janeiro State/UERJ/Brazil (Brazil); Anjos, M.J. [Physics Institute, UERJ, RJ (Brazil); Lopes, R.T. [Nuclear Instrumentation Laboratory, COPPE, UFRJ (Brazil)


    Characterization of trabeculae structures is one of the most important applications of imaging techniques in the biomedical area. The aim of this study was to investigate structure modifications in trabecular and cortical bones using non destructive techniques such as X-ray microtomography, X-ray microfluorescence by synchrotron radiation and scanning electron microscopy. The results obtained reveal the potential of this computational technique to verify the capability of characterization of internal bone structures.

  6. Forensic Analysis of Digital Image Tampering (United States)


    2.2 – Example of invisible watermark using Steganography Software F5 ............. 8 Figure 2.3 – Example of copy-move image forgery [12...examples of this evolution. Audio has progressed from analog audio tapes and records to Compact Discs and MP3s. Video displays have advanced from the...on it for security or anti-tamper reasons. Figure 2.2 shows an example of this. Figure 2.2 – Example of invisible watermark using Steganography

  7. Imaging System and Method for Biomedical Analysis (United States)


    fluorescent nanoparticles . Generally, Noiseux et al. teach injecting multiple fluorescent nanoparticle dyes into the food sample, imaging the sample a...example, AIDS, malaria , cholera, lymphoma, and typhoid. The present disclosure can be used to capture and count microscopic cells for application as...Base plate 214 is sealed against cover 204 by the adhesive 210. Base plate 214 can have a thickness 216 of, for example, about 100 µm. At least a



    Barrett Lowe; Arun Kulkarni


    Classical methods for classification of pixels in multispectral images include supervised classifiers such as the maximum-likelihood classifier, neural network classifiers, fuzzy neural networks, support vector machines, and decision trees. Recently, there has been an increase of interest in ensemble learning – a method that generates many classifiers and aggregates their results. Breiman proposed Random Forestin 2001 for classification and clustering. Random Forest grows many decision tre...

  9. Measurement and analysis of image sensors (United States)

    Vitek, Stanislav


    For astronomical applications is necessary to have high precision in sensing and processing the image data. In this time are used the large CCD sensors from the various reasons. For the replacement of CCD sensors with CMOS sensing devices is important to know transfer characteristics of used CCD sensors. In the special applications like the robotic telescopes (fully automatic, without human interactions) seems to be good using of specially designed smart sensors, which have integrated more functions and have more features than CCDs.

  10. Real-time video-image analysis (United States)

    Eskenazi, R.; Rayfield, M. J.; Yakimovsky, Y.


    Digitizer and storage system allow rapid random access to video data by computer. RAPID (random-access picture digitizer) uses two commercially-available, charge-injection, solid-state TV cameras as sensors. It can continuously update its memory with each frame of video signal, or it can hold given frame in memory. In either mode, it generates composite video output signal representing digitized image in memory.

  11. An investigation of image compression on NIIRS rating degradation through automated image analysis (United States)

    Chen, Hua-Mei; Blasch, Erik; Pham, Khanh; Wang, Zhonghai; Chen, Genshe


    The National Imagery Interpretability Rating Scale (NIIRS) is a subjective quantification of static image widely adopted by the Geographic Information System (GIS) community. Efforts have been made to relate NIIRS image quality to sensor parameters using the general image quality equations (GIQE), which make it possible to automatically predict the NIIRS rating of an image through automated image analysis. In this paper, we present an automated procedure to extract line edge profile based on which the NIIRS rating of a given image can be estimated through the GIQEs if the ground sampling distance (GSD) is known. Steps involved include straight edge detection, edge stripes determination, and edge intensity determination, among others. Next, we show how to employ GIQEs to estimate NIIRS degradation without knowing the ground truth GSD and investigate the effects of image compression on the degradation of an image's NIIRS rating. Specifically, we consider JPEG and JPEG2000 image compression standards. The extensive experimental results demonstrate the effect of image compression on the ground sampling distance and relative edge response, which are the major factors effecting NIIRS rating.

  12. Method for measuring anterior chamber volume by image analysis (United States)

    Zhai, Gaoshou; Zhang, Junhong; Wang, Ruichang; Wang, Bingsong; Wang, Ningli


    Anterior chamber volume (ACV) is very important for an oculist to make rational pathological diagnosis as to patients who have some optic diseases such as glaucoma and etc., yet it is always difficult to be measured accurately. In this paper, a method is devised to measure anterior chamber volumes based on JPEG-formatted image files that have been transformed from medical images using the anterior-chamber optical coherence tomographer (AC-OCT) and corresponding image-processing software. The corresponding algorithms for image analysis and ACV calculation are implemented in VC++ and a series of anterior chamber images of typical patients are analyzed, while anterior chamber volumes are calculated and are verified that they are in accord with clinical observation. It shows that the measurement method is effective and feasible and it has potential to improve accuracy of ACV calculation. Meanwhile, some measures should be taken to simplify the handcraft preprocess working as to images.

  13. Improving lip wrinkles: lipstick-related image analysis. (United States)

    Ryu, Jong-Seong; Park, Sun-Gyoo; Kwak, Taek-Jong; Chang, Min-Youl; Park, Moon-Eok; Choi, Khee-Hwan; Sung, Kyung-Hye; Shin, Hyun-Jong; Lee, Cheon-Koo; Kang, Yun-Seok; Yoon, Moung-Seok; Rang, Moon-Jeong; Kim, Seong-Jin


