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Sample records for sar image processing

  1. Bistatic sAR data processing algorithms

    CERN Document Server

    Qiu, Xiaolan; Hu, Donghui

    2013-01-01

    Synthetic Aperture Radar (SAR) is critical for remote sensing. It works day and night, in good weather or bad. Bistatic SAR is a new kind of SAR system, where the transmitter and receiver are placed on two separate platforms. Bistatic SAR is one of the most important trends in SAR development, as the technology renders SAR more flexible and safer when used in military environments. Imaging is one of the most difficult and important aspects of bistatic SAR data processing. Although traditional SAR signal processing is fully developed, bistatic SAR has a more complex system structure, so sign

  2. An Integrated Processing Strategy for Mountain Glacier Motion Monitoring Based on SAR Images

    Science.gov (United States)

    Ruan, Z.; Yan, S.; Liu, G.; LV, M.

    2017-12-01

    Mountain glacier dynamic variables are important parameters in studies of environment and climate change in High Mountain Asia. Due to the increasing events of abnormal glacier-related hazards, research of monitoring glacier movements has attracted more interest during these years. Glacier velocities are sensitive and changing fast under complex conditions of high mountain regions, which implies that analysis of glacier dynamic changes requires comprehensive and frequent observations with relatively high accuracy. Synthetic aperture radar (SAR) has been successfully exploited to detect glacier motion in a number of previous studies, usually with pixel-tracking and interferometry methods. However, the traditional algorithms applied to mountain glacier regions are constrained by the complex terrain and diverse glacial motion types. Interferometry techniques are prone to fail in mountain glaciers because of their narrow size and the steep terrain, while pixel-tracking algorithm, which is more robust in high mountain areas, is subject to accuracy loss. In order to derive glacier velocities continually and efficiently, we propose a modified strategy to exploit SAR data information for mountain glaciers. In our approach, we integrate a set of algorithms for compensating non-glacial-motion-related signals which exist in the offset values retrieved by sub-pixel cross-correlation of SAR image pairs. We exploit modified elastic deformation model to remove the offsets associated with orbit and sensor attitude, and for the topographic residual offset we utilize a set of operations including DEM-assisted compensation algorithm and wavelet-based algorithm. At the last step of the flow, an integrated algorithm combining phase and intensity information of SAR images will be used to improve regional motion results failed in cross-correlation related processing. The proposed strategy is applied to the West Kunlun Mountain and Muztagh Ata region in western China using ALOS

  3. Bistatic SAR: Imagery & Image Products.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Wahl, Daniel E.; Jakowatz, Charles V,

    2014-10-01

    While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

  4. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

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

  5. Deep learning for SAR image formation

    Science.gov (United States)

    Mason, Eric; Yonel, Bariscan; Yazici, Birsen

    2017-04-01

    The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

  6. Convolutional Neural Networks for SAR Image Segmentation

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Nobel-Jørgensen, Morten

    2015-01-01

    Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

  7. Imaging in severe acute respiratory syndrome (SARS)

    International Nuclear Information System (INIS)

    Antonio, G.E.; Wong, K.T.; Chu, W.C.W.; Hui, D.S.C.; Cheng, F.W.T.; Yuen, E.H.Y.; Chung, S.S.C.; Fok, T.F.; Sung, J.J.Y.; Ahuja, A.T.

    2003-01-01

    Severe acute respiratory syndrome (SARS) is a highly infectious disease caused by a novel coronavirus, and has become pandemic within a short period of time. Imaging plays an important role in the diagnosis, management and follow-up of patients with SARS. The current status of imaging in SARS is presented in this review

  8. Precision Rectification of Airborne SAR Image

    DEFF Research Database (Denmark)

    Dall, Jørgen; Liao, M.; Zhang, Zhe

    1997-01-01

    A simple and direct procedure for the rectification of a certain class of airborne SAR data is presented. The relief displacements of SAR data are effectively removed by means of a digital elevation model and the image is transformed to the ground coordinate system. SAR data from the Danish EMISAR...

  9. ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. W. Zhao

    2016-06-01

    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.

  10. SAR image effects on coherence and coherence estimation.

    Energy Technology Data Exchange (ETDEWEB)

    Bickel, Douglas Lloyd

    2014-01-01

    Radar coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.

  11. RESEARCH ON AIRBORNE SAR IMAGING BASED ON ESC ALGORITHM

    Directory of Open Access Journals (Sweden)

    X. T. Dong

    2017-09-01

    Full Text Available Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC. In this paper, extend chirp scaling algorithm (ECS is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  12. Research on Airborne SAR Imaging Based on Esc Algorithm

    Science.gov (United States)

    Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.

    2017-09-01

    Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  13. Image based SAR product simulation for analysis

    Science.gov (United States)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  14. Two dimensional estimates from ocean SAR images

    Directory of Open Access Journals (Sweden)

    J. M. Le Caillec

    1996-01-01

    Full Text Available Synthetic Aperture Radar (SAR images of the ocean yield a lot of information on the sea-state surface providing that the mapping process between the surface and the image is clearly defined. However it is well known that SAR images exhibit non-gaussian statistics and that the motion of the scatterers on the surface, while the image is being formed, may yield to nonlinearities. The detection and quantification of these nonlinearities are made possible by using Higher Order Spectra (HOS methods and more specifically, bispectrum estimation. The development of the latter method allowed us to find phase relations between different parts of the image and to recognise their level of coupling, i.e. if and how waves of different wavelengths interacted nonlinearly. This information is quite important as the usual models assume strong nonlinearities when the waves are propagating in the azimuthal direction (i.e. along the satellite track and almost no nonlinearities when propagating in the range direction. In this paper, the mapping of the ocean surface to the SAR image is reinterpreted and a specific model (i.e. a Second Order Volterra Model is introduced. The nonlinearities are thus explained as either produced by a nonlinear system or due to waves propagating into selected directions (azimuth or range and interacting during image formation. It is shown that quadratic nonlinearities occur for waves propagating near the range direction while for those travelling in the azimuthal direction the nonlinearities, when present, are mostly due to wave interactions but are almost completely removed by the filtering effect coming from the surface motion itself (azimuth cut-off. An inherent quadratic interaction filtering (azimuth high pass filter is also present. But some other effects, apparently nonlinear, are not detected with the methods described here, meaning that either the usual relation developed for the Ocean-to-SAR transform is somewhat incomplete

  15. SAR image formation with azimuth interpolation after azimuth transform

    Science.gov (United States)

    Doerry,; Armin W. , Martin; Grant D. , Holzrichter; Michael, W [Albuquerque, NM

    2008-07-08

    Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.

  16. Attribute Learning for SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-04-01

    Full Text Available This paper presents a classification approach based on attribute learning for high spatial resolution Synthetic Aperture Radar (SAR images. To explore the representative and discriminative attributes of SAR images, first, an iterative unsupervised algorithm is designed to cluster in the low-level feature space, where the maximum edge response and the ratio of mean-to-variance are included; a cross-validation step is applied to prevent overfitting. Second, the most discriminative clustering centers are sorted out to construct an attribute dictionary. By resorting to the attribute dictionary, a representation vector describing certain categories in the SAR image can be generated, which in turn is used to perform the classifying task. The experiments conducted on TerraSAR-X images indicate that those learned attributes have strong visual semantics, which are characterized by bright and dark spots, stripes, or their combinations. The classification method based on these learned attributes achieves better results.

  17. Wavelet Filter Banks for Super-Resolution SAR Imaging

    Science.gov (United States)

    Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

    2011-01-01

    This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

  18. Permanent scatterer InSAR processing: Forsmark

    International Nuclear Information System (INIS)

    Dehls, John F.

    2006-04-01

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km 2 . Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of errors

  19. Permanent scatterer InSAR processing: Forsmark

    Energy Technology Data Exchange (ETDEWEB)

    Dehls, John F [Geological Survey of Norway, Trondheim (Norway)

    2006-04-15

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km{sup 2}. Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of

  20. AUTOMATIC INTERPRETATION OF HIGH RESOLUTION SAR IMAGES: FIRST RESULTS OF SAR IMAGE SIMULATION FOR SINGLE BUILDINGS

    Directory of Open Access Journals (Sweden)

    J. Tao

    2012-09-01

    Full Text Available Due to the all-weather data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR plays an important role in remote sensing applications like change detection. However, because of the complex geometric mapping of buildings in urban areas, SAR images are often hard to interpret. SAR simulation techniques ease the visual interpretation of SAR images, while fully automatic interpretation is still a challenge. This paper presents a method for supporting the interpretation of high resolution SAR images with simulated radar images using a LiDAR digital surface model (DSM. Line features are extracted from the simulated and real SAR images and used for matching. A single building model is generated from the DSM and used for building recognition in the SAR image. An application for the concept is presented for the city centre of Munich where the comparison of the simulation to the TerraSAR-X data shows a good similarity. Based on the result of simulation and matching, special features (e.g. like double bounce lines, shadow areas etc. can be automatically indicated in SAR image.

  1. CFAR Edge Detector for Polarimetric SAR Images

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning; Nielsen, Allan Aasbjerg

    2003-01-01

    Finding the edges between different regions in an image is one of the fundamental steps of image analysis, and several edge detectors suitable for the special statistics of synthetic aperture radar (SAR) intensity images have previously been developed. In this paper, a new edge detector for polar...

  2. Fast Superpixel Segmentation Algorithm for PolSAR Images

    Directory of Open Access Journals (Sweden)

    Zhang Yue

    2017-10-01

    Full Text Available As a pre-processing technique, superpixel segmentation algorithms should be of high computational efficiency, accurate boundary adherence and regular shape in homogeneous regions. A fast superpixel segmentation algorithm based on Iterative Edge Refinement (IER has shown to be applicable on optical images. However, it is difficult to obtain the ideal results when IER is applied directly to PolSAR images due to the speckle noise and small or slim regions in PolSAR images. To address these problems, in this study, the unstable pixel set is initialized as all the pixels in the PolSAR image instead of the initial grid edge pixels. In the local relabeling of the unstable pixels, the fast revised Wishart distance is utilized instead of the Euclidean distance in CIELAB color space. Then, a post-processing procedure based on dissimilarity measure is empolyed to remove isolated small superpixels as well as to retain the strong point targets. Finally, extensive experiments based on a simulated image and a real-world PolSAR image from Airborne Synthetic Aperture Radar (AirSAR are conducted, showing that the proposed algorithm, compared with three state-of-the-art methods, performs better in terms of several commonly used evaluation criteria with high computational efficiency, accurate boundary adherence, and homogeneous regularity.

  3. Autofocus algorithm for curvilinear SAR imaging

    Science.gov (United States)

    Bleszynski, E.; Bleszynski, M.; Jaroszewicz, T.

    2012-05-01

    We describe an approach to autofocusing for large apertures on curved SAR trajectories. It is a phase-gradient type method in which phase corrections compensating trajectory perturbations are estimated not directly from the image itself, but rather on the basis of partial" SAR data { functions of the slow and fast times { recon- structed (by an appropriate forward-projection procedure) from windowed scene patches, of sizes comparable to distances between distinct targets or localized features of the scene. The resulting partial data" can be shown to contain the same information on the phase perturbations as that in the original data, provided the frequencies of the perturbations do not exceed a quantity proportional to the patch size. The algorithm uses as input a sequence of conventional scene images based on moderate-size subapertures constituting the full aperture for which the phase corrections are to be determined. The subaperture images are formed with pixel sizes comparable to the range resolution which, for the optimal subaperture size, should be also approximately equal the cross-range resolution. The method does not restrict the size or shape of the synthetic aperture and can be incorporated in the data collection process in persistent sensing scenarios. The algorithm has been tested on the publicly available set of GOTCHA data, intentionally corrupted by random-walk-type trajectory uctuations (a possible model of errors caused by imprecise inertial navigation system readings) of maximum frequencies compatible with the selected patch size. It was able to eciently remove image corruption for apertures of sizes up to 360 degrees.

  4. G0-WISHART Distribution Based Classification from Polarimetric SAR Images

    Science.gov (United States)

    Hu, G. C.; Zhao, Q. H.

    2017-09-01

    Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

  5. Relevant Scatterers Characterization in SAR Images

    Science.gov (United States)

    Chaabouni, Houda; Datcu, Mihai

    2006-11-01

    Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

  6. SAR Image Classification Based on Its Texture Features

    Institute of Scientific and Technical Information of China (English)

    LI Pingxiang; FANG Shenghui

    2003-01-01

    SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

  7. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  8. Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

    Science.gov (United States)

    Tan, Zhen-ya; He, Feng

    2018-04-01

    With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

  9. Space Radar Image of West Texas - SAR scan

    Science.gov (United States)

    1999-01-01

    This radar image of the Midland/Odessa region of West Texas, demonstrates an experimental technique, called ScanSAR, that allows scientists to rapidly image large areas of the Earth's surface. The large image covers an area 245 kilometers by 225 kilometers (152 miles by 139 miles). It was obtained by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying aboard the space shuttle Endeavour on October 5, 1994. The smaller inset image is a standard SIR-C image showing a portion of the same area, 100 kilometers by 57 kilometers (62 miles by 35 miles) and was taken during the first flight of SIR-C on April 14, 1994. The bright spots on the right side of the image are the cities of Odessa (left) and Midland (right), Texas. The Pecos River runs from the top center to the bottom center of the image. Along the left side of the image are, from top to bottom, parts of the Guadalupe, Davis and Santiago Mountains. North is toward the upper right. Unlike conventional radar imaging, in which a radar continuously illuminates a single ground swath as the space shuttle passes over the terrain, a Scansar radar illuminates several adjacent ground swaths almost simultaneously, by 'scanning' the radar beam across a large area in a rapid sequence. The adjacent swaths, typically about 50 km (31 miles) wide, are then merged during ground processing to produce a single large scene. Illumination for this L-band scene is from the top of the image. The beams were scanned from the top of the scene to the bottom, as the shuttle flew from left to right. This scene was acquired in about 30 seconds. A normal SIR-C image is acquired in about 13 seconds. The ScanSAR mode will likely be used on future radar sensors to construct regional and possibly global radar images and topographic maps. The ScanSAR processor is being designed for 1996 implementation at NASA's Alaska SAR Facility, located at the University of Alaska Fairbanks, and will produce digital images from the

  10. The Radiometric Measurement Quantity for SAR Images

    OpenAIRE

    Döring, Björn J.; Schwerdt, Marco

    2013-01-01

    A Synthetic Aperture Radar (SAR) system measures among other quantities the terrain radar reflectivity. After image calibration, the pixel intensities are commonly expressed in terms of radar cross sections (for point targets) or as backscatter coefficients (for distributed targets), which are directly related. This paper argues that pixel intensities are not generally proportional to radar cross section or derived physical quantities. The paper further proposes to replace the inaccurate term...