    The appearance of lip wrinkles is problematic if it is adversely influenced by lipstick make-up causing incomplete color tone, spread phenomenon and pigment remnants. It is mandatory to develop an objective assessment method for lip wrinkle status by which the potential of wrinkle-improving products to lips can be screened. The present study is aimed at finding out the useful parameters from the image analysis of lip wrinkles that is affected by lipstick application. The digital photograph image of lips before and after lipstick application was assessed from 20 female volunteers. Color tone was measured by Hue, Saturation and Intensity parameters, and time-related pigment spread was calculated by the area over vermilion border by image-analysis software (Image-Pro). The efficacy of wrinkle-improving lipstick containing asiaticoside was evaluated from 50 women by using subjective and objective methods including image analysis in a double-blind placebo-controlled fashion. The color tone and spread phenomenon after lipstick make-up were remarkably affected by lip wrinkles. The level of standard deviation by saturation value of image-analysis software was revealed as a good parameter for lip wrinkles. By using the lipstick containing asiaticoside for 8 weeks, the change of visual grading scores and replica analysis indicated the wrinkle-improving effect. As the depth and number of wrinkles were reduced, the lipstick make-up appearance by image analysis also improved significantly. The lip wrinkle pattern together with lipstick make-up can be evaluated by the image-analysis system in addition to traditional assessment methods. Thus, this evaluation system is expected to test the efficacy of wrinkle-reducing lipstick that was not described in previous dermatologic clinical studies.

  14. An approach for quantitative image quality analysis for CT (United States)

    Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe


    An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

  15. Automated image analysis of atomic force microscopy images of rotavirus particles

    Energy Technology Data Exchange (ETDEWEB)

    Venkataraman, S. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Allison, D.P. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Biochemistry, Cellular, and Molecular Biology, University of Tennessee, Knoxville, TN 37996 (United States); Molecular Imaging Inc. Tempe, AZ, 85282 (United States); Qi, H. [Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Morrell-Falvey, J.L. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Kallewaard, N.L. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Crowe, J.E. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Doktycz, M.J. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States)]. E-mail:


    A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM.

  16. Infrared hyperspectral tunable filter imaging spectrometer for remote leak detection, chemical speciation, and stack/vent analysis applications (United States)

    Hinnrichs, Michele


    With support from the Department of Energy, the State of California and the Gas Technology Institute, Pacific Advanced Technology is developing a small field portable infrared imaging spectrometer (Sherlock) based on the advances in hyperspectral tunable filter technology, that will be applied to the detection of fugitive gas leaks. This imaging spectrometer uses the Image Multi-spectral Sensing (IMSS) diffractive optic tunable filter invented by Pacific Advanced Technology . The Sherlock has an embedded digital signal processor for real time detection of the gas leak while surrounded by severe background noise. The infrared sensor engine is a 256 x 320 midwave cooled focal plane array which spans the spectral range from 3 to 5 microns, ideal for most hydrocarbon leaks. The technology is by no means limited to this spectral region, and can just as easily work in the longwave infrared from 8 to 12 microns for chemical detection applications. This paper will present the design of the Sherlock camera as well as processed data collected at a gas processing plant and an instrumented kiln at LSU using the prototype camera. The processed data shows that the IMSS imaging spectrometer, using an all passive approach, has the sensitivity to detect methane gas leaks at short range with a flow rate as low as 0.01 scfm2. In addition, the IMSS imaging spectrometer can measure hot gas plumes at longer ranges. As will be shown in this paper the IMSS can detect and image warm species gas additives of methane and propane in the Kiln exhaust stack. The methane injected gas with a concentration of 72 ppm and the propane with a concentration of 49 ppm (as seen by the IMSS sensor) at a range of 60 meters. The atmospheric path was a stressing environment, being hot and humid, for any imaging infrared spectrometer.

  17. Towards a quantitative OCT image analysis.

    Directory of Open Access Journals (Sweden)

    Marina Garcia Garrido

    Full Text Available Optical coherence tomography (OCT is an invaluable diagnostic tool for the detection and follow-up of retinal pathology in patients and experimental disease models. However, as morphological structures and layering in health as well as their alterations in disease are complex, segmentation procedures have not yet reached a satisfactory level of performance. Therefore, raw images and qualitative data are commonly used in clinical and scientific reports. Here, we assess the value of OCT reflectivity profiles as a basis for a quantitative characterization of the retinal status in a cross-species comparative study.Spectral-Domain Optical Coherence Tomography (OCT, confocal Scanning-Laser Ophthalmoscopy (SLO, and Fluorescein Angiography (FA were performed in mice (Mus musculus, gerbils (Gerbillus perpadillus, and cynomolgus monkeys (Macaca fascicularis using the Heidelberg Engineering Spectralis system, and additional SLOs and FAs were obtained with the HRA I (same manufacturer. Reflectivity profiles were extracted from 8-bit greyscale OCT images using the ImageJ software package ( profiles obtained from OCT scans of all three animal species correlated well with ex vivo histomorphometric data. Each of the retinal layers showed a typical pattern that varied in relative size and degree of reflectivity across species. In general, plexiform layers showed a higher level of reflectivity than nuclear layers. A comparison of reflectivity profiles from specialized retinal regions (e.g. visual streak in gerbils, fovea in non-human primates with respective regions of human retina revealed multiple similarities. In a model of Retinitis Pigmentosa (RP, the value of reflectivity profiles for the follow-up of therapeutic interventions was demonstrated.OCT reflectivity profiles provide a detailed, quantitative description of retinal layers and structures including specialized retinal regions. Our results highlight the

  18. The study of seasonal composition and dynamics of wetland ecosystems and wintering bird habitat at Poyang Lake, PR China using object-based image analysis and field observations (United States)

    Dronova, Iryna

    plant functional types (PFTs) from the medium-resolution Landsat satellite data. I assessed the sensitivity in PFT classification accuracy to image object scale, machine-learning classification method and hierarchical level of vegetation classes determined from ecological functional traits of the locally dominant plant species. Both the overall and class-specific accuracy values were higher at coarser object scales compared to near-pixel levels, regardless of the machine-learning algorithm, with the overall accuracy exceeding 85-90%. However, more narrowly defined PFT classes differed in their highest-accuracy object scale values due to their unique patch structure, ecology of the dominant species and disturbance agents. To improve classification agreement between different levels of vegetation type hierarchy and reduce the uncertainty, future analyses should integrate spectral and geometric properties of vegetation patches with species' functional ecological traits. In periodically flooded wetlands such as Poyang Lake, rapid short-term surface dynamics and frequent inundation may constrain detection of directional long-term effects of climate change, succession or alien species invasions. To address this challenge, I proposed to classify Poyang Lake wetlands into "dynamic cover types" (DCTs) representing short-term ecological regimes shaped by phenology, disturbance and inundation, instead of static classes. I defined and mapped Poyang Lake DCTs for one flood cycle (late summer 2007-late spring 2008) from combined time series of medium-resolution multi-spectral and radar imagery. I further assessed sensitivity of DCTs to hydrological and climatic variation by comparing results with a hypothetical change scenario of a warmer wetter spring simulated by substituting spring 2008 input images with 2007 ones. This analysis identified the major steps in seasonal wetland change driven by flooding and vegetation phenology and spatial differences in change schedules across the

  19. Assessment of cluster yield components by image analysis. (United States)

    Diago, Maria P; Tardaguila, Javier; Aleixos, Nuria; Millan, Borja; Prats-Montalban, Jose M; Cubero, Sergio; Blasco, Jose


    Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way. Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R(2) between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%. The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods. © 2014 Society of Chemical Industry.

  20. Cnn Based Retinal Image Upscaling Using Zero Component Analysis (United States)

    Nasonov, A.; Chesnakov, K.; Krylov, A.


    The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.

  1. Enhanced bone structural analysis through pQCT image preprocessing. (United States)

    Cervinka, T; Hyttinen, J; Sievanen, H


    Several factors, including preprocessing of the image, can affect the reliability of pQCT-measured bone traits, such as cortical area and trabecular density. Using repeated scans of four different liquid phantoms and repeated in vivo scans of distal tibiae from 25 subjects, the performance of two novel preprocessing methods, based on the down-sampling of grayscale intensity histogram and the statistical approximation of image data, was compared to 3 x 3 and 5 x 5 median filtering. According to phantom measurements, the signal to noise ratio in the raw pQCT images (XCT 3000) was low ( approximately 20dB) which posed a challenge for preprocessing. Concerning the cortical analysis, the reliability coefficient (R) was 67% for the raw image and increased to 94-97% after preprocessing without apparent preference for any method. Concerning the trabecular density, the R-values were already high ( approximately 99%) in the raw images leaving virtually no room for improvement. However, some coarse structural patterns could be seen in the preprocessed images in contrast to a disperse distribution of density levels in the raw image. In conclusion, preprocessing cannot suppress the high noise level to the extent that the analysis of mean trabecular density is essentially improved, whereas preprocessing can enhance cortical bone analysis and also facilitate coarse structural analyses of the trabecular region.

  2. Gonio photometric imaging for recording of reflectance spectra of 3D objects (United States)

    Miyake, Yoichi; Tsumura, Norimichi; Haneishi, Hideaki; Hayashi, Junichiro


    In recent years, it is required to develop a system for 3D capture of archives in museums and galleries. In visualizing of 3D object, it is important to reproduce both color and glossiness accurately. Our final goal is to construct digital archival systems in museum and Internet or virtual museum via World Wide Web. To archive our goal, we have developed the multi-spectral imaging systems to record and estimate reflectance spectra of the art paints based on principal component analysis and Wiener estimation method. In this paper, Gonio photometric imaging method is introduced for recording of 3D object. Five-band images of the object are taken under seven different illuminants angles. The set of five-band images are then analyzed on the basis of both dichromatic reflection model and Phong model to extract Gonio photometric information of the object. Prediction of reproduced images of the object under several illuminants and illumination angles is demonstrated and images that are synthesized with 3D wire frame image taken by 3D digitizer are also presented.

  3. Advanced Color Image Processing and Analysis

    CERN Document Server


    This volume does much more than survey modern advanced color processing. Starting with a historical perspective on ways we have classified color, it sets out the latest numerical techniques for analyzing and processing colors, the leading edge in our search to accurately record and print what we see. The human eye perceives only a fraction of available light wavelengths, yet we live in a multicolor world of myriad shining hues. Colors rich in metaphorical associations make us “purple with rage” or “green with envy” and cause us to “see red.” Defining colors has been the work of centuries, culminating in today’s complex mathematical coding that nonetheless remains a work in progress: only recently have we possessed the computing capacity to process the algebraic matrices that reproduce color more accurately. With chapters on dihedral color and image spectrometers, this book provides technicians and researchers with the knowledge they need to grasp the intricacies of today’s color imaging.

  4. Spectral mixture analysis of EELS spectrum-images

    Energy Technology Data Exchange (ETDEWEB)

    Dobigeon, Nicolas [University of Toulouse, IRIT/INP-ENSEEIHT, 2 rue Camichel, 31071 Toulouse Cedex 7 (France); Brun, Nathalie, E-mail: [University of Paris Sud, Laboratoire de Physique des Solides, CNRS, UMR 8502, 91405 Orsay Cedex (France)


    Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, Earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types Horizontal-Ellipsis ) present in an observed scene and to estimate their respective proportions in each mixed pixel of the acquired image. This task is usually referred to as spectral mixture analysis or spectral unmixing (SU). SU aims at decomposing the measured pixel spectrum into a collection of constituent spectra, called endmembers, and a set of corresponding fractions (abundances) that indicate the proportion of each endmember present in the pixel. Similarly, when processing spectrum-images, microscopists usually try to map elemental, physical and chemical state information of a given material. This paper reports how a SU algorithm dedicated to remote sensing hyperspectral images can be successfully applied to analyze spectrum-image resulting from electron energy-loss spectroscopy (EELS). SU generally overcomes standard limitations inherent to other multivariate statistical analysis methods, such as principal component analysis (PCA) or independent component analysis (ICA), that have been previously used to analyze EELS maps. Indeed, ICA and PCA may perform poorly for linear spectral mixture analysis due to the strong dependence between the abundances of the different materials. One example is presented here to demonstrate the potential of this technique for EELS analysis. -- Highlights: Black-Right-Pointing-Pointer EELS spectrum images are identical to hyperspectral images for Earth science. Black-Right-Pointing-Pointer Spectral unmixing algorithms have proliferated in the remote sensing field. Black-Right-Pointing-Pointer These powerful techniques can be successfully applied to EELS mapping. Black-Right-Pointing-Pointer Potential