  11. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  12. Tie Points Extraction for SAR Images Based on Differential Constraints

    Science.gov (United States)

    Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

    2018-04-01

    Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  13. TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    X. Xiong

    2018-04-01

    Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  14. Object Georeferencing in UAV-Based SAR Terrain Images

    Directory of Open Access Journals (Sweden)

    Łabowski Michał

    2016-12-01

    Full Text Available Synthetic aperture radars (SAR allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV. The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

  15. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  16. Imaging manifestations of the cavitation in pulmonary parenchyma of SARS

    International Nuclear Information System (INIS)

    Yuan Chunwang; Zhao Dawei; Wang Wei; Jia Cuiyu; Bai Chunsheng

    2004-01-01

    Objective: To investigate the imaging appearances of cavitation in pulmonary parenchyma and the clinical features of the cases of SARS. Methods: Chest imaging films and clinical data of 180 patients with clinically confirmed SARS were analyzed retrospectively. The imaging manifestations of cavitation and the clinical features of the patients were observed and evaluated. Results: Of 180 patients, cavitations were showed in 5 (2.8%), which were all found through X-ray or CT scanning. Most of them were round or irregular, and had thick wall. The 5 patients all had been in hospital and treated with more dosage antibiotics, antivirus medicines and glucocorticoid for long time, the glucocorticoid was used for 25-65 d, and in the first 10-15 days the dosage was 160-240 mg per day. In hospitalization, one of them had been diagnosed diabetes mellitus, four had increased fasting blood sugar, the counts of white blood cells [(14.1-20.4) x 10 9 /L] increased significantly, the percent of neutrophils might increased also. Meanwhile, there was a continue increase of lactate dehydrogenase (228.00-475.00 U/L), glutamic dehydrogenase (10.08-60.00 U/L) and hydroxybutyrate dehydrogenase (190.00-444.00 U/L) in lab examination. Conclusion: SARS can cause cavitation in pulmonary parenchyma in posterior process of the disease. CT scanning can find the cavitation earlier and accurately, catching the imaging features of them is helpful in differential diagnosis, guiding therapy and estimating prognosis

  17. Polarimetric SAR image classification based on discriminative dictionary learning model

    Science.gov (United States)

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  18. SAR image regularization with fast approximate discrete minimization.

    Science.gov (United States)

    Denis, Loïc; Tupin, Florence; Darbon, Jérôme; Sigelle, Marc

    2009-07-01

    Synthetic aperture radar (SAR) images, like other coherent imaging modalities, suffer from speckle noise. The presence of this noise makes the automatic interpretation of images a challenging task and noise reduction is often a prerequisite for successful use of classical image processing algorithms. Numerous approaches have been proposed to filter speckle noise. Markov random field (MRF) modelization provides a convenient way to express both data fidelity constraints and desirable properties of the filtered image. In this context, total variation minimization has been extensively used to constrain the oscillations in the regularized image while preserving its edges. Speckle noise follows heavy-tailed distributions, and the MRF formulation leads to a minimization problem involving nonconvex log-likelihood terms. Such a minimization can be performed efficiently by computing minimum cuts on weighted graphs. Due to memory constraints, exact minimization, although theoretically possible, is not achievable on large images required by remote sensing applications. The computational burden of the state-of-the-art algorithm for approximate minimization (namely the alpha -expansion) is too heavy specially when considering joint regularization of several images. We show that a satisfying solution can be reached, in few iterations, by performing a graph-cut-based combinatorial exploration of large trial moves. This algorithm is applied to joint regularization of the amplitude and interferometric phase in urban area SAR images.

  19. Synthetic aperture design for increased SAR image rate

    Science.gov (United States)

    Bielek, Timothy P [Albuquerque, NM; Thompson, Douglas G [Albuqerque, NM; Walker, Bruce C [Albuquerque, NM

    2009-03-03

    High resolution SAR images of a target scene at near video rates can be produced by using overlapped, but nevertheless, full-size synthetic apertures. The SAR images, which respectively correspond to the apertures, can be analyzed in sequence to permit detection of movement in the target scene.

  20. Multi-look polarimetric SAR image filtering using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper

    2000-01-01

    Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...

  1. Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

    Science.gov (United States)

    Xu, Xin; Gui, Rong; Pu, Fangling

    2018-01-01

    Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499

  2. Advanced InSAR imaging for dune mapping

    Science.gov (United States)

    Havivi, Shiran; August, Yitzhak; Blumberg, Dan G.; Rotman, Stanley R.

    2015-04-01

    Aeolian morphologies are formed in the presence of sufficient wind energy and available particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970's, remote sensing imagery both optical and radar, are used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of Aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two images or more. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This research aims to demonstrate how interferometric decorrelation, or, coherence change detection, can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the Nitzanim coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of varying levels of stability and vegetation cover and have been monitored meteorologically, geomorphologically and

  3. Guided SAR image despeckling with probabilistic non local weights

    Science.gov (United States)

    Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

    2017-12-01

    SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

  4. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

    Directory of Open Access Journals (Sweden)

    Fan Zhang

    2016-04-01

    Full Text Available With the development of synthetic aperture radar (SAR technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO. However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  5. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

    Science.gov (United States)

    Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

    2016-04-07

    With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  6. The Establishment of the SAR images database System Based on Oracle and ArcSDE

    International Nuclear Information System (INIS)

    Zhou, Jijin; Li, Zhen; Chen, Quan; Tian, Bangsen

    2014-01-01

    Synthetic aperture radar is a kind of microwave imaging system, and has the advantages of multi-band, multi-polarization and multi-angle. At present, there is no SAR images database system based on typical features. For solving problems in interpretation and identification, a new SAR images database system of the typical features is urgent in the current development need. In this article, a SAR images database system based on Oracle and ArcSDE was constructed. The main works involving are as follows: (1) SAR image data was calibrated and corrected geometrically and geometrically. Besides, the fully polarimetric image was processed as the coherency matrix[T] to preserve the polarimetric information. (2) After analyzing multiple space borne SAR images, the metadata table was defined as: IMAGEID; Name of features; Latitude and Longitude; Sensor name; Range and Azimuth resolution etc. (3) Through the comparison between GeoRaster and ArcSDE, result showed ArcSDE is a more appropriate technology to store images in a central database. The System stores and manages multisource SAR image data well, reflects scattering, geometry, polarization, band and angle characteristics, and combines with analysis of the managed objects and service objects of the database as well as focuses on constructing SAR image system in the aspects of data browse and data retrieval. According the analysis of characteristics of SAR images such as scattering, polarization, incident angle and wave band information, different weights can be given to these characteristics. Then an interpreted tool is formed to provide an efficient platform for interpretation

  7. Basic to Advanced InSAR Processing: GMTSAR

    Science.gov (United States)

    Sandwell, D. T.; Xu, X.; Baker, S.; Hogrelius, A.; Mellors, R. J.; Tong, X.; Wei, M.; Wessel, P.

    2017-12-01

    Monitoring crustal deformation using InSAR is becoming a standard technique for the science and application communities. Optimal use of the new data streams from Sentinel-1 and NISAR will require open software tools as well as education on the strengths and limitations of the InSAR methods. Over the past decade we have developed freely available, open-source software for processing InSAR data. The software relies on the Generic Mapping Tools (GMT) for the back-end data analysis and display and is thus called GMTSAR. With startup funding from NSF, we accelerated the development of GMTSAR to include more satellite data sources and provide better integration and distribution with GMT. In addition, with support from UNAVCO we have offered 6 GMTSAR short courses to educate mostly novice InSAR users. Currently, the software is used by hundreds of scientists and engineers around the world to study deformation at more than 4300 different sites. The most challenging aspect of the recent software development was the transition from image alignment using the cross-correlation method to a completely new alignment algorithm that uses only the precise orbital information to geometrically align images to an accuracy of better than 7 cm. This development was needed to process a new data type that is being acquired by the Sentinel-1A/B satellites. This combination of software and open data is transforming radar interferometry from a research tool into a fully operational time series analysis tool. Over the next 5 years we are planning to continue to broaden the user base through: improved software delivery methods; code hardening; better integration with data archives; support for high level products being developed for NISAR; and continued education and outreach.

  8. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng

    2014-03-14

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  9. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng; Jonsson, Sigurjon; Hanssen, Ramon F.

    2014-01-01

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  10. Pixel Classification of SAR ice images using ANFIS-PSO Classifier

    Directory of Open Access Journals (Sweden)

    G. Vasumathi

    2016-12-01

    Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

  11. AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

    Directory of Open Access Journals (Sweden)

    Y. Xiang

    2017-09-01

    Full Text Available Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  12. Automatic Coregistration for Multiview SAR Images in Urban Areas

    Science.gov (United States)

    Xiang, Y.; Kang, W.; Wang, F.; You, H.

    2017-09-01

    Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  13. A Novel Sidelobe Reduction Algorithm Based on Two-Dimensional Sidelobe Correction Using D-SVA for Squint SAR Images

    Directory of Open Access Journals (Sweden)

    Min Liu

    2018-03-01

    Full Text Available Sidelobe reduction is a very primary task for synthetic aperture radar (SAR images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method.

  14. Enhancement of SAR images using fuzzy shrinkage technique

    Indian Academy of Sciences (India)

    This paper presents speckle noise reduction in SAR images using a combination of curvelet and fuzzy logic technique to restore speckle-affected images. This method overcomes the limitation of discontinuity in hard threshold and permanent deviation in soft threshold. First, it decomposes noise image into different ...

  15. Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review

    Directory of Open Access Journals (Sweden)

    Xiaoli Ding

    2009-02-01

    Full Text Available Interferometric Synthetic Aperture Radar (InSAR is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.

  16. Multi-image Matching of Airborne SAR Imagery by SANCC

    Directory of Open Access Journals (Sweden)

    DING Hao

    2015-03-01

    Full Text Available In order to improve accuracy of SAR matching, a multi-image matching method based on sum of adaptive normalized cross-correlation (SANCC is proposed. It utilizes geometrical and radiometric information of multi-baselinesynthetic aperture radar (SARimages effectively. Firstly, imaging parameters, platform parameters and approximate digital surface model (DSM are used to predict matching line. Secondly, similarity and proximity in Gestalt theory are introduced to SANCC, and SANCC measures of potential matching points along the matching line are calculated. Thirdly, multi-image matching results and object coordinates of matching points are obtained by winner-take-all (WTA optimization strategy. The approach has been demonstrated with airborne SAR images acquired by a Chinese airborne SAR system (CASMSAR system. The experimental results indicate that the proposed algorithm is effective for providing dense and accuracy matching points, reducing the number of mismatches caused by repeated textures, and offering a better solution to match in poor textured areas.

  17. Restoration of polarimetric SAR images using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning

    2001-01-01

    approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented......Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering...

  18. Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture

    Science.gov (United States)

    Hilland, Jeffrey E.; Bicknell, Thomas; Miller, Carol L.

    1991-01-01

    The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.

  19. STUDY ON THE CLASSIFICATION OF GAOFEN-3 POLARIMETRIC SAR IMAGES USING DEEP NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    J. Zhang

    2018-04-01

    Full Text Available Polarimetric Synthetic Aperture Radar(POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

  20. Study on the Classification of GAOFEN-3 Polarimetric SAR Images Using Deep Neural Network

    Science.gov (United States)

    Zhang, J.; Zhang, J.; Zhao, Z.

    2018-04-01

    Polarimetric Synthetic Aperture Radar (POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

  1. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross section...

  2. Enhancement of SAR images using fuzzy shrinkage technique in ...

    Indian Academy of Sciences (India)

    Shivakumara Swamy Puranik Math

    2017-08-03

    Aug 3, 2017 ... not use threshold approach only by proper selection of shrinking parameter the speckle in SAR image is ... but cost estimation of hyper-parameters will be high. The ..... To find the effectiveness of the proposed image in a.

  3. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    Directory of Open Access Journals (Sweden)

    Lu Ping-ping

    2014-06-01

    Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

  4. Circular SAR Optimization Imaging Method of Buildings

    Directory of Open Access Journals (Sweden)

    Wang Jian-feng

    2015-12-01

    Full Text Available The Circular Synthetic Aperture Radar (CSAR can obtain the entire scattering properties of targets because of its great ability of 360° observation. In this study, an optimal orientation of the CSAR imaging algorithm of buildings is proposed by applying a combination of coherent and incoherent processing techniques. FEKO software is used to construct the electromagnetic scattering modes and simulate the radar echo. The FEKO imaging results are compared with the isotropic scattering results. On comparison, the optimal azimuth coherent accumulation angle of CSAR imaging of buildings is obtained. Practically, the scattering directions of buildings are unknown; therefore, we divide the 360° echo of CSAR into many overlapped and few angle echoes corresponding to the sub-aperture and then perform an imaging procedure on each sub-aperture. Sub-aperture imaging results are applied to obtain the all-around image using incoherent fusion techniques. The polarimetry decomposition method is used to decompose the all-around image and further retrieve the edge information of buildings successfully. The proposed method is validated with P-band airborne CSAR data from Sichuan, China.

  5. Spacial Variation in SAR Images of Different Resolution for Agricultural Fields

    DEFF Research Database (Denmark)

    Sandholt, Inge; Skriver, Henning

    1999-01-01

    The spatial variation in two types of Synthetic Aperture Radar (SAR) images covering agricultural fields is analysed. C-band polarimetric SAR data from the Danish airborne SAR, EMISAR, have been compared to space based ERS-1 C-band SAR with respect to scale and effect of polarization. The general...

  6. SAR Wave Mode Processing- Improvements Towards Sentinel-1 Mission

    Science.gov (United States)

    Johnsen, Harald; Collard, Fabrice

    2013-03-01

    The Sentinel-1 level-2 (L2) ocean product (OCN) has been designed to deliver geophysical parameters related to the wind, waves and surface velocity to a large panel of end-users. Each L2 OCN product contains up to three geophysical components: the radial velocity (RVL), the ocean surface wind field (OWI) and the ocean swell wave spectra (OSW) components. The Sentinel-1 Level 2 OSW component is the two-dimensional ocean surface wave spectra estimated from a Sentinel-1 Level 1 Single-Look Complex (SLC) SAR image by inversion of the corresponding image cross-spectra. The cross spectra are computed by performing inter-looking in azimuth followed by co- and cross-spectra estimation among the detected individual look images. The image from which a single OSW is computed can be a SLC vignette from the WV mode, or a co-polarized subimage extracted from a SM SLC image. The experiences with ASAR have shown the need to improve the modulation transfer functions (MTF), especially the wind dependency in the RAR MTF. The OSW processing scheme is an upgraded version of the ASAR WM Level 2 processing accounting for these findings. The Sentinel-1 Level 2 OSW processing has been evaluated using ASAR WM and ASAR SM data, and preliminary key results are presented in this paper.

  7. Azimuth Ambiguities Removal in Littoral Zones Based on Multi-Temporal SAR Images

    Directory of Open Access Journals (Sweden)

    Xiangguang Leng

    2017-08-01

    Full Text Available Synthetic aperture radar (SAR is one of the most important techniques for ocean monitoring. Azimuth ambiguities are a real problem in SAR images today, which can cause performance degradation in SAR ocean applications. In particular, littoral zones can be strongly affected by land-based sources, whereas they are usually regions of interest (ROI. Given the presence of complexity and diversity in littoral zones, azimuth ambiguities removal is a tough problem. As SAR sensors can have a repeat cycle, multi-temporal SAR images provide new insight into this problem. A method for azimuth ambiguities removal in littoral zones based on multi-temporal SAR images is proposed in this paper. The proposed processing chain includes co-registration, local correlation, binarization, masking, and restoration steps. It is designed to remove azimuth ambiguities caused by fixed land-based sources. The idea underlying the proposed method is that sea surface is dynamic, whereas azimuth ambiguities caused by land-based sources are constant. Thus, the temporal consistence of azimuth ambiguities is higher than sea clutter. It opens up the possibilities to use multi-temporal SAR data to remove azimuth ambiguities. The design of the method and the experimental procedure are based on images from the Sentinel data hub of Europe Space Agency (ESA. Both Interferometric Wide Swath (IW and Stripmap (SM mode images are taken into account to validate the proposed method. This paper also presents two RGB composition methods for better azimuth ambiguities visualization. Experimental results show that the proposed method can remove azimuth ambiguities in littoral zones effectively.

  8. Information theoretic bounds for compressed sensing in SAR imaging

    International Nuclear Information System (INIS)

    Jingxiong, Zhang; Ke, Yang; Jianzhong, Guo

    2014-01-01

    Compressed sensing (CS) is a new framework for sampling and reconstructing sparse signals from measurements significantly fewer than those prescribed by Nyquist rate in the Shannon sampling theorem. This new strategy, applied in various application areas including synthetic aperture radar (SAR), relies on two principles: sparsity, which is related to the signals of interest, and incoherence, which refers to the sensing modality. An important question in CS-based SAR system design concerns sampling rate necessary and sufficient for exact or approximate recovery of sparse signals. In the literature, bounds of measurements (or sampling rate) in CS have been proposed from the perspective of information theory. However, these information-theoretic bounds need to be reviewed and, if necessary, validated for CS-based SAR imaging, as there are various assumptions made in the derivations of lower and upper bounds on sub-Nyquist sampling rates, which may not hold true in CS-based SAR imaging. In this paper, information-theoretic bounds of sampling rate will be analyzed. For this, the SAR measurement system is modeled as an information channel, with channel capacity and rate-distortion characteristics evaluated to enable the determination of sampling rates required for recovery of sparse scenes. Experiments based on simulated data will be undertaken to test the theoretic bounds against empirical results about sampling rates required to achieve certain detection error probabilities

  9. An Advanced Rotation Invariant Descriptor for SAR Image Registration

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2017-07-01

    Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

  10. The artificial object detection and current velocity measurement using SAR ocean surface images

    Science.gov (United States)

    Alpatov, Boris; Strotov, Valery; Ershov, Maksim; Muraviev, Vadim; Feldman, Alexander; Smirnov, Sergey

    2017-10-01

    Due to the fact that water surface covers wide areas, remote sensing is the most appropriate way of getting information about ocean environment for vessel tracking, security purposes, ecological studies and others. Processing of synthetic aperture radar (SAR) images is extensively used for control and monitoring of the ocean surface. Image data can be acquired from Earth observation satellites, such as TerraSAR-X, ERS, and COSMO-SkyMed. Thus, SAR image processing can be used to solve many problems arising in this field of research. This paper discusses some of them including ship detection, oil pollution control and ocean currents mapping. Due to complexity of the problem several specialized algorithm are necessary to develop. The oil spill detection algorithm consists of the following main steps: image preprocessing, detection of dark areas, parameter extraction and classification. The ship detection algorithm consists of the following main steps: prescreening, land masking, image segmentation combined with parameter measurement, ship orientation estimation and object discrimination. The proposed approach to ocean currents mapping is based on Doppler's law. The results of computer modeling on real SAR images are presented. Based on these results it is concluded that the proposed approaches can be used in maritime applications.

  11. SAR processing in the cloud for oil detection in the Arctic

    Science.gov (United States)

    Garron, J.; Stoner, C.; Meyer, F. J.

    2016-12-01

    A new world of opportunity is being thawed from the ice of the Arctic, driven by decreased persistent Arctic sea-ice cover, increases in shipping, tourism, natural resource development. Tools that can automatically monitor key sea ice characteristics and potential oil spills are essential for safe passage in these changing waters. Synthetic aperture radar (SAR) data can be used to discriminate sea ice types and oil on the ocean surface and also for feature tracking. Additionally, SAR can image the earth through the night and most weather conditions. SAR data is volumetrically large and requires significant computing power to manipulate. Algorithms designed to identify key environmental features, like oil spills, in SAR imagery require secondary processing, and are computationally intensive, which can functionally limit their application in a real-time setting. Cloud processing is designed to manage big data and big data processing jobs by means of small cycles of off-site computations, eliminating up-front hardware costs. Pairing SAR data with cloud processing has allowed us to create and solidify a processing pipeline for SAR data products in the cloud to compare operational algorithms efficiency and effectiveness when run using an Alaska Satellite Facility (ASF) defined Amazon Machine Image (AMI). The products created from this secondary processing, were compared to determine which algorithm was most accurate in Arctic feature identification, and what operational conditions were required to produce the results on the ASF defined AMI. Results will be used to inform a series of recommendations to oil-spill response data managers and SAR users interested in expanding their analytical computing power.

  12. THz-SAR Vibrating Target Imaging via the Bayesian Method

    Directory of Open Access Journals (Sweden)

    Bin Deng

    2017-01-01

    Full Text Available Target vibration bears important information for target recognition, and terahertz, due to significant micro-Doppler effects, has strong advantages for remotely sensing vibrations. In this paper, the imaging characteristics of vibrating targets with THz-SAR are at first analyzed. An improved algorithm based on an excellent Bayesian approach, that is, the expansion-compression variance-component (ExCoV method, has been proposed for reconstructing scattering coefficients of vibrating targets, which provides more robust and efficient initialization and overcomes the deficiencies of sidelobes as well as artifacts arising from the traditional correlation method. A real vibration measurement experiment of idle cars was performed to validate the range model. Simulated SAR data of vibrating targets and a tank model in a real background in 220 GHz show good performance at low SNR. Rapidly evolving high-power terahertz devices will offer viable THz-SAR application at a distance of several kilometers.

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

    Directory of Open Access Journals (Sweden)

    Nina Merkle

    2017-06-01

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

  14. Time domain SAR raw data simulation using CST and image focusing of 3D objects

    Science.gov (United States)

    Saeed, Adnan; Hellwich, Olaf

    2017-10-01

    This paper presents the use of a general purpose electromagnetic simulator, CST, to simulate realistic synthetic aperture radar (SAR) raw data of three-dimensional objects. Raw data is later focused in MATLAB using range-doppler algorithm. Within CST Microwave Studio a replica of TerraSAR-X chirp signal is incident upon a modeled Corner Reflector (CR) whose design and material properties are identical to that of the real one. Defining mesh and other appropriate settings reflected wave is measured at several distant points within a line parallel to the viewing direction. This is analogous to an array antenna and is synthesized to create a long aperture for SAR processing. The time domain solver in CST is based on the solution of differential form of Maxwells equations. Exported data from CST is arranged into a 2-d matrix of axis range and azimuth. Hilbert transform is applied to convert the real signal to complex data with phase information. Range compression, range cell migration correction (RCMC), and azimuth compression are applied in time domain to obtain the final SAR image. This simulation can provide valuable information to clarify which real world objects cause images suitable for high accuracy identification in the SAR images.

  15. Ka-band InSAR Imaging and Analysis Based on IMU Data

    Directory of Open Access Journals (Sweden)

    Shi Jun

    2014-02-01

    Full Text Available Compared with other bands, the millimeter wave Interferometric Synthetic Aperture Radar (InSAR has high accuracy and small size, which is a hot topic in InSAR research. On the other hand, shorter wavelength causes difficulties in 2D imaging and interferometric phase extraction. In this study, the imaging and phase performance of the streaming Back Projection (BP method combined with IMU data are analyzed and discussed on the basis of actual Ka-band InSAR data. It is found that because the wavelength of the Ka-band is short, it is more sensitive to the antenna phase-center history. To ensure the phase-preserving capacity, the IMU data must be used with accurate motion error compensation. Furthermore, during data processing, we verify the flat-earth-removing capacity of the BP algorithm that calculates and compensates the master and slave antenna phase centers individually.

  16. SAR Imaging through the Earth’s Ionosphere

    Science.gov (United States)

    2013-11-06

    Xiaoqing Pi, Anthony Freeman, Bruce Chapman, Paul Rosen, and Zhenhong Li . Imaging ionospheric inhomogeneities using spaceborne synthetic aperture radar. J...resolution SAR phase correction. IEEE Trans. Aerosp. Electron. Syst., 30(3):827–835, 1994. [30] Lianlin Li and Fang Li . Ionosphere tomography based on...Manduchi and G. A. Mian . Accuracy analysis for correlation-based image registartion algorithms. In Proceedings of the 1993 IEEE International

  17. Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory

    Directory of Open Access Journals (Sweden)

    Rui Zhou

    2018-01-01

    Full Text Available Synthetic aperture radar (SAR equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

  18. Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

    Science.gov (United States)

    Zhou, Rui; Sun, Jinping; Hu, Yuxin; Qi, Yaolong

    2018-01-31

    Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

  19. The SARVIEWS Project: Automated SAR Processing in Support of Operational Near Real-time Volcano Monitoring

    Science.gov (United States)

    Meyer, F. J.; Webley, P. W.; Dehn, J.; Arko, S. A.; McAlpin, D. B.; Gong, W.

    2016-12-01

    Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing has become established in operational volcano monitoring. Centers like the Alaska Volcano Observatory rely heavily on remote sensing data from optical and thermal sensors to provide time-critical hazard information. Despite this high use of remote sensing data, the presence of clouds and a dependence on solar illumination often limit their impact on decision making. Synthetic Aperture Radar (SAR) systems are widely considered superior to optical sensors in operational monitoring situations, due to their weather and illumination independence. Still, the contribution of SAR to operational volcano monitoring has been limited in the past due to high data costs, long processing times, and low temporal sampling rates of most SAR systems. In this study, we introduce the automatic SAR processing system SARVIEWS, whose advanced data analysis and data integration techniques allow, for the first time, a meaningful integration of SAR into operational monitoring systems. We will introduce the SARVIEWS database interface that allows for automatic, rapid, and seamless access to the data holdings of the Alaska Satellite Facility. We will also present a set of processing techniques designed to automatically generate a set of SAR-based hazard products (e.g. change detection maps, interferograms, geocoded images). The techniques take advantage of modern signal processing and radiometric normalization schemes, enabling the combination of data from different geometries. Finally, we will show how SAR-based hazard information is integrated in existing multi-sensor decision support tools to enable joint hazard analysis with data from optical and thermal sensors. We will showcase the SAR processing system using a set of recent natural disasters (both earthquakes and volcanic eruptions) to demonstrate its

  20. Extraction of lead and ridge characteristics from SAR images of sea ice

    Science.gov (United States)

    Vesecky, John F.; Smith, Martha P.; Samadani, Ramin

    1990-01-01

    Image-processing techniques for extracting the characteristics of lead and pressure ridge features in SAR images of sea ice are reported. The methods are applied to a SAR image of the Beaufort Sea collected from the Seasat satellite on October 3, 1978. Estimates of lead and ridge statistics are made, e.g., lead and ridge density (number of lead or ridge pixels per unit area of image) and the distribution of lead area and orientation as well as ridge length and orientation. The information derived is useful in both ice science and polar operations for such applications as albedo and heat and momentum transfer estimates, as well as ship routing and offshore engineering.

  1. Feature Matching for SAR and Optical Images Based on Gaussian-Gamma-shaped Edge Strength Map

    Directory of Open Access Journals (Sweden)

    CHEN Min

    2016-03-01

    Full Text Available A matching method for SAR and optical images, robust to pixel noise and nonlinear grayscale differences, is presented. Firstly, a rough correction to eliminate rotation and scale change between images is performed. Secondly, features robust to speckle noise of SAR image are detected by improving the original phase congruency based method. Then, feature descriptors are constructed on the Gaussian-Gamma-shaped edge strength map according to the histogram of oriented gradient pattern. Finally, descriptor similarity and geometrical relationship are combined to constrain the matching processing.The experimental results demonstrate that the proposed method provides significant improvement in correct matches number and image registration accuracy compared with other traditional methods.

  2. MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

    Energy Technology Data Exchange (ETDEWEB)

    Eichel, Paul H.

    2013-08-01

    MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.