  5. Spectral mixture analysis of EELS spectrum-images. (United States)

    Dobigeon, Nicolas; Brun, Nathalie


    Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, Earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types…) present in an observed scene and to estimate their respective proportions in each mixed pixel of the acquired image. This task is usually referred to as spectral mixture analysis or spectral unmixing (SU). SU aims at decomposing the measured pixel spectrum into a collection of constituent spectra, called endmembers, and a set of corresponding fractions (abundances) that indicate the proportion of each endmember present in the pixel. Similarly, when processing spectrum-images, microscopists usually try to map elemental, physical and chemical state information of a given material. This paper reports how a SU algorithm dedicated to remote sensing hyperspectral images can be successfully applied to analyze spectrum-image resulting from electron energy-loss spectroscopy (EELS). SU generally overcomes standard limitations inherent to other multivariate statistical analysis methods, such as principal component analysis (PCA) or independent component analysis (ICA), that have been previously used to analyze EELS maps. Indeed, ICA and PCA may perform poorly for linear spectral mixture analysis due to the strong dependence between the abundances of the different materials. One example is presented here to demonstrate the potential of this technique for EELS analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. NEPR Principle Component Analysis - NOAA TIFF Image (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a representation of seafloor topography in Northeast Puerto Rico derived from a bathymetry model with a principle component analysis (PCA). The area...

  7. Quantitative analysis of in vivo confocal microscopy images: a review. (United States)

    Patel, Dipika V; McGhee, Charles N


    In vivo confocal microscopy (IVCM) is a non-invasive method of examining the living human cornea. The recent trend towards quantitative studies using IVCM has led to the development of a variety of methods for quantifying image parameters. When selecting IVCM images for quantitative analysis, it is important to be consistent regarding the location, depth, and quality of images. All images should be de-identified, randomized, and calibrated prior to analysis. Numerous image analysis software are available, each with their own advantages and disadvantages. Criteria for analyzing corneal epithelium, sub-basal nerves, keratocytes, endothelium, and immune/inflammatory cells have been developed, although there is inconsistency among research groups regarding parameter definition. The quantification of stromal nerve parameters, however, remains a challenge. Most studies report lower inter-observer repeatability compared with intra-observer repeatability, and observer experience is known to be an important factor. Standardization of IVCM image analysis through the use of a reading center would be crucial for any future large, multi-centre clinical trials using IVCM.

  8. Visual analysis of the computer simulation for both imaging and non-imaging optical systems (United States)

    Barladian, B. K.; Potemin, I. S.; Zhdanov, D. D.; Voloboy, A. G.; Shapiro, L. S.; Valiev, I. V.; Birukov, E. D.


    Typical results of the optic simulation are images generated on the virtual sensors of various kinds. As a rule, these images represent two-dimensional distribution of the light values in Cartesian coordinates (luminance, illuminance) or in polar coordinates (luminous intensity). Using the virtual sensors allows making the calculation and design of different kinds of illumination devices, providing stray light analysis, synthesizing of photorealistic images of three-dimensional scenes under the complex illumination generated with optical systems, etc. Based on rich experience in the development and practical using of computer systems of virtual prototyping and photorealistic visualization the authors formulated a number of basic requirements for the visualization and analysis of the results of light simulations represented as two-dimensional distribution of luminance, illuminance and luminous intensity values. The requirements include the tone mapping operators, pseudo color imaging, visualization of the spherical panorama, regression analysis, the analysis of the image sections and regions, analysis of pixel values, the image data export, etc. All those requirements were successfully satisfied in designed software component for visual analysis of the light simulation results. The module "LumiVue" is an integral part of "Lumicept" modeling system and the corresponding plug-in of computer-aided design and support for CATIA product. A number of visual examples of analysis of calculated two-dimensional distribution of luminous intensity, illuminance and luminance illustrate the article. The examples are results of simulation and design of lighting optical systems, secondary optics for LEDs, stray light analysis, virtual prototyping and photorealistic rendering.

  9. Analysis of Fast- ICA Algorithm for Separation of Mixed Images

    Directory of Open Access Journals (Sweden)

    Tanmay Awasthy


    Full Text Available Independent component analysis (ICA is a newly developed method in which the aim is to find a linear representation of nongaussian statistics so that the components are statistically independent, or as independent as possible. Such techniques are actively being used in study of both statistical image processing and unsupervised neural learning application. This paper represents the Fast Independent component analysis algorithm for separation of mixed images. To solve the blind signal separation problems Independent component analysis approach used statistical independence of the source signals. This paper focuses on the theory and methods of ICA in contrast to classical transformations along with the applications of this method to blind source separation .For an illustration of the algorithm, visualized the immixing process with a set of images has been done. To express the results of our analysis simulations have been presented.

  10. A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis. (United States)

    Sánchez, Clara I; Hornero, Roberto; López, María I; Aboy, Mateo; Poza, Jesús; Abásolo, Daniel


    We present an automatic image processing algorithm to detect hard exudates. Automatic detection of hard exudates from retinal images is an important problem since hard exudates are associated with diabetic retinopathy and have been found to be one of the most prevalent earliest signs of retinopathy. The algorithm is based on Fisher's linear discriminant analysis and makes use of colour information to perform the classification of retinal exudates. We prospectively assessed the algorithm performance using a database containing 58 retinal images with variable colour, brightness, and quality. Our proposed algorithm obtained a sensitivity of 88% with a mean number of 4.83+/-4.64 false positives per image using the lesion-based performance evaluation criterion, and achieved an image-based classification accuracy of 100% (sensitivity of 100% and specificity of 100%).