  3. Potential of TCPInSAR in Monitoring Linear Infrastructure with a Small Dataset of SAR Images: Application of the Donghai Bridge, China

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2018-03-01

    Full Text Available Reliably monitoring deformation associated with linear infrastructures, such as long-span bridges, is vitally important to assess their structural health. In this paper, we attempt to employ satellite interferometric synthetic aperture radar (InSAR to map the deformation of Donghai Bridge over a half of an annual cycle. The bridge, as the fourth longest cross-sea bridge in the world, located in the north of Hangzhou Bay, East China Sea where the featureless sea surface largely occupied the radar image raises challenges to accurately co-register the coherent points along the bridge. To tackle the issues due to co-registration and the limited number of synthetic aperture radar (SAR images, we adopt the termed temporarily-coherent point (TCP InSAR (TCPInSAR technique to process the radar images. TCPs that are not necessarily coherent during the whole observation period can be identified within every two SAR acquisitions during the co-registration procedure based on the statistics of azimuth and range offsets. In the process, co-registration is performed only using the offsets of these TCPs, leading to improved interferometric phases and the local Delaunay triangulation is used to construct point pairs to reduce the atmospheric artifacts along the bridge. With the TCPInSAR method the deformation rate along the bridge is estimated with no need of phase unwrapping. The achieved result reveals that the Donghai Bridge suffered a line-of-sight (LOS deformation rate up to −2.3 cm/year from January 2009 to July 2009 at the cable-stayed part, which is likely due to the thermal expansion of cables.

  4. Road detection in SAR images using a tensor voting algorithm

    Science.gov (United States)

    Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian

    2007-11-01

    In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

  5. Scalable Track Detection in SAR CCD Images

    Energy Technology Data Exchange (ETDEWEB)

    Chow, James G [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Quach, Tu-Thach [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.

  6. SAR Imaging of Ground Moving Targets with Non-ideal Motion Error Compensation(in English

    Directory of Open Access Journals (Sweden)

    Zhou Hui

    2015-06-01

    Full Text Available Conventional ground moving target imaging algorithms mainly focus on the range cell migration correction and the motion parameter estimation of the moving target. However, in real Synthetic Aperture Radar (SAR data processing, non-ideal motion error compensation is also a critical process, which focuses and has serious impacts on the imaging quality of moving targets. Non-ideal motion error can not be compensated by either the stationary SAR motion error compensation algorithms or the autofocus techniques. In this paper, two sorts of non-ideal motion errors that affect the Doppler centroid of the moving target is analyzed, and a novel non-ideal motion error compensation algorithm is proposed based on the Inertial Navigation System (INS data and the range walk trajectory. Simulated and real data processing results are provided to demonstrate the effectiveness of the proposed algorithm.

  7. InSAR Deformation Time Series Processed On-Demand in the Cloud

    Science.gov (United States)

    Horn, W. B.; Weeden, R.; Dimarchi, H.; Arko, S. A.; Hogenson, K.

    2017-12-01

    During this past year, ASF has developed a cloud-based on-demand processing system known as HyP3 (http://hyp3.asf.alaska.edu/), the Hybrid Pluggable Processing Pipeline, for Synthetic Aperture Radar (SAR) data. The system makes it easy for a user who doesn't have the time or inclination to install and use complex SAR processing software to leverage SAR data in their research or operations. One such processing algorithm is generation of a deformation time series product, which is a series of images representing ground displacements over time, which can be computed using a time series of interferometric SAR (InSAR) products. The set of software tools necessary to generate this useful product are difficult to install, configure, and use. Moreover, for a long time series with many images, the processing of just the interferograms can take days. Principally built by three undergraduate students at the ASF DAAC, the deformation time series processing relies the new Amazon Batch service, which enables processing of jobs with complex interconnected dependencies in a straightforward and efficient manner. In the case of generating a deformation time series product from a stack of single-look complex SAR images, the system uses Batch to serialize the up-front processing, interferogram generation, optional tropospheric correction, and deformation time series generation. The most time consuming portion is the interferogram generation, because even for a fairly small stack of images many interferograms need to be processed. By using AWS Batch, the interferograms are all generated in parallel; the entire process completes in hours rather than days. Additionally, the individual interferograms are saved in Amazon's cloud storage, so that when new data is acquired in the stack, an updated time series product can be generated with minimal addiitonal processing. This presentation will focus on the development techniques and enabling technologies that were used in developing the time

  8. A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation

    Directory of Open Access Journals (Sweden)

    Xuejiao Wen

    2018-05-01

    Full Text Available Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

  9. A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation.

    Science.gov (United States)

    Wen, Xuejiao; Qiu, Xiaolan; Han, Bing; Ding, Chibiao; Lei, Bin; Chen, Qi

    2018-05-07

    Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

  10. Doppler Spectrum-Based NRCS Estimation Method for Low-Scattering Areas in Ocean SAR Images

    Directory of Open Access Journals (Sweden)

    Hui Meng

    2017-02-01

    Full Text Available The image intensities of low-backscattering areas in synthetic aperture radar (SAR images are often seriously contaminated by the system noise floor and azimuthal ambiguity signal from adjacent high-backscattering areas. Hence, the image intensity of low-backscattering areas does not correctly reflect the backscattering intensity, which causes confusion in subsequent image processing or interpretation. In this paper, a method is proposed to estimate the normalized radar cross-section (NRCS of low-backscattering area by utilizing the differences between noise, azimuthal ambiguity, and signal in the Doppler frequency domain of single-look SAR images; the aim is to eliminate the effect of system noise and azimuthal ambiguity. Analysis shows that, for a spaceborne SAR with a noise equivalent sigma zero (NESZ of −25 dB and a single-look pixel of 8 m × 5 m, the NRCS-estimation precision of this method can reach −38 dB at a resolution of 96 m × 100 m. Three examples are given to validate the advantages of this method in estimating the low NRCS and the filtering of the azimuthal ambiguity.

  11. Operational SAR Data Processing in GIS Environments for Rapid Disaster Mapping

    Science.gov (United States)

    Bahr, Thomas

    2014-05-01

    The use of SAR data has become increasingly popular in recent years and in a wide array of industries. Having access to SAR can be highly important and critical especially for public safety. Updating a GIS with contemporary information from SAR data allows to deliver a reliable set of geospatial information to advance civilian operations, e.g. search and rescue missions. SAR imaging offers the great advantage, over its optical counterparts, of not being affected by darkness, meteorological conditions such as clouds, fog, etc., or smoke and dust, frequently associated with disaster zones. In this paper we present the operational processing of SAR data within a GIS environment for rapid disaster mapping. For this technique we integrated the SARscape modules for ENVI with ArcGIS®, eliminating the need to switch between software packages. Thereby the premier algorithms for SAR image analysis can be directly accessed from ArcGIS desktop and server environments. They allow processing and analyzing SAR data in almost real time and with minimum user interaction. This is exemplified by the November 2010 flash flood in the Veneto region, Italy. The Bacchiglione River burst its banks on Nov. 2nd after two days of heavy rainfall throughout the northern Italian region. The community of Bovolenta, 22 km SSE of Padova, was covered by several meters of water. People were requested to stay in their homes; several roads, highways sections and railroads had to be closed. The extent of this flooding is documented by a series of Cosmo-SkyMed acquisitions with a GSD of 2.5 m (StripMap mode). Cosmo-SkyMed is a constellation of four Earth observation satellites, allowing a very frequent coverage, which enables monitoring using a very high temporal resolution. This data is processed in ArcGIS using a single-sensor, multi-mode, multi-temporal approach consisting of 3 steps: (1) The single images are filtered with a Gamma DE-MAP filter. (2) The filtered images are geocoded using a reference

  12. The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm

    Science.gov (United States)

    Tan, Linglong; Li, Changkai; Wang, Yueqin

    2018-04-01

    SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.

  13. Mapping tectonic and anthropogenic processes in central California using satellite and airborne InSAR

    Science.gov (United States)

    Liu, Z.; Lundgren, P.; Liang, C.; Farr, T. G.; Fielding, E. J.

    2017-12-01

    The improved spatiotemporal resolution of surface deformation from recent satellite and airborne InSAR measurements provides a great opportunity to improve our understanding of both tectonic and non-tectonic processes. In central California the primary plate boundary fault system (San Andreas fault) lies adjacent to the San Joaquin Valley (SJV), a vast structural trough that accounts for about one-sixth of the United Sates' irrigated land and one-fifth of its extracted groundwater. The central San Andreas fault (CSAF) displays a range of fault slip behavior with creeping in its central segment that decreases towards its northwest and southeast ends, where it transitions to being fully locked. Despite much progress, many questions regarding fault and anthropogenic processes in the region still remain. In this study, we combine satellite InSAR and NASA airborne UAVSAR data to image fault and anthropogenic deformation. The UAVSAR data cover fault perpendicular swaths imaged from opposing look directions and fault parallel swaths since 2009. The much finer spatial resolution and optimized viewing geometry provide important constraints on near fault deformation and fault slip at very shallow depth. We performed a synoptic InSAR time series analysis using Sentinel-1, ALOS, and UAVSAR interferograms. We estimate azimuth mis-registration between single look complex (SLC) images of Sentinel-1 in a stack sense to achieve accurate azimuth co-registration between SLC images for low coherence and/or long interval interferometric pairs. We show that it is important to correct large-scale ionosphere features in ALOS-2 ScanSAR data for accurate deformation measurements. Joint analysis of UAVSAR and ALOS interferometry measurements show clear variability in deformation along the fault strike, suggesting variable fault creep and locking at depth and along strike. In addition to fault creep, the L-band ALOS, and especially ALOS-2 ScanSAR interferometry, show large-scale ground

  14. Fusion method of SAR and optical images for urban object extraction

    Science.gov (United States)

    Jia, Yonghong; Blum, Rick S.; Li, Fangfang

    2007-11-01

    A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

  15. SIMULATION OF SHIP GENERATED TURBULENT AND VORTICAL WAKE IMAGING BY SAR

    Institute of Scientific and Technical Information of China (English)

    Wang Aiming; Zhu Minhui

    2004-01-01

    Synthetic Aperture Radar (SAR) imaging of ocean surface features is studied. The simulation of the turbulent and vortical features generated by a moving ship and SAR imaging of these wakes is carried out. The turbulent wake damping the ocean surface capillary waves may be partially responsible for the suppression of surface waves near the ship track. The vortex pair generating a change in the lateral flow field behind the ship may be partially responsible for an enhancement of the waves near the edges of the smooth area. These hydrodynamic phenomena as well as the changes of radar backscatter generated by turbulence and vortex are simulated.An SAR imaging model is then used on such ocean surface features to provide SAR images.Comparison of two ships' simulated SAR images shows that the wake features are different for various ship parameters.

  16. Unsupervised SBAS-DInSAR Processing of Space-borne SAR data for Earth Surface Displacement Time Series Generation

    Science.gov (United States)

    Casu, F.; de Luca, C.; Lanari, R.; Manunta, M.; Zinno, I.

    2016-12-01

    During the last 25 years, the Differential Synthetic Aperture Radar Interferometry (DInSAR) has played an important role for understanding the Earth's surface deformation and its dynamics. In particular, the large collections of SAR data acquired by a number of space-borne missions (ERS, ENVISAT, ALOS, RADARSAT, TerraSAR-X, COSMO-SkyMed) have pushed toward the development of advanced DInSAR techniques for monitoring the temporal evolution of the ground displacements with an high spatial density. Moreover, the advent of the Copernicus Sentinel-1 (S1) constellation is providing a further increase in the SAR data flow available to the Earth science community, due to its characteristics of global coverage strategy and free and open access data policy. Therefore, managing and storing such a huge amount of data, processing it in an effcient way and maximizing the available archives exploitation are becoming high priority issues. In this work we present some recent advances in the DInSAR field for dealing with the effective exploitation of the present and future SAR data archives. In particular, an efficient parallel SBAS implementation (namely P-SBAS) that takes benefit from high performance computing is proposed. Then, the P-SBAS migration to the emerging Cloud Computing paradigm is shown, together with extensive tests carried out in the Amazon's Elastic Cloud Compute (EC2) infrastructure. Finally, the integration of the P-SBAS processing chain within the ESA Geohazards Exploitation Platform (GEP), for setting up operational on-demand and systematic web tools, open to every user, aimed at automatically processing stacks of SAR data for the generation of SBAS displacement time series, is also illustrated. A number of experimental results obtained by using the ERS, ENVISAT and S1 data in areas characterized by volcanic, seismic and anthropogenic phenomena will be shown. This work is partially supported by: the DPC-CNR agreement, the EPOS-IP project and the ESA GEP project.

  17. Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

    Science.gov (United States)

    Rezaeian, A.; Homayouni, S.; Safari, A.

    2015-12-01

    Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  18. SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

    Directory of Open Access Journals (Sweden)

    A. Rezaeian

    2015-12-01

    Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  19. On Signal Modeling of Moon-Based Synthetic Aperture Radar (SAR Imaging of Earth

    Directory of Open Access Journals (Sweden)

    Zhen Xu

    2018-03-01

    Full Text Available The Moon-based Synthetic Aperture Radar (Moon-Based SAR, using the Moon as a platform, has a great potential to offer global-scale coverage of the earth’s surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the “stop-and-go” assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of ‘stop-and-go’ assumption are first estimated, and then characteristics of Moon-Based SAR imaging’s azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing.

  20. A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    A. Castillo Atoche

    2013-01-01

    Full Text Available A novel parallel tool for large-scale image enhancement/reconstruction and postprocessing of radar/SAR sensor systems is addressed. The proposed parallel tool performs the following intelligent processing steps: image formation, for the application of different system-level effects of image degradation with a particular remote sensing (RS system and simulation of random noising effects, enhancement/reconstruction by employing nonparametric robust high-resolution techniques, and image postprocessing using the fuzzy anisotropic diffusion technique which incorporates a better edge-preserving noise removal effect and faster diffusion process. This innovative tool allows the processing of high-resolution images provided with different radar/SAR sensor systems as required by RS endusers for environmental monitoring, risk prevention, and resource management. To verify the performance implementation of the proposed parallel framework, the processing steps are developed and specifically tested on graphic processing units (GPU, achieving considerable speedups compared to the serial version of the same techniques implemented in C language.

  1. Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images

    Directory of Open Access Journals (Sweden)

    Maria Daniela Graziano

    2017-10-01

    Full Text Available A novel technique for ship wake detection has been recently proposed and applied on X-band Synthetic Aperture Radar images provided by COSMO/SkyMed and TerraSAR-X. The approach shows that the vast majority of wake features are correctly detected and validated in critical situations. In this paper, the algorithm was applied to 28 wakes imaged by Sentinel-1 mission with different polarizations and incidence angles with the aim of testing the method’s robustness with reference to radar frequency and resolution. The detection process is properly modified. The results show that the features were correctly classified in 78.5% of cases, whereas false confirmations occur mainly on Kelvin cusps. Finally, the results were compared with the algorithm performance on X-band images, showing that no significant difference arises. In fact, the total false confirmations rate was 15.8% on X-band images and 18.5% on C-band images. Moreover, since the main criticality concerns again the false confirmation of Kelvin cusps, the same empirical criterion suggested for the X-band SAR images yielded a negligible 1.5% of false detection rate.

  2. Robust tie points selection for InSAR image coregistration

    Science.gov (United States)

    Skanderi, Takieddine; Chabira, Boulerbah; Afifa, Belkacem; Belhadj Aissa, Aichouche

    2013-10-01

    Image coregistration is an important step in SAR interferometry which is a well known method for DEM generation and surface displacement monitoring. A practical and widely used automatic coregistration algorithm is based on selecting a number of tie points in the master image and looking for the correspondence of each point in the slave image using correlation technique. The characteristics of these points, their number and their distribution have a great impact on the reliability of the estimated transformation. In this work, we present a method for automatic selection of suitable tie points that are well distributed over the common area without decreasing the desired tie points' number. First we select candidate points using Harris operator. Then from these points we select tie points depending on their cornerness measure (the highest first). Once a tie point is selected, its correspondence is searched for in the slave image, if the similarity measure maximum is less than a given threshold or it is at the border of the search window, this point is discarded and we proceed to the next Harris point, else, the cornerness of the remaining candidates Harris points are multiplied by a spatially radially increasing function centered at the selected point to disadvantage the points in a neighborhood of a radius determined from the size of the common area and the desired number of points. This is repeated until the desired number of points is selected. Results of an ERS1/2 tandem pair are presented and discussed.

  3. Accelerated Scientific InSAR Processing, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Neva Ridge Technologies proposes to develop a suite of software tools for the analysis of SAR and InSAR data, focused on having a robust and adopted capability well...

  4. Advanced Interferometric Synthetic Aperture Imaging Radar (InSAR) for Dune Mapping

    Science.gov (United States)

    Havivi, Shiran; Amir, Doron; Schvartzman, Ilan; August, Yitzhak; Mamman, Shimrit; Rotman, Stanely R.; Blumberg, Dan G.

    2016-04-01

    Aeolian morphologies are formed in the presence of sufficient wind energy and available lose particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970s, remote sensing imagery, both optical and radar, have been used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two or more images. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR methods. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This work aims to demonstrate how interferometric decorrelation can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the coherence change detection method was used, in order to identify dune stability or instability and the dune activity level. The Nitzanim-Ashdod coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of

  5. Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2017-02-01

    Full Text Available By acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies with image parameters, such as aspect and incidence angle. To investigate vehicle detectability in SAR images for traffic monitoring applications, images of four common types of vehicles in China were acquired using the fully polarimetric (FP SAR of Radarsat-2 in our experiments. Methods for measuring a vehicle’s aspect angle and backscatter intensity are introduced. The experimental FP SAR images are used to analyze the detectability, which is affected by factors such as vehicle size, vehicle shape, and aspect angle. Moreover, a new metric to improve vehicle detectability in FP SAR images is proposed and compared with the well-known intensity metric. The experimental results show that shape is a crucial factor in affecting the backscatter intensity of vehicles, which also oscillates with varying aspect angle. If the size of a vehicle is smaller than the SAR image resolution, using the intensity metric would result in low detectability. However, it could be improved in an FP SAR image by using the proposed metric. Compared with the intensity metric, the overall detectability is improved from 72% to 90% in our experiments. Therefore, this study indicates that FP SAR images have the ability to detect stationary vehicles on the road and are meaningful for traffic monitoring.

  6. Synthetic aperture integration (SAI) algorithm for SAR imaging

    Science.gov (United States)

    Chambers, David H; Mast, Jeffrey E; Paglieroni, David W; Beer, N. Reginald

    2013-07-09

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  7. Unsupervised DInSAR processing chain for multi-scale displacement analysis

    Science.gov (United States)

    Casu, Francesco; Manunta, Michele

    2016-04-01

    Earth Observation techniques can be very helpful for the estimation of several sources of ground deformation due to their characteristics of large spatial coverage, high resolution and cost effectiveness. In this scenario, Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the most effective methodologies for its capability to generate spatially dense deformation maps at both global and local spatial scale, with centimeter to millimeter accuracy. DInSAR exploits the phase difference (interferogram) between SAR image pairs relevant to acquisitions gathered at different times, but with the same illumination geometry and from sufficiently close flight tracks, whose separation is typically referred to as baseline. Among several, the SBAS algorithm is one of the most used DInSAR approaches and it is aimed at generating displacement time series at a multi-scale level by exploiting a set of small baseline interferograms. SBAS, and generally DInSAR, has taken benefit from the large availability of spaceborne SAR data collected along years by several satellite systems, with particular regard to the European ERS and ENVISAT sensors, which have acquired SAR images worldwide during approximately 20 years. Moreover, since 2014 the new generation of Copernicus Sentinel satellites has started to acquire data with a short revisit time (12 days) and a global coverage policy, thus flooding the scientific EO community with an unprecedent amount of data. To efficiently manage such amount of data, proper processing facilities (as those coming from the emerging Cloud Computing technologies) have to be used, as well as novel algorithms aimed at their efficient exploitation have to be developed. In this work we present a set of results achieved by exploiting a recently proposed implementation of the SBAS algorithm, namely Parallel-SBAS (P-SBAS), which allows us to effectively process, in an unsupervised way and in a limited time frame, a huge number of SAR images

  8. AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Fischer

    2018-04-01

    Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

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

    Science.gov (United States)

    Aiello, Martina; Gianinetto, Marco

    2017-10-01

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

  10. Effect of Antenna Pointing Errors on SAR Imaging Considering the Change of the Point Target Location

    Science.gov (United States)

    Zhang, Xin; Liu, Shijie; Yu, Haifeng; Tong, Xiaohua; Huang, Guoman

    2018-04-01

    Towards spaceborne spotlight SAR, the antenna is regulated by the SAR system with specific regularity, so the shaking of the internal mechanism is inevitable. Moreover, external environment also has an effect on the stability of SAR platform. Both of them will cause the jitter of the SAR platform attitude. The platform attitude instability will introduce antenna pointing error on both the azimuth and range directions, and influence the acquisition of SAR original data and ultimate imaging quality. In this paper, the relations between the antenna pointing errors and the three-axis attitude errors are deduced, then the relations between spaceborne spotlight SAR imaging of the point target and antenna pointing errors are analysed based on the paired echo theory, meanwhile, the change of the azimuth antenna gain is considered as the spotlight SAR platform moves ahead. The simulation experiments manifest the effects on spotlight SAR imaging caused by antenna pointing errors are related to the target location, that is, the pointing errors of the antenna beam will severely influence the area far away from the scene centre of azimuth direction in the illuminated scene.

  11. Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps

    Science.gov (United States)

    Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.

    2018-04-01

    Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

  12. SAR image dataset of military ground targets with multiple poses for ATR

    Science.gov (United States)

    Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc

    2017-10-01

    Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.

  13. A High-precision Motion Compensation Method for SAR Based on Image Intensity Optimization

    Directory of Open Access Journals (Sweden)

    Hu Ke-bin

    2015-02-01

    Full Text Available Owing to the platform instability and precision limitations of motion sensors, motion errors negatively affect the quality of synthetic aperture radar (SAR images. The autofocus Back Projection (BP algorithm based on the optimization of image sharpness compensates for motion errors through phase error estimation. This method can attain relatively good performance, while assuming the same phase error for all pixels, i.e., it ignores the spatial variance of motion errors. To overcome this drawback, a high-precision motion error compensation method is presented in this study. In the proposed method, the Antenna Phase Centers (APC are estimated via optimization using the criterion of maximum image intensity. Then, the estimated APCs are applied for BP imaging. Because the APC estimation equals the range history estimation for each pixel, high-precision phase compensation for every pixel can be achieved. Point-target simulations and processing of experimental data validate the effectiveness of the proposed method.

  14. SAR image classification based on CNN in real and simulation datasets

    Science.gov (United States)

    Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

    2018-04-01

    Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

  15. High Resolution SAR Imaging Employing Geometric Features for Extracting Seismic Damage of Buildings

    Science.gov (United States)

    Cui, L. P.; Wang, X. P.; Dou, A. X.; Ding, X.

    2018-04-01

    Synthetic Aperture Radar (SAR) image is relatively easy to acquire but difficult for interpretation. This paper probes how to identify seismic damage of building using geometric features of SAR. The SAR imaging geometric features of buildings, such as the high intensity layover, bright line induced by double bounce backscattering and dark shadow is analysed, and show obvious differences texture features of homogeneity, similarity and entropy in combinatorial imaging geometric regions between the un-collapsed and collapsed buildings in airborne SAR images acquired in Yushu city damaged by 2010 Ms7.1 Yushu, Qinghai, China earthquake, which implicates a potential capability to discriminate collapsed and un-collapsed buildings from SAR image. Study also shows that the proportion of highlight (layover & bright line) area (HA) is related to the seismic damage degree, thus a SAR image damage index (SARDI), which related to the ratio of HA to the building occupation are of building in a street block (SA), is proposed. While HA is identified through feature extraction with high-pass and low-pass filtering of SAR image in frequency domain. A partial region with 58 natural street blocks in the Yushu City are selected as study area. Then according to the above method, HA is extracted, SARDI is then calculated and further classified into 3 classes. The results show effective through validation check with seismic damage classes interpreted artificially from post-earthquake airborne high resolution optical image, which shows total classification accuracy 89.3 %, Kappa coefficient 0.79 and identical to the practical seismic damage distribution. The results are also compared and discussed with the building damage identified from SAR image available by other authors.

  16. A new implementation of full resolution SBAS-DInSAR processing chain for the effective monitoring of structures and infrastructures

    Science.gov (United States)

    Bonano, Manuela; Buonanno, Sabatino; Ojha, Chandrakanta; Berardino, Paolo; Lanari, Riccardo; Zeni, Giovanni; Manunta, Michele

    2017-04-01

    The advanced DInSAR technique referred to as Small BAseline Subset (SBAS) algorithm has already largely demonstrated its effectiveness to carry out multi-scale and multi-platform surface deformation analyses relevant to both natural and man-made hazards. Thanks to its capability to generate displacement maps and long-term deformation time series at both regional (low resolution analysis) and local (full resolution analysis) spatial scales, it allows to get more insights on the spatial and temporal patterns of localized displacements relevant to single buildings and infrastructures over extended urban areas, with a key role in supporting risk mitigation and preservation activities. The extensive application of the multi-scale SBAS-DInSAR approach in many scientific contexts has gone hand in hand with new SAR satellite mission development, characterized by different frequency bands, spatial resolution, revisit times and ground coverage. This brought to the generation of huge DInSAR data stacks to be efficiently handled, processed and archived, with a strong impact on both the data storage and the computational requirements needed for generating the full resolution SBAS-DInSAR results. Accordingly, innovative and effective solutions for the automatic processing of massive SAR data archives and for the operational management of the derived SBAS-DInSAR products need to be designed and implemented, by exploiting the high efficiency (in terms of portability, scalability and computing performances) of the new ICT methodologies. In this work, we present a novel parallel implementation of the full resolution SBAS-DInSAR processing chain, aimed at investigating localized displacements affecting single buildings and infrastructures relevant to very large urban areas, relying on different granularity level parallelization strategies. The image granularity level is applied in most steps of the SBAS-DInSAR processing chain and exploits the multiprocessor systems with distributed

  17. a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image

    Science.gov (United States)

    Li, L.; Yang, H.; Chen, Q.; Liu, X.

    2018-04-01

    Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

  18. GOTCHA experience report: three-dimensional SAR imaging with complete circular apertures

    Science.gov (United States)

    Ertin, Emre; Austin, Christian D.; Sharma, Samir; Moses, Randolph L.; Potter, Lee C.

    2007-04-01

    We study circular synthetic aperture radar (CSAR) systems collecting radar backscatter measurements over a complete circular aperture of 360 degrees. This study is motivated by the GOTCHA CSAR data collection experiment conducted by the Air Force Research Laboratory (AFRL). Circular SAR provides wide-angle information about the anisotropic reflectivity of the scattering centers in the scene, and also provides three dimensional information about the location of the scattering centers due to a non planar collection geometry. Three dimensional imaging results with single pass circular SAR data reveals that the 3D resolution of the system is poor due to the limited persistence of the reflectors in the scene. We present results on polarimetric processing of CSAR data and illustrate reasoning of three dimensional shape from multi-view layover using prior information about target scattering mechanisms. Next, we discuss processing of multipass (CSAR) data and present volumetric imaging results with IFSAR and three dimensional backprojection techniques on the GOTCHA data set. We observe that the volumetric imaging with GOTCHA data is degraded by aliasing and high sidelobes due to nonlinear flightpaths and sparse and unequal sampling in elevation. We conclude with a model based technique that resolves target features and enhances the volumetric imagery by extrapolating the phase history data using the estimated model.

  19. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN

    OpenAIRE

    Guo, Hao; Wu, Danni; An, Jubai

    2017-01-01

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred f...

  20. Improved GO/PO method and its application to wideband SAR image of conducting objects over rough surface

    Science.gov (United States)

    Jiang, Wang-Qiang; Zhang, Min; Nie, Ding; Jiao, Yong-Chang

    2018-04-01

    To simulate the multiple scattering effect of target in synthetic aperture radar (SAR) image, the hybrid method GO/PO method, which combines the geometrical optics (GO) and physical optics (PO), is employed to simulate the scattering field of target. For ray tracing is time-consuming, the Open Graphics Library (OpenGL) is usually employed to accelerate the process of ray tracing. Furthermore, the GO/PO method is improved for the simulation in low pixel situation. For the improved GO/PO method, the pixels are arranged corresponding to the rectangular wave beams one by one, and the GO/PO result is the sum of the contribution values of all the rectangular wave beams. To get high-resolution SAR image, the wideband echo signal is simulated which includes information of many electromagnetic (EM) waves with different frequencies. Finally, the improved GO/PO method is used to simulate the SAR image of targets above rough surface. And the effects of reflected rays and the size of pixel matrix on the SAR image are also discussed.