  11. Acne image analysis: lesion localization and classification (United States)

    Abas, Fazly Salleh; Kaffenberger, Benjamin; Bikowski, Joseph; Gurcan, Metin N.


    Acne is a common skin condition present predominantly in the adolescent population, but may continue into adulthood. Scarring occurs commonly as a sequel to severe inflammatory acne. The presence of acne and resultant scars are more than cosmetic, with a significant potential to alter quality of life and even job prospects. The psychosocial effects of acne and scars can be disturbing and may be a risk factor for serious psychological concerns. Treatment efficacy is generally determined based on an invalidated gestalt by the physician and patient. However, the validated assessment of acne can be challenging and time consuming. Acne can be classified into several morphologies including closed comedones (whiteheads), open comedones (blackheads), papules, pustules, cysts (nodules) and scars. For a validated assessment, the different morphologies need to be counted independently, a method that is far too time consuming considering the limited time available for a consultation. However, it is practical to record and analyze images since dermatologists can validate the severity of acne within seconds after uploading an image. This paper covers the processes of region-ofinterest determination using entropy-based filtering and thresholding as well acne lesion feature extraction. Feature extraction methods using discrete wavelet frames and gray-level co-occurence matrix were presented and their effectiveness in separating the six major acne lesion classes were discussed. Several classifiers were used to test the extracted features. Correct classification accuracy as high as 85.5% was achieved using the binary classification tree with fourteen principle components used as descriptors. Further studies are underway to further improve the algorithm performance and validate it on a larger database.

  12. Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features. (United States)

    Gevaert, Olivier; Mitchell, Lex A; Achrol, Achal S; Xu, Jiajing; Echegaray, Sebastian; Steinberg, Gary K; Cheshier, Samuel H; Napel, Sandy; Zaharchuk, Greg; Plevritis, Sylvia K


    To derive quantitative image features from magnetic resonance (MR) images that characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to create radiogenomic maps associating these features with various molecular data. Clinical, molecular, and MR imaging data for GBMs in 55 patients were obtained from the Cancer Genome Atlas and the Cancer Imaging Archive after local ethics committee and institutional review board approval. Regions of interest (ROIs) corresponding to enhancing necrotic portions of tumor and peritumoral edema were drawn, and quantitative image features were derived from these ROIs. Robust quantitative image features were defined on the basis of an intraclass correlation coefficient of 0.6 for a digital algorithmic modification and a test-retest analysis. The robust features were visualized by using hierarchic clustering and were correlated with survival by using Cox proportional hazards modeling. Next, these robust image features were correlated with manual radiologist annotations from the Visually Accessible Rembrandt Images (VASARI) feature set and GBM molecular subgroups by using nonparametric statistical tests. A bioinformatic algorithm was used to create gene expression modules, defined as a set of coexpressed genes together with a multivariate model of cancer driver genes predictive of the module's expression pattern. Modules were correlated with robust image features by using the Spearman correlation test to create radiogenomic maps and to link robust image features with molecular pathways. Eighteen image features passed the robustness analysis and were further analyzed for the three types of ROIs, for a total of 54 image features. Three enhancement features were significantly correlated with survival, 77 significant correlations were found between robust quantitative features and the VASARI feature set, and seven image features were correlated with molecular subgroups (P < .05 for all). A radiogenomics map was

  13. Analysis of Two-Dimensional Electrophoresis Gel Images

    DEFF Research Database (Denmark)

    Pedersen, Lars


    This thesis describes and proposes solutions to some of the currently most important problems in pattern recognition and image analysis of two-dimensional gel electrophoresis (2DGE) images. 2DGE is the leading technique to separate individual proteins in biological samples with many biological...... the methods developed in the literature specifically for matching protein spot patterns, the focus is on a method based on neighbourhood relations. These methods are applied to a range of 2DGE protein spot data in a comparative study. The point pattern matching requires segmentation of the gel images...... and since the correct image segmentation can be difficult, a new alternative approach, exploiting prior knowledge from a reference gel about the protein locations to segment an incoming gel image, is proposed....

  14. Image analysis of ocular fundus for retinopathy characterization

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela; Cuadros, Jorge


    Automated analysis of ocular fundus images is a common procedure in countries as England, including both nonemergency examination and retinal screening of patients with diabetes mellitus. This involves digital image capture and transmission of the images to a digital reading center for evaluation and treatment referral. In collaboration with the Optometry Department, University of California, Berkeley, we have tested computer vision algorithms to segment vessels and lesions in ground-truth data (DRIVE database) and hundreds of images of non-macular centric and nonuniform illumination views of the eye fundus from EyePACS program. Methods under investigation involve mathematical morphology (Figure 1) for image enhancement and pattern matching. Recently, we have focused in more efficient techniques to model the ocular fundus vasculature (Figure 2), using deformable contours. Preliminary results show accurate segmentation of vessels and high level of true-positive microaneurysms.

  15. Deep Learning for Intelligent Substation Device Infrared Fault Image Analysis

    Directory of Open Access Journals (Sweden)

    Lin Ying


    Full Text Available As an important kind of data for device status evaluation, the increasing infrared image data in electrical system puts forward a new challenge to traditional manually processing mode. To overcome this problem, this paper proposes a feasible way to automatically process massive infrared fault images. We take advantage of the imaging characteristics of infrared fault images and detect fault regions together with its belonging device part by our proposed algorithm, which first segment images into superpixels, and then adopt the state-of-the-art convolutional and recursive neural network for intelligent object recognition. In the experiment, we compare several unsupervised pre-training methods considering the importance of a pre-train procedure, and discuss the proper parameters for the proposed network. The experimental results show the good performance of our algorithm, and its efficiency for infrared analysis.