  1. PC image processing

    International Nuclear Information System (INIS)

    Hwa, Mok Jin Il; Am, Ha Jeng Ung

    1995-04-01

    This book starts summary of digital image processing and personal computer, and classification of personal computer image processing system, digital image processing, development of personal computer and image processing, image processing system, basic method of image processing such as color image processing and video processing, software and interface, computer graphics, video image and video processing application cases on image processing like satellite image processing, color transformation of image processing in high speed and portrait work system.

  2. A New Method Based on Two-Stage Detection Mechanism for Detecting Ships in High-Resolution SAR Images

    Directory of Open Access Journals (Sweden)

    Xu Yongli

    2017-01-01

    Full Text Available Ship detection in synthetic aperture radar (SAR remote sensing images, being a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Aiming at the requirements of ship detection in high-resolution SAR images, the accuracy, the intelligent level, a better real-time operation and processing efficiency, The characteristics of ocean background and ship target in high-resolution SAR images were analyzed, we put forward a ship detection algorithm in high-resolution SAR images. The algorithm consists of two detection stages: The first step designs a pre-training classifier based on improved spectral residual visual model to obtain the visual salient regions containing ship targets quickly, then achieve the purpose of probably detection of ships. In the second stage, considering the Bayesian theory of binary hypothesis detection, a local maximum posterior probability (MAP classifier is designed for the classification of pixels. After the parameter estimation and judgment criterion, the classification of pixels are carried out in the target areas to achieve the classification of two types of pixels in the salient regions. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X, Radarsat-2, are used to evaluate the performance of detection methods. Comparing with classical CFAR detection algorithms, experimental results show that the algorithm can achieve a better effect of suppressing false alarms, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 25% to 45%.

  3. Wind mapping offshore in coastal Mediterranean area using SAR images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...... of missing data. Here, we focus on evaluating the use of SAR for offshore wind mapping. Preliminary results from the analysis of SAR-based ocean winds in Mediterranean areas show interesting large scale wind flow features consistent with results from previous studies using numerical models and space borne...

  4. Ship Classification with High Resolution TerraSAR-X Imagery Based on Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Zhi Zhao

    2013-01-01

    Full Text Available Ship surveillance using space-borne synthetic aperture radar (SAR, taking advantages of high resolution over wide swaths and all-weather working capability, has attracted worldwide attention. Recent activity in this field has concentrated mainly on the study of ship detection, but the classification is largely still open. In this paper, we propose a novel ship classification scheme based on analytic hierarchy process (AHP in order to achieve better performance. The main idea is to apply AHP on both feature selection and classification decision. On one hand, the AHP based feature selection constructs a selection decision problem based on several feature evaluation measures (e.g., discriminability, stability, and information measure and provides objective criteria to make comprehensive decisions for their combinations quantitatively. On the other hand, we take the selected feature sets as the input of KNN classifiers and fuse the multiple classification results based on AHP, in which the feature sets’ confidence is taken into account when the AHP based classification decision is made. We analyze the proposed classification scheme and demonstrate its results on a ship dataset that comes from TerraSAR-X SAR images.

  5. Research on a dem Coregistration Method Based on the SAR Imaging Geometry

    Science.gov (United States)

    Niu, Y.; Zhao, C.; Zhang, J.; Wang, L.; Li, B.; Fan, L.

    2018-04-01

    Due to the systematic error, especially the horizontal deviation that exists in the multi-source, multi-temporal DEMs (Digital Elevation Models), a method for high precision coregistration is needed. This paper presents a new fast DEM coregistration method based on a given SAR (Synthetic Aperture Radar) imaging geometry to overcome the divergence and time-consuming problem of the conventional DEM coregistration method. First, intensity images are simulated for two DEMs under the given SAR imaging geometry. 2D (Two-dimensional) offsets are estimated in the frequency domain using the intensity cross-correlation operation in the FFT (Fast Fourier Transform) tool, which can greatly accelerate the calculation process. Next, the transformation function between two DEMs is achieved via the robust least-square fitting of 2D polynomial operation. Accordingly, two DEMs can be precisely coregistered. Last, two DEMs, i.e., one high-resolution LiDAR (Light Detection and Ranging) DEM and one low-resolution SRTM (Shutter Radar Topography Mission) DEM, covering the Yangjiao landslide region of Chongqing are taken as an example to test the new method. The results indicate that, in most cases, this new method can achieve not only a result as much as 80 times faster than the minimum elevation difference (Least Z-difference, LZD) DEM registration method, but also more accurate and more reliable results.

  6. RAMP AMM-1 SAR Image Mosaic of Antarctica

    Data.gov (United States)

    National Aeronautics and Space Administration — In 1997, the Canadian RADARSAT-1 satellite was rotated in orbit so that its Synthetic Aperture Radar (SAR) antenna looked south towards Antarctica. This permitted...

  7. 3D Tomographic SAR Imaging in Densely Vegetated Mountainous Rural Areas in China and Sweden

    Science.gov (United States)

    Feng, L.; Muller, J. P., , Prof

    2017-12-01

    3D SAR Tomography (TomoSAR) and 4D SAR Differential Tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to create an important new innovation of SAR Interferometry, to unscramble complex scenes with multiple scatterers mapped into the same SAR cell. In addition to this 3-D shape reconstruction and deformation solution in complex urban/infrastructure areas, and recent cryospheric ice investigations, emerging tomographic remote sensing applications include forest applications, e.g. tree height and biomass estimation, sub-canopy topographic mapping, and even search, rescue and surveillance. However, these scenes are characterized by temporal decorrelation of scatterers, orbital, tropospheric and ionospheric phase distortion and an open issue regarding possible height blurring and accuracy losses for TomoSAR applications particularly in densely vegetated mountainous rural areas. Thus, it is important to develop solutions for temporal decorrelation, orbital, tropospheric and ionospheric phase distortion.We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China and L and P band airborne SAR data (BioSAR 2008 - ESA) in the Krycklan river catchment, Northern Sweden. The new TanDEM-X 12m DEM is used to assist co - registration of all the data stacks over China first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract

  8. A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

    Science.gov (United States)

    Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

    2018-03-01

    Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

  9. APPLICATION OF FUSION WITH SAR AND OPTICAL IMAGES IN LAND USE CLASSIFICATION BASED ON SVM

    Directory of Open Access Journals (Sweden)

    C. Bao

    2012-07-01

    Full Text Available As the increment of remote sensing data with multi-space resolution, multi-spectral resolution and multi-source, data fusion technologies have been widely used in geological fields. Synthetic Aperture Radar (SAR and optical camera are two most common sensors presently. The multi-spectral optical images express spectral features of ground objects, while SAR images express backscatter information. Accuracy of the image classification could be effectively improved fusing the two kinds of images. In this paper, Terra SAR-X images and ALOS multi-spectral images were fused for land use classification. After preprocess such as geometric rectification, radiometric rectification noise suppression and so on, the two kind images were fused, and then SVM model identification method was used for land use classification. Two different fusion methods were used, one is joining SAR image into multi-spectral images as one band, and the other is direct fusing the two kind images. The former one can raise the resolution and reserve the texture information, and the latter can reserve spectral feature information and improve capability of identifying different features. The experiment results showed that accuracy of classification using fused images is better than only using multi-spectral images. Accuracy of classification about roads, habitation and water bodies was significantly improved. Compared to traditional classification method, the method of this paper for fused images with SVM classifier could achieve better results in identifying complicated land use classes, especially for small pieces ground features.

  10. Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

    Science.gov (United States)

    Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng

    2016-01-01

    Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974

  11. A Novel 3D Imaging Method for Airborne Downward-Looking Sparse Array SAR Based on Special Squint Model

    Directory of Open Access Journals (Sweden)

    Xiaozhen Ren

    2014-01-01

    Full Text Available Three-dimensional (3D imaging technology based on antenna array is one of the most important 3D synthetic aperture radar (SAR high resolution imaging modes. In this paper, a novel 3D imaging method is proposed for airborne down-looking sparse array SAR based on the imaging geometry and the characteristic of echo signal. The key point of the proposed algorithm is the introduction of a special squint model in cross track processing to obtain accurate focusing. In this special squint model, point targets with different cross track positions have different squint angles at the same range resolution cell, which is different from the conventional squint SAR. However, after theory analysis and formulation deduction, the imaging procedure can be processed with the uniform reference function, and the phase compensation factors and algorithm realization procedure are demonstrated in detail. As the method requires only Fourier transform and multiplications and thus avoids interpolations, it is computationally efficient. Simulations with point scatterers are used to validate the method.

  12. Skipping the real world: Classification of PolSAR images without explicit feature extraction

    Science.gov (United States)

    Hänsch, Ronny; Hellwich, Olaf

    2018-06-01

    The typical processing chain for pixel-wise classification from PolSAR images starts with an optional preprocessing step (e.g. speckle reduction), continues with extracting features projecting the complex-valued data into the real domain (e.g. by polarimetric decompositions) which are then used as input for a machine-learning based classifier, and ends in an optional postprocessing (e.g. label smoothing). The extracted features are usually hand-crafted as well as preselected and represent (a somewhat arbitrary) projection from the complex to the real domain in order to fit the requirements of standard machine-learning approaches such as Support Vector Machines or Artificial Neural Networks. This paper proposes to adapt the internal node tests of Random Forests to work directly on the complex-valued PolSAR data, which makes any explicit feature extraction obsolete. This approach leads to a classification framework with a significantly decreased computation time and memory footprint since no image features have to be computed and stored beforehand. The experimental results on one fully-polarimetric and one dual-polarimetric dataset show that, despite the simpler approach, accuracy can be maintained (decreased by only less than 2 % for the fully-polarimetric dataset) or even improved (increased by roughly 9 % for the dual-polarimetric dataset).

  13. Data Based Parameter Estimation Method for Circular-scanning SAR Imaging

    Directory of Open Access Journals (Sweden)

    Chen Gong-bo

    2013-06-01

    Full Text Available The circular-scanning Synthetic Aperture Radar (SAR is a novel working mode and its image quality is closely related to the accuracy of the imaging parameters, especially considering the inaccuracy of the real speed of the motion. According to the characteristics of the circular-scanning mode, a new data based method for estimating the velocities of the radar platform and the scanning-angle of the radar antenna is proposed in this paper. By referring to the basic conception of the Doppler navigation technique, the mathematic model and formulations for the parameter estimation are firstly improved. The optimal parameter approximation based on the least square criterion is then realized in solving those equations derived from the data processing. The simulation results verified the validity of the proposed scheme.

  14. The integration of Human Factors (HF) in the SAR process training course text

    International Nuclear Information System (INIS)

    Ryan, T.G.

    1995-03-01

    This text provides the technical basis for a two-day course on human factors (HF), as applied to the Safety Analysis Report (SAR) process. The overall objective of this text and course is to: provide the participant with a working knowledge of human factors-related requirements, suggestions for doing a human safety analysis applying a graded approach, and an ability to demonstrate using the results of the human safety analysis, that human factors elements as defined by DOE (human factors engineering, procedures, training, oversight, staffing, qualifications), can support wherever necessary, nuclear safety commitments in the SAR. More specifically, the objectives of the text and course are: (1) To provide the SAR preparer with general guidelines for doing HE within the context of a graded approach for the SAR; (2) To sensitize DOE facility managers and staff, safety analysts and SAR preparers, independent reviewers, and DOE reviewers and regulators, to DOE Order 5480.23 requirements for HE in the SAR; (3) To provide managers, analysts, reviewers and regulators with a working knowledge of HE concepts and techniques within the context of a graded approach for the SAR, and (4) To provide SAR managers and DOE reviewers and regulators with general guidelines for monitoring and coordinating the work of preparers of HE inputs throughout the SAR process, and for making decisions regarding the safety relevance of HE inputs to the SAR. As a ready reference for implementing the human factors requirements of DOE Order 5480.22 and DOE Standard 3009-94, this course text and accompanying two-day course are intended for all persons who are involved in the SAR

  15. The integration of Human Factors (HF) in the SAR process training course text

    Energy Technology Data Exchange (ETDEWEB)

    Ryan, T.G.

    1995-03-01

    This text provides the technical basis for a two-day course on human factors (HF), as applied to the Safety Analysis Report (SAR) process. The overall objective of this text and course is to: provide the participant with a working knowledge of human factors-related requirements, suggestions for doing a human safety analysis applying a graded approach, and an ability to demonstrate using the results of the human safety analysis, that human factors elements as defined by DOE (human factors engineering, procedures, training, oversight, staffing, qualifications), can support wherever necessary, nuclear safety commitments in the SAR. More specifically, the objectives of the text and course are: (1) To provide the SAR preparer with general guidelines for doing HE within the context of a graded approach for the SAR; (2) To sensitize DOE facility managers and staff, safety analysts and SAR preparers, independent reviewers, and DOE reviewers and regulators, to DOE Order 5480.23 requirements for HE in the SAR; (3) To provide managers, analysts, reviewers and regulators with a working knowledge of HE concepts and techniques within the context of a graded approach for the SAR, and (4) To provide SAR managers and DOE reviewers and regulators with general guidelines for monitoring and coordinating the work of preparers of HE inputs throughout the SAR process, and for making decisions regarding the safety relevance of HE inputs to the SAR. As a ready reference for implementing the human factors requirements of DOE Order 5480.22 and DOE Standard 3009-94, this course text and accompanying two-day course are intended for all persons who are involved in the SAR.

  16. First Image Products from EcoSAR - Osa Peninsula, Costa Rica

    Science.gov (United States)

    Osmanoglu, Batuhan; Lee, SeungKuk; Rincon, Rafael; Fatuyinbo, Lola; Bollian, Tobias; Ranson, Jon

    2016-01-01

    Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

  17. 2002/2003 IfSAR data for Southern California: Radar Reflectance Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata document describes the collection and processing of topographic elevation point data derived from Interferometric Synthetic Aperture Radar (IfSAR)...

  18. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  19. A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs

    Directory of Open Access Journals (Sweden)

    Min-Kyu Kim

    2015-12-01

    Full Text Available This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs. The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB.

  20. Offshore Wind Resource Estimation in Mediterranean Area Using SAR Images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods of m...

  1. Project W-320 SAR and process control thermal analyses

    International Nuclear Information System (INIS)

    Sathyanarayana, K.

    1997-01-01

    This report summarizes the results of thermal hydraulic computer modeling supporting Project W-320 for process control and SAR documentation. Parametric analyses were performed for the maximum steady state waste temperature. The parameters included heat load distribution, tank heat load, fluffing factor and thermal conductivity. Uncertainties in the fluffing factor and heat load distribution had the largest effect on maximum waste temperature. Safety analyses were performed for off normal events including loss of ventilation, loss of evaporation and loss of secondary chiller. The loss of both the primary and secondary ventilation was found to be the most limiting event with saturation temperature in the bottom waste reaching in just over 30 days. An evaluation was performed for the potential lowering of the supernatant level in tank 241-AY-102. The evaluation included a loss of ventilation and steam bump analysis. The reduced supernatant level decreased the time to reach saturation temperature in the waste for the loss of ventilation by about one week. However, the consequence of a steam bump were dramatically reduced

  2. Mechanisms of SAR Imaging of Shallow Water Topography of the Subei Bank

    Directory of Open Access Journals (Sweden)

    Shuangshang Zhang

    2017-11-01

    Full Text Available In this study, the C-band radar backscatter features of the shallow water topography of Subei Bank in the Southern Yellow Sea are statistically investigated using 25 ENVISAT (Environmental Satellite ASAR (advanced synthetic aperture radar and ERS-2 (European Remote-Sensing Satellite-2 SAR images acquired between 2006 and 2010. Different bathymetric features are found on SAR imagery under different sea states. Under low to moderate wind speeds (3.1~6.3 m/s, the wide bright patterns with an average width of 6 km are shown and correspond to sea surface imprints of tidal channels formed by two adjacent sand ridges, while the sand ridges appear as narrower (only 1 km wide, fingerlike, quasi-linear features on SAR imagery in high winds (5.4~13.9 m/s. Two possible SAR imaging mechanisms of coastal bathymetry are proposed in the case where the flow is parallel to the major axes of tidal channels or sand ridges. When the surface Ekman current is opposite to the mean tidal flow, two vortexes will converge at the central line of the tidal channel in the upper layer and form a convergent zone over the sea surface. Thus, the tidal channels are shown as wide and bright stripes on SAR imagery. For the SAR imaging of sand ridges, all the SAR images were acquired at low tidal levels. In this case, the ocean surface waves are possibly broken up under strong winds when propagating from deep water to the shallower water, which leads to an increase of surface roughness over the sand ridges.

  3. IMAGE ENHANCEMENT AND SPECKLE REDUCTION OF FULL POLARIMETRIC SAR DATA BY GAUSSIAN MARKOV RANDOM FIELD

    Directory of Open Access Journals (Sweden)

    M. Mahdian

    2013-09-01

    Full Text Available In recent years, the use of Polarimetric Synthetic Aperture Radar (PolSAR data in different applications dramatically has been increased. In SAR imagery an interference phenomenon with random behavior exists which is called speckle noise. The interpretation of data encounters some troubles due to the presence of speckle which can be considered as a multiplicative noise affecting all coherent imaging systems. Indeed, speckle degrade radiometric resolution of PolSAR images, therefore it is needful to perform speckle filtering on the SAR data type. Markov Random Field (MRF has proven to be a powerful method for drawing out eliciting contextual information from remotely sensed images. In the present paper, a probability density function (PDF, which is fitted well with the PolSAR data based on the goodness-of-fit test, is first obtained for the pixel-wise analysis. Then the contextual smoothing is achieved with the MRF method. This novel speckle reduction method combines an advanced statistical distribution with spatial contextual information for PolSAR data. These two parts of information are combined based on weighted summation of pixel-wise and contextual models. This approach not only preserves edge information in the images, but also improves signal-to-noise ratio of the results. The method maintains the mean value of original signal in the homogenous areas and preserves the edges of features in the heterogeneous regions. Experiments on real medium resolution ALOS data from Tehran, and also high resolution full polarimetric SAR data over the Oberpfaffenhofen test-site in Germany, demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.

  4. The Generalized Gamma-DBN for High-Resolution SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Zhiqiang Zhao

    2018-06-01

    Full Text Available With the increase of resolution, effective characterization of synthetic aperture radar (SAR image becomes one of the most critical problems in many earth observation applications. Inspired by deep learning and probability mixture models, a generalized Gamma deep belief network (g Γ-DBN is proposed for SAR image statistical modeling and land-cover classification in this work. Specifically, a generalized Gamma-Bernoulli restricted Boltzmann machine (gΓB-RBM is proposed to capture high-order statistical characterizes from SAR images after introducing the generalized Gamma distribution. After stacking the g Γ B-RBM and several standard binary RBMs in a hierarchical manner, a gΓ-DBN is constructed to learn high-level representation of different SAR land-covers. Finally, a discriminative neural network is constructed by adding an additional predict layer for different land-covers over the constructed deep structure. Performance of the proposed approach is evaluated via several experiments on some high-resolution SAR image patch sets and two large-scale scenes which are captured by ALOS PALSAR-2 and COSMO-SkyMed satellites respectively.

  5. Geocoding of SAR Image Using the Orbit and Attitude Determination of RADARSAT

    Directory of Open Access Journals (Sweden)

    Jin Wook So

    1998-06-01

    Full Text Available The Synthetic Aperture Radar (SAR image and the Digital Elevation Model (DEM of an target area are put into use to generate three dimensional image map. An method of image map generation is explained. The orbit and attitude determination of satellite makes it possible to model signal acquisition configuration precisely, which is a key to mapping image coordinates to geographic coordinates of concerned area. An application is made to RADARSAT in the purpose of testing its validity. To determine the orbit, zero Doppler range is used. And to determine the attitude, Doppler centroid frequency, which is the frequency observed when target is in the center of antenna's view, is used. Conventional geocoding has been performed on the basis of direct method(mapping image coordinates to geographic coordinates, but in this research the inverse method (mapping from geographic coordinates to image coordinates is taken. This paper shows that precise signal acquisition modeling based on the orbit and attitude determination of satellite as a platform leads to a satellite-centered accurate geocoding process. It also shows how to model relative motion between spaceborne radar and target. And the relative motion is described in ECIC (earth-centered initial coordinates using Doppler equation and signal acquisition geometry.

  6. Expressway deformation mapping using high-resolution TerraSAR-X images

    KAUST Repository

    Shi, Xuguo

    2014-01-27

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  7. Expressway deformation mapping using high-resolution TerraSAR-X images

    KAUST Repository

    Shi, Xuguo; Liao, Mingsheng; Wang, Teng; Zhang, Lu; Shan, Wei; Wang, Chunjiao

    2014-01-01

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  8. Classification of agricultural fields using time series of dual polarimetry TerraSAR-X images

    Directory of Open Access Journals (Sweden)

    S. Mirzaee

    2014-10-01

    Full Text Available Due to its special imaging characteristics, Synthetic Aperture Radar (SAR has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient.

  9. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images

    Directory of Open Access Journals (Sweden)

    Wenguang Wang

    2015-09-01

    Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.

  10. Classification of PolSAR Images Using Multilayer Autoencoders and a Self-Paced Learning Approach

    Directory of Open Access Journals (Sweden)

    Wenshuai Chen

    2018-01-01

    Full Text Available In this paper, a novel polarimetric synthetic aperture radar (PolSAR image classification method based on multilayer autoencoders and self-paced learning (SPL is proposed. The multilayer autoencoders network is used to learn the features, which convert raw data into more abstract expressions. Then, softmax regression is applied to produce the predicted probability distributions over all the classes of each pixel. When we optimize the multilayer autoencoders network, self-paced learning is used to accelerate the learning convergence and achieve a stronger generalization capability. Under this learning paradigm, the network learns the easier samples first and gradually involves more difficult samples in the training process. The proposed method achieves the overall classification accuracies of 94.73%, 94.82% and 78.12% on the Flevoland dataset from AIRSAR, Flevoland dataset from RADARSAT-2 and Yellow River delta dataset, respectively. Such results are comparable with other state-of-the-art methods.

  11. A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains

    Directory of Open Access Journals (Sweden)

    Enrico Stein

    2013-10-01

    Full Text Available A two-component fully automated flood monitoring system is described and evaluated. This is a result of combining two individual flood services that are currently under development at DLR’s (German Aerospace Center Center for Satellite based Crisis Information (ZKI to rapidly support disaster management activities. A first-phase monitoring component of the system systematically detects potential flood events on a continental scale using daily-acquired medium spatial resolution optical data from the Moderate Resolution Imaging Spectroradiometer (MODIS. A threshold set controls the activation of the second-phase crisis component of the system, which derives flood information at higher spatial detail using a Synthetic Aperture Radar (SAR based satellite mission (TerraSAR-X. The proposed activation procedure finds use in the identification of flood situations in different spatial resolutions and in the time-critical and on demand programming of SAR satellite acquisitions at an early stage of an evolving flood situation. The automated processing chains of the MODIS (MFS and the TerraSAR-X Flood Service (TFS include data pre-processing, the computation and adaptation of global auxiliary data, thematic classification, and the subsequent dissemination of flood maps using an interactive web-client. The system is operationally demonstrated and evaluated via the monitoring two recent flood events in Russia 2013 and Albania/Montenegro 2013.

  12. Analysis of the fractal dimension of volcano geomorphology through Synthetic Aperture Radar (SAR) amplitude images acquired in C and X band.

    Science.gov (United States)

    Pepe, S.; Di Martino, G.; Iodice, A.; Manzo, M.; Pepe, A.; Riccio, D.; Ruello, G.; Sansosti, E.; Tizzani, P.; Zinno, I.

    2012-04-01

    In the last two decades several aspects relevant to volcanic activity have been analyzed in terms of fractal parameters that effectively describe natural objects geometry. More specifically, these researches have been aimed at the identification of (1) the power laws that governed the magma fragmentation processes, (2) the energy of explosive eruptions, and (3) the distribution of the associated earthquakes. In this paper, the study of volcano morphology via satellite images is dealt with; in particular, we use the complete forward model developed by some of the authors (Di Martino et al., 2012) that links the stochastic characterization of amplitude Synthetic Aperture Radar (SAR) images to the fractal dimension of the imaged surfaces, modelled via fractional Brownian motion (fBm) processes. Based on the inversion of such a model, a SAR image post-processing has been implemented (Di Martino et al., 2010), that allows retrieving the fractal dimension of the observed surfaces, dictating the distribution of the roughness over different spatial scales. The fractal dimension of volcanic structures has been related to the specific nature of materials and to the effects of active geodynamic processes. Hence, the possibility to estimate the fractal dimension from a single amplitude-only SAR image is of fundamental importance for the characterization of volcano structures and, moreover, can be very helpful for monitoring and crisis management activities in case of eruptions and other similar natural hazards. The implemented SAR image processing performs the extraction of the point-by-point fractal dimension of the scene observed by the sensor, providing - as an output product - the map of the fractal dimension of the area of interest. In this work, such an analysis is performed on Cosmo-SkyMed, ERS-1/2 and ENVISAT images relevant to active stratovolcanoes in different geodynamic contexts, such as Mt. Somma-Vesuvio, Mt. Etna, Vulcano and Stromboli in Southern Italy, Shinmoe

  13. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas

    Directory of Open Access Journals (Sweden)

    Zhenwei Chen

    2016-09-01

    Full Text Available Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  14. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas.

    Science.gov (United States)

    Chen, Zhenwei; Zhang, Lei; Zhang, Guo

    2016-09-17

    Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  15. A comparative study on methods of improving SCR for ship detection in SAR image

    Science.gov (United States)

    Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li

    2017-10-01

    Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.

  16. Azimuth-Variant Signal Processing in High-Altitude Platform Passive SAR with Spaceborne/Airborne Transmitter

    Directory of Open Access Journals (Sweden)

    Huaizong Shao

    2013-03-01

    Full Text Available High-altitude platforms (HAP or near-space vehicle offers several advantages over current low earth orbit (LEO satellite and airplane, because HAP is not constrained by orbital mechanics and fuel consumption. These advantages provide potential for some specific remote sensing applications that require persistent monitoring or fast-revisiting frequency. This paper investigates the azimuth-variant signal processing in HAP-borne bistatic synthetic aperture radar (BiSAR with spaceborne or airborne transmitter for high-resolution remote sensing. The system configuration, azimuth-variant Doppler characteristics and two-dimensional echo spectrum are analyzed. Conceptual system simulation results are also provided. Since the azimuth-variant BiSAR geometry brings a challenge for developing high precision data processing algorithms, we propose an image formation algorithm using equivalent velocity and nonlinear chirp scaling (NCS to address the azimuth-variant signal processing problem. The proposed algorithm is verified by numerical simulation results.

  17. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

    Science.gov (United States)

    Guo, Hao; Wu, Danni; An, Jubai

    2017-08-09

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

  18. Combining TerraSAR-X and Landsat Images for Emergency Response in Urban Environments

    Directory of Open Access Journals (Sweden)

    Shiran Havivi

    2018-05-01

    Full Text Available Rapid damage mapping following a disaster event, especially in an urban environment, is critical to ensure that the emergency response in the affected area is rapid and efficient. This work presents a new method for mapping damage assessment in urban environments. Based on combining SAR and optical data, the method is applicable as support during initial emergency planning and rescue operations. The study focuses on the urban areas affected by the Tohoku earthquake and subsequent tsunami event in Japan that occurred on 11 March 2011. High-resolution TerraSAR-X (TSX images of before and after the event, and a Landsat 5 image before the event were acquired. The affected areas were analyzed with the SAR data using only one interferometric SAR (InSAR coherence map. To increase the damage mapping accuracy, the normalized difference vegetation index (NDVI was applied. The generated map, with a grid size of 50 m, provides a quantitative assessment of the nature and distribution of the damage. The damage mapping shows detailed information about the affected area, with high overall accuracy (89%, and high Kappa coefficient (82% and, as expected, it shows total destruction along the coastline compared to the inland region.