  16. Standardization of Image Quality Analysis – ISO 19264

    DEFF Research Database (Denmark)

    Kejser, Ulla Bøgvad; Wüller, Dietmar


    There are a variety of image quality analysis tools available for the archiving world, which are based on different test charts and analysis algorithms. ISO has formed a working group in 2012 to harmonize these approaches and create a standard way of analyzing the image quality for archiving...... systems. This has resulted in three documents that have been or are going to be published soon. ISO 19262 defines the terms used in the area of image capture to unify the language. ISO 19263 describes the workflow issues and provides detailed information on how the measurements are done. Last...... but not least ISO 19264 describes the measurements in detail and provides aims and tolerance levels for the different aspects. This paper will present the new ISO 19264 technical specification to analyze image quality based on a single capture of a multi-pattern test chart, and discuss the reasoning behind its...

  17. Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow (United States)

    Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.


    The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

  18. Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow (United States)

    Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.


    The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

  19. Standardization of Image Quality Analysis – ISO 19264

    DEFF Research Database (Denmark)

    Kejser, Ulla Bøgvad; Wüller, Dietmar


    There are a variety of image quality analysis tools available for the archiving world, which are based on different test charts and analysis algorithms. ISO has formed a working group in 2012 to harmonize these approaches and create a standard way of analyzing the image quality for archiving...... systems. This has resulted in three documents that have been or are going to be published soon. ISO 19262 defines the terms used in the area of image capture to unify the language. ISO 19263 describes the workflow issues and provides detailed information on how the measurements are done. Last...... but not least ISO 19264 describes the measurements in detail and provides aims and tolerance levels for the different aspects. This paper will present the new ISO 19264 technical specification to analyze image quality based on a single capture of a multi-pattern test chart, and discuss the reasoning behind its...

  20. Mathematical methods in time series analysis and digital image processing

    CERN Document Server

    Kurths, J; Maass, P; Timmer, J


    The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.

  1. Peripheral blood smear image analysis: A comprehensive review. (United States)

    Mohammed, Emad A; Mohamed, Mostafa M A; Far, Behrouz H; Naugler, Christopher


    Peripheral blood smear image examination is a part of the routine work of every laboratory. The manual examination of these images is tedious, time-consuming and suffers from interobserver variation. This has motivated researchers to develop different algorithms and methods to automate peripheral blood smear image analysis. Image analysis itself consists of a sequence of steps consisting of image segmentation, features extraction and selection and pattern classification. The image segmentation step addresses the problem of extraction of the object or region of interest from the complicated peripheral blood smear image. Support vector machine (SVM) and artificial neural networks (ANNs) are two common approaches to image segmentation. Features extraction and selection aims to derive descriptive characteristics of the extracted object, which are similar within the same object class and different between different objects. This will facilitate the last step of the image analysis process: pattern classification. The goal of pattern classification is to assign a class to the selected features from a group of known classes. There are two types of classifier learning algorithms: supervised and unsupervised. Supervised learning algorithms predict the class of the object under test using training data of known classes. The training data have a predefined label for every class and the learning algorithm can utilize this data to predict the class of a test object. Unsupervised learning algorithms use unlabeled training data and divide them into groups using similarity measurements. Unsupervised learning algorithms predict the group to which a new test object belong to, based on the training data without giving an explicit class to that object. ANN, SVM, decision tree and K-nearest neighbor are possible approaches to classification algorithms. Increased discrimination may be obtained by combining several classifiers together.

  2. Peripheral blood smear image analysis: A comprehensive review

    Directory of Open Access Journals (Sweden)

    Emad A Mohammed


    Full Text Available Peripheral blood smear image examination is a part of the routine work of every laboratory. The manual examination of these images is tedious, time-consuming and suffers from interobserver variation. This has motivated researchers to develop different algorithms and methods to automate peripheral blood smear image analysis. Image analysis itself consists of a sequence of steps consisting of image segmentation, features extraction and selection and pattern classification. The image segmentation step addresses the problem of extraction of the object or region of interest from the complicated peripheral blood smear image. Support vector machine (SVM and artificial neural networks (ANNs are two common approaches to image segmentation. Features extraction and selection aims to derive descriptive characteristics of the extracted object, which are similar within the same object class and different between different objects. This will facilitate the last step of the image analysis process: pattern classification. The goal of pattern classification is to assign a class to the selected features from a group of known classes. There are two types of classifier learning algorithms: supervised and unsupervised. Supervised learning algorithms predict the class of the object under test using training data of known classes. The training data have a predefined label for every class and the learning algorithm can utilize this data to predict the class of a test object. Unsupervised learning algorithms use unlabeled training data and divide them into groups using similarity measurements. Unsupervised learning algorithms predict the group to which a new test object belong to, based on the training data without giving an explicit class to that object. ANN, SVM, decision tree and K-nearest neighbor are possible approaches to classification algorithms. Increased discrimination may be obtained by combining several classifiers together.

  3. Photoacoustic and Ultrasonic Image-Guided Needle Biopsy of the Prostate (United States)


    AWARD NUMBER: W81XWH-14-1-0024 TITLE: Photoacoustic and Ultrasonic Image-Guided Needle Biopsy of the Prostate PRINCIPAL INVESTIGATOR: Richard...light sources to yield multi-spectral photoacoustic (PA) imaging data in excised prostate tissue. Two types of interstitial sources – a directional...ANSI Std. Z39.18 Photoacoustic and Ultrasonic Image-Guided Needle Biopsy of the Prostate 34 Table of Contents Page 1. Introduction

  4. Nonlinear Denoising and Analysis of Neuroimages With Kernel Principal Component Analysis and Pre-Image Estimation

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Abrahamsen, Trine Julie; Madsen, Kristoffer Hougaard


    We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising...... base these illustrations on two fMRI BOLD data sets — one from a simple finger tapping experiment and the other from an experiment on object recognition in the ventral temporal lobe....

  5. IJBlob: An ImageJ Library for Connected Component Analysis and Shape Analysis



    The IJBlob library is a free ImageJ library for connected component analysis. Furthermore, it implements several contour based shape features to describe, filter or classify binary objects in images. Other features are extensible by the IJBlob extension framework. Because connected component labeling is a fundamental operation in many image processing pipelines (e.g. pattern recognition), the library could be useful for many ImageJ projects. The library is written in Java and the recent relea...

  6. Applying Image Matching to Video Analysis (United States)


    Database of Spent Cartridge Cases of Firearms". Forensic Science International . Page(s) 97-106. 2001. 21: Birchfield, S. "Derivation of Kanade-Lucas-Tomasi...Ortega-Garcia, J. "Bayesian Analysis of Fingerprint, Face and Signature Evidences with Automatic Biometric Systems". Forensic Science International . Vol

  7. Evaluation of stereoscopic 3D displays for image analysis tasks (United States)

    Peinsipp-Byma, E.; Rehfeld, N.; Eck, R.


    In many application domains the analysis of aerial or satellite images plays an important role. The use of stereoscopic display technologies can enhance the image analyst's ability to detect or to identify certain objects of interest, which results in a higher performance. Changing image acquisition from analog to digital techniques entailed the change of stereoscopic visualisation techniques. Recently different kinds of digital stereoscopic display techniques with affordable prices have appeared on the market. At Fraunhofer IITB usability tests were carried out to find out (1) with which kind of these commercially available stereoscopic display techniques image analysts achieve the best performance and (2) which of these techniques achieve a high acceptance. First, image analysts were interviewed to define typical image analysis tasks which were expected to be solved with a higher performance using stereoscopic display techniques. Next, observer experiments were carried out whereby image analysts had to solve defined tasks with different visualization techniques. Based on the experimental results (performance parameters and qualitative subjective evaluations of the used display techniques) two of the examined stereoscopic display technologies were found to be very good and appropriate.

  8. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jianping Hua


    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  9. Satellite Image Pansharpening Using a Hybrid Approach for Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Nguyen Thanh Hoan


    Full Text Available Intensity-Hue-Saturation (IHS, Brovey Transform (BT, and Smoothing-Filter-Based-Intensity Modulation (SFIM algorithms were used to pansharpen GeoEye-1 imagery. The pansharpened images were then segmented in Berkeley Image Seg using a wide range of segmentation parameters, and the spatial and spectral accuracy of image segments was measured. We found that pansharpening algorithms that preserve more of the spatial information of the higher resolution panchromatic image band (i.e., IHS and BT led to more spatially-accurate segmentations, while pansharpening algorithms that minimize the distortion of spectral information of the lower resolution multispectral image bands (i.e., SFIM led to more spectrally-accurate image segments. Based on these findings, we developed a new IHS-SFIM combination approach, specifically for object-based image analysis (OBIA, which combined the better spatial information of IHS and the more accurate spectral information of SFIM to produce image segments with very high spatial and spectral accuracy.

  10. Image edge detection based on multi-fractal spectrum analysis

    Institute of Scientific and Technical Information of China (English)

    WANG Shao-yuan; WANG Yao-nan


    In this paper,an image edge detection method based on multi-fractal spectrum analysis is presented.The coarse grain H(o)lder exponent of the image pixels is first computed,then,its multi-fractal spectrum is estimated by the kernel estimation method.Finally,the image edge detection is done by means of different multi-fractal spectrum values.Simulation results show that this method is efficient and has better locality compared with the traditional edge detection methods such as the Sobel method.

  11. Multiphoton autofluorescence spectral analysis for fungus imaging and identification (United States)

    Lin, Sung-Jan; Tan, Hsin-Yuan; Kuo, Chien-Jui; Wu, Ruei-Jr; Wang, Shiou-Han; Chen, Wei-Liang; Jee, Shiou-Hwa; Dong, Chen-Yuan


    We performed multiphoton imaging on fungi of medical significance. Fungal hyphae and spores of Aspergillus flavus, Micosporum gypseum, Micosoprum canis, Trichophyton rubrum, and Trichophyton tonsurans were found to be strongly autofluorescent but generate less prominent second harmonic signal. The cell wall and septum of fungal hyphae can be easily identified by autofluorescence imaging. We found that fungi of various species have distinct autofluorescence characteristics. Our result shows that the combination of multiphoton imaging and spectral analysis can be used to visualize and identify fungal species. This approach may be developed into an effective diagnostic tool for fungal identification.

  12. Water imaging in living plant by nondestructive neutron beam analysis

    Energy Technology Data Exchange (ETDEWEB)

    Nakanishi, M. Tomoko [Graduate School of Agricultural and Life Sciences, Univ. of Tokyo, Tokyo (Japan)


    Analysis of biological activity in intact cells or tissues is essential to understand many life processes. Techniques for these in vivo measurements have not been well developed. We present here a nondestructive method to image water in living plants using a neutron beam. This technique provides the highest resolution for water in tissue yet obtainable. With high specificity to water, this neutron beam technique images water movement in seeds or in roots imbedded in soil, as well as in wood and meristems during development. The resolution of the image attainable now is about 15um. We also describe how this new technique will allow new investigations in the field of plant research. (author)

  13. Image Analysis of Fabric Pilling Based on Light Projection

    Institute of Scientific and Technical Information of China (English)

    陈霞; 黄秀宝


    The objective assessment of fabric pilling based on light projection and image analysis has been exploited recently.The device for capturing the cross-sectional images of the pilled fabrics with light projection is elaborated.The detection of the profile line and integration of the sequential cross-sectional pilled image are discussed.The threshold based on Gaussian model is recommended for pill segmentation.The results show that the installed system is capable of eliminating the interference with pill information from the fabric color and pattern.

  14. Automatic quantitative analysis of cardiac MR perfusion images (United States)

    Breeuwer, Marcel M.; Spreeuwers, Luuk J.; Quist, Marcel J.


    Magnetic Resonance Imaging (MRI) is a powerful technique for imaging cardiovascular diseases. The introduction of cardiovascular MRI into clinical practice is however hampered by the lack of efficient and accurate image analysis methods. This paper focuses on the evaluation of blood perfusion in the myocardium (the heart muscle) from MR images, using contrast-enhanced ECG-triggered MRI. We have developed an automatic quantitative analysis method, which works as follows. First, image registration is used to compensate for translation and rotation of the myocardium over time. Next, the boundaries of the myocardium are detected and for each position within the myocardium a time-intensity profile is constructed. The time interval during which the contrast agent passes for the first time through the left ventricle and the myocardium is detected and various parameters are measured from the time-intensity profiles in this interval. The measured parameters are visualized as color overlays on the original images. Analysis results are stored, so that they can later on be compared for different stress levels of the heart. The method is described in detail in this paper and preliminary validation results are presented.

  15. SIMA: Python software for analysis of dynamic fluorescence imaging data

    Directory of Open Access Journals (Sweden)

    Patrick eKaifosh


    Full Text Available Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs, and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at

  16. Proceedings of the Airborne Imaging Spectrometer Data Analysis Workshop (United States)

    Vane, G. (Editor); Goetz, A. F. H. (Editor)


    The Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on April 8 to 10, 1985. It was attended by 92 people who heard reports on 30 investigations currently under way using AIS data that have been collected over the past two years. Written summaries of 27 of the presentations are in these Proceedings. Many of the results presented at the Workshop are preliminary because most investigators have been working with this fundamentally new type of data for only a relatively short time. Nevertheless, several conclusions can be drawn from the Workshop presentations concerning the value of imaging spectrometry to Earth remote sensing. First, work with AIS has shown that direct identification of minerals through high spectral resolution imaging is a reality for a wide range of materials and geological settings. Second, there are strong indications that high spectral resolution remote sensing will enhance the ability to map vegetation species. There are also good indications that imaging spectrometry will be useful for biochemical studies of vegetation. Finally, there are a number of new data analysis techniques under development which should lead to more efficient and complete information extraction from imaging spectrometer data. The results of the Workshop indicate that as experience is gained with this new class of data, and as new analysis methodologies are developed and applied, the value of imaging spectrometry should increase.

  17. Breast Image Analysis for Risk Assessment, Detection, Diagnosis, and Treatment of Cancer

    NARCIS (Netherlands)

    Giger, M.L.; Karssemeijer, N.; Schnabel, J.A.


    The role of breast image analysis in radiologists' interpretation tasks in cancer risk assessment, detection, diagnosis, and treatment continues to expand. Breast image analysis methods include segmentation, feature extraction techniques, classifier design, biomechanical modeling, image registration

  18. Nanobiodevices for Biomolecule Analysis and Imaging (United States)

    Yasui, Takao; Kaji, Noritada; Baba, Yoshinobu


    Nanobiodevices have been developed to analyze biomolecules and cells for biomedical applications. In this review, we discuss several nanobiodevices used for disease-diagnostic devices, molecular imaging devices, regenerative medicine, and drug-delivery systems and describe the numerous advantages of nanobiodevices, especially in biological, medical, and clinical applications. This review also outlines the fabrication technologies for nanostructures and nanomaterials, including top-down nanofabrication and bottom-up molecular self-assembly approaches. We describe nanopillar arrays and nanowall arrays for the ultrafast separation of DNA or protein molecules and nanoball materials for the fast separation of a wide range of DNA molecules, and we present examples of applications of functionalized carbon nanotubes to obtain information about subcellular localization on the basis of mobility differences between free fluorophores and fluorophore-labeled carbon nanotubes. Finally, we discuss applications of newly synthesized quantum dots to the screening of small interfering RNA, highly sensitive detection of disease-related proteins, and development of cancer therapeutics and diagnostics.

  19. Perfect imaging analysis of the spherical geodesic waveguide (United States)

    González, Juan C.; Benítez, Pablo; Miñano, Juan C.; Grabovičkić, Dejan


    Negative Refractive Lens (NRL) has shown that an optical system can produce images with details below the classic Abbe diffraction limit. This optical system transmits the electromagnetic fields, emitted by an object plane, towards an image plane producing the same field distribution in both planes. In particular, a Dirac delta electric field in the object plane is focused without diffraction limit to the Dirac delta electric field in the image plane. Two devices with positive refraction, the Maxwell Fish Eye lens (MFE) and the Spherical Geodesic Waveguide (SGW) have been claimed to break the diffraction limit using positive refraction with a different meaning. In these cases, it has been considered the power transmission from a point source to a point receptor, which falls drastically when the receptor is displaced from the focus by a distance much smaller than the wavelength. Although these systems can detect displacements up to λ/3000, they cannot be compared to the NRL, since the concept of image is different. The SGW deals only with point source and drain, while in the case of the NRL, there is an object and an image surface. Here, it is presented an analysis of the SGW with defined object and image surfaces (both are conical surfaces), similarly as in the case of the NRL. The results show that a Dirac delta electric field on the object surface produces an image below the diffraction limit on the image surface.

  20. Fractal-based image texture analysis of trabecular bone architecture. (United States)

    Jiang, C; Pitt, R E; Bertram, J E; Aneshansley, D J


    Fractal-based image analysis methods are investigated to extract textural features related to the anisotropic structure of trabecular bone from the X-ray images of cubic bone specimens. Three methods are used to quantify image textural features: power spectrum, Minkowski dimension and mean intercept length. The global fractal dimension is used to describe the overall roughness of the image texture. The anisotropic features formed by the trabeculae are characterised by a fabric ellipse, whose orientation and eccentricity reflect the textural anisotropy of the image. Tests of these methods with synthetic images of known fractal dimension show that the Minkowski dimension provides a more accurate and consistent estimation of global fractal dimension. Tests on bone x-ray (eccentricity range 0.25-0.80) images indicate that the Minkowski dimension is more sensitive to the changes in textural orientation. The results suggest that the Minkowski dimension is a better measure for characterising trabecular bone anisotropy in the x-ray images of thick specimens.