  19. Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory

    Directory of Open Access Journals (Sweden)

    Dongqing Peng

    2016-11-01

    Full Text Available Based on Time-Frequency (TF analysis and a-contrario theory, this paper presents a new approach for extraction of linear arranged power transmission tower series in Polarimetric Synthetic Aperture Radar (PolSAR images. Firstly, the PolSAR multidimensional information is analyzed using a linear TF decomposition approach. The stationarity of each pixel is assessed by testing the maximum likelihood ratio statistics of the coherency matrix. Then, based on the maximum likelihood log-ratio image, a Cell-Averaging Constant False Alarm Rate (CA-CFAR detector with Weibull clutter background and a post-processing operator is used to detect point-like targets in the image. Finally, a searching approach based on a-contrario theory is applied to extract the linear arranged targets from detected point-like targets. The experimental results on three sets of PolSAR data verify the effectiveness of this approach.

  20. Integrated Data Processing Methodology for Airborne Repeat-pass Differential SAR Interferometry

    Science.gov (United States)

    Dou, C.; Guo, H.; Han, C.; Yue, X.; Zhao, Y.

    2014-11-01

    Short temporal baseline and multiple ground deformation information can be derived from the airborne differential synthetic aperture radar Interforemetry (D-InSAR). However, affected by the turbulence of the air, the aircraft would deviate from the designed flight path with high frequent vibrations and changes both in the flight trajectory and attitude. Restricted by the accuracy of the position and orientation system (POS), these high frequent deviations can not be accurately reported, which would pose great challenges in motion compensation and interferometric process. Thus, these challenges constrain its wider applications. The objective of this paper is to investigate the accurate estimation and compensation of the residual motion errors in the airborne SAR imagery and time-varying baseline errors between the diffirent data acquirations, furthermore, to explore the integration data processing theory for the airborne D-InSAR system, and thus help to accomplish the correct derivation of the ground deformation by using the airborne D-InSAR measurements.

  1. Ultra Wide X-Band Microwave Imaging of Concealed Weapons and Explosives Using 3D-SAR Technique

    Directory of Open Access Journals (Sweden)

    P. Millot

    2015-01-01

    Full Text Available In order to detect and image concealed weapons and explosives, an electromagnetic imaging tool with its related signal processing is presented. The aim is to penetrate clothes and to find personal-born weapons and explosives under clothes. The chosen UWB frequency range covers the whole X-band. The frequency range is justified after transmission measurements of numerous clothes that are dry or slightly wet. The apparatus and the 3D near-field SAR processor are described. A strategy for contour identification is presented with results of some simulants of weapon and explosive. A conclusion is drawn on the possible future of this technique.

  2. Grid infrastructure for automatic processing of SAR data for flood applications

    Science.gov (United States)

    Kussul, Natalia; Skakun, Serhiy; Shelestov, Andrii

    2010-05-01

    More and more geosciences applications are being put on to the Grids. Due to the complexity of geosciences applications that is caused by complex workflow, the use of computationally intensive environmental models, the need of management and integration of heterogeneous data sets, Grid offers solutions to tackle these problems. Many geosciences applications, especially those related to the disaster management and mitigations require the geospatial services to be delivered in proper time. For example, information on flooded areas should be provided to corresponding organizations (local authorities, civil protection agencies, UN agencies etc.) no more than in 24 h to be able to effectively allocate resources required to mitigate the disaster. Therefore, providing infrastructure and services that will enable automatic generation of products based on the integration of heterogeneous data represents the tasks of great importance. In this paper we present Grid infrastructure for automatic processing of synthetic-aperture radar (SAR) satellite images to derive flood products. In particular, we use SAR data acquired by ESA's ENVSAT satellite, and neural networks to derive flood extent. The data are provided in operational mode from ESA rolling archive (within ESA Category-1 grant). We developed a portal that is based on OpenLayers frameworks and provides access point to the developed services. Through the portal the user can define geographical region and search for the required data. Upon selection of data sets a workflow is automatically generated and executed on the resources of Grid infrastructure. For workflow execution and management we use Karajan language. The workflow of SAR data processing consists of the following steps: image calibration, image orthorectification, image processing with neural networks, topographic effects removal, geocoding and transformation to lat/long projection, and visualisation. These steps are executed by different software, and can be

  3. A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

    Science.gov (United States)

    Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

    2013-04-01

    There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood

  4. Random Forests as a tool for estimating uncertainty at pixel-level in SAR image classification

    DEFF Research Database (Denmark)

    Loosvelt, Lien; Peters, Jan; Skriver, Henning

    2012-01-01

    , we introduce Random Forests for the probabilistic mapping of vegetation from high-dimensional remote sensing data and present a comprehensive methodology to assess and analyze classification uncertainty based on the local probabilities of class membership. We apply this method to SAR image data...

  5. SAR Image Simulation of Ship Targets Based on Multi-Path Scattering

    Science.gov (United States)

    Guo, Y.; Wang, H.; Ma, H.; Li, K.; Xia, Z.; Hao, Y.; Guo, H.; Shi, H.; Liao, X.; Yue, H.

    2018-04-01

    Synthetic Aperture Radar (SAR) plays an important role in the classification and recognition of ship targets because of its all-weather working ability and fine resolution. In SAR images, besides the sea clutter, the influence of the sea surface on the radar echo is also known as the so-called multipath effect. These multipath effects will generate some extra "pseudo images", which may cause the distortion of the target image and affect the estimation of the characteristic parameters. In this paper,the multipath effect of rough sea surface and its influence on the estimation of ship characteristic parameters are studied. The imaging of the first and the secondary reflection of sea surface is presented . The artifacts not only overlap with the image of the target itself, but may also appear in the sea near the target area. It is difficult to distinguish them, and this artifact has an effect on the length and width of the ship.

  6. SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

    Directory of Open Access Journals (Sweden)

    Wu Yiquan

    2017-08-01

    Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

  7. Urban-area extraction from polarimetric SAR image using combination of target decomposition and orientation angle

    Science.gov (United States)

    Zou, Bin; Lu, Da; Wu, Zhilu; Qiao, Zhijun G.

    2016-05-01

    The results of model-based target decomposition are the main features used to discriminate urban and non-urban area in polarimetric synthetic aperture radar (PolSAR) application. Traditional urban-area extraction methods based on modelbased target decomposition usually misclassified ground-trunk structure as urban-area or misclassified rotated urbanarea as forest. This paper introduces another feature named orientation angle to improve urban-area extraction scheme for the accurate mapping in urban by PolSAR image. The proposed method takes randomness of orientation angle into account for restriction of urban area first and, subsequently, implements rotation angle to improve results that oriented urban areas are recognized as double-bounce objects from volume scattering. ESAR L-band PolSAR data of the Oberpfaffenhofen Test Site Area was used to validate the proposed algorithm.

  8. Target discrimination method for SAR images based on semisupervised co-training

    Science.gov (United States)

    Wang, Yan; Du, Lan; Dai, Hui

    2018-01-01

    Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

  9. Human factors engineering checklists for application in the SAR process

    Energy Technology Data Exchange (ETDEWEB)

    Overlin, T.K.; Romero, H.A.; Ryan, T.G.

    1995-03-01

    This technical report was produced to assist the preparers and reviewers of the human factors portions of the SAR in completing their assigned tasks regarding analysis and/or review of completed analyses. The checklists, which are the main body of the report, and the subsequent tables, were developed to assist analysts in generating the needed analysis data to complete the human engineering analysis for the SAR. The technical report provides a series of 19 human factors engineering (HFE) checklists which support the safety analyses of the US Department of Energy`s (DOE) reactor and nonreactor facilities and activities. The results generated using these checklists and in the preparation of the concluding analyses provide the technical basis for preparing the human factors chapter, and subsequent inputs to other chapters, required by DOE as a part of the safety analysis reports (SARs). This document is divided into four main sections. The first part explains the origin of the checklists, the sources utilized, and other information pertaining to the purpose and scope of the report. The second part, subdivided into 19 sections, is the checklists themselves. The third section is the glossary which defines terms that could either be unfamiliar or have specific meanings within the context of these checklists. The final section is the subject index in which the glossary terms are referenced back to the specific checklist and page the term is encountered.

  10. Human factors engineering checklists for application in the SAR process

    International Nuclear Information System (INIS)

    Overlin, T.K.; Romero, H.A.; Ryan, T.G.

    1995-03-01

    This technical report was produced to assist the preparers and reviewers of the human factors portions of the SAR in completing their assigned tasks regarding analysis and/or review of completed analyses. The checklists, which are the main body of the report, and the subsequent tables, were developed to assist analysts in generating the needed analysis data to complete the human engineering analysis for the SAR. The technical report provides a series of 19 human factors engineering (HFE) checklists which support the safety analyses of the US Department of Energy's (DOE) reactor and nonreactor facilities and activities. The results generated using these checklists and in the preparation of the concluding analyses provide the technical basis for preparing the human factors chapter, and subsequent inputs to other chapters, required by DOE as a part of the safety analysis reports (SARs). This document is divided into four main sections. The first part explains the origin of the checklists, the sources utilized, and other information pertaining to the purpose and scope of the report. The second part, subdivided into 19 sections, is the checklists themselves. The third section is the glossary which defines terms that could either be unfamiliar or have specific meanings within the context of these checklists. The final section is the subject index in which the glossary terms are referenced back to the specific checklist and page the term is encountered

  11. The Nasa-Isro SAR Mission Science Data Products and Processing Workflows

    Science.gov (United States)

    Rosen, P. A.; Agram, P. S.; Lavalle, M.; Cohen, J.; Buckley, S.; Kumar, R.; Misra-Ray, A.; Ramanujam, V.; Agarwal, K. M.

    2017-12-01

    The NASA-ISRO SAR (NISAR) Mission is currently in the development phase and in the process of specifying its suite of data products and algorithmic workflows, responding to inputs from the NISAR Science and Applications Team. NISAR will provide raw data (Level 0), full-resolution complex imagery (Level 1), and interferometric and polarimetric image products (Level 2) for the entire data set, in both natural radar and geocoded coordinates. NASA and ISRO are coordinating the formats, meta-data layers, and algorithms for these products, for both the NASA-provided L-band radar and the ISRO-provided S-band radar. Higher level products will be also be generated for the purpose of calibration and validation, over large areas of Earth, including tectonic plate boundaries, ice sheets and sea-ice, and areas of ecosystem disturbance and change. This level of comprehensive product generation has been unprecedented for SAR missions in the past, and leads to storage processing challenges for the production system and the archive center. Further, recognizing the potential to support applications that require low latency product generation and delivery, the NISAR team is optimizing the entire end-to-end ground data system for such response, including exploring the advantages of cloud-based processing, algorithmic acceleration using GPUs, and on-demand processing schemes that minimize computational and transport costs, but allow rapid delivery to science and applications users. This paper will review the current products, workflows, and discuss the scientific and operational trade-space of mission capabilities.

  12. Discernibility of Burial Mounds in High-Resolution X-Band SAR Images for Archaeological Prospections in the Altai Mountains

    Directory of Open Access Journals (Sweden)

    Timo Balz

    2016-09-01

    Full Text Available The Altai Mountains are a heritage-rich archaeological landscape with monuments in almost every valley. Modern nation state borders dissect the region and limit archaeological landscape analysis to intra-national areas of interest. Remote sensing can help to overcome these limitations. Due to its high precision, Synthetic Aperture Radar (SAR data can be a very useful tool for supporting archaeological prospections, but compared to optical imagery, the detectability of sites of archaeological interest is limited. We analyzed the limitations of SAR using TerraSAR-X images in different modes. Based on ground truth, the discernibility of burial mounds was analyzed in different SAR acquisition modes. We show that very-high-resolution TerraSAR-X staring spotlight images are very well suited for the task, with >75% of the larger mounds being discernible, while in images with a lower spatial resolution only a few large sites can be detected, at rates below 50%.

  13. Fast iterative censoring CFAR algorithm for ship detection from SAR images

    Science.gov (United States)

    Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

    2017-11-01

    Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

  14. Change detection in a time series of polarimetric SAR images

    DEFF Research Database (Denmark)

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    A test statistic for the equality of two or several variance-covariance matrices following the real (as opposed to the complex) Wishart distribution with an associated probability of finding a smaller value of the test statistic is described in the literature [1]. In 2003 we introduced a test...... statistic for the equality of two variance-covariance matrices following the complex Wishart distribution with an associated probability measure [2]. In that paper we also demonstrated the use of the test statistic to change detection over time in both fully polarimetric and azimuthal symmetric SAR data...... positives (postulating a change when there actually is none) and/or false negatives (missing an actual change). Therefore we need to test for equality for all time points simultaneously. In this paper we demonstrate a new test statistic for the equality of several variance-covariance matrices from the real...

  15. Neural network-based feature point descriptors for registration of optical and SAR images

    Science.gov (United States)

    Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

    2018-04-01

    Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

  16. Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

    Directory of Open Access Journals (Sweden)

    Osmar Abílio de Carvalho Júnior

    2014-04-01

    Full Text Available Speckle noise (salt and pepper is inherent to synthetic aperture radar (SAR, which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA, a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS Phased-Array Synthetic-Aperture Radar (PALSAR sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari, containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF or noise-adjusted principal components (NAPCs. Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

  17. On the use of Cloud Computing and Machine Learning for Large-Scale SAR Science Data Processing and Quality Assessment Analysi

    Science.gov (United States)

    Hua, H.

    2016-12-01

    Geodetic imaging is revolutionizing geophysics, but the scope of discovery has been limited by labor-intensive technological implementation of the analyses. The Advanced Rapid Imaging and Analysis (ARIA) project has proven capability to automate SAR data processing and analysis. Existing and upcoming SAR missions such as Sentinel-1A/B and NISAR are also expected to generate massive amounts of SAR data. This has brought to the forefront the need for analytical tools for SAR quality assessment (QA) on the large volumes of SAR data-a critical step before higher-level time series and velocity products can be reliably generated. Initially leveraging an advanced hybrid-cloud computing science data system for performing large-scale processing, machine learning approaches were augmented for automated analysis of various quality metrics. Machine learning-based user-training of features, cross-validation, prediction models were integrated into our cloud-based science data processing flow to enable large-scale and high-throughput QA analytics for enabling improvements to the production quality of geodetic data products.

  18. Development of Signal Processing Algorithms for High Resolution Airborne Millimeter Wave FMCW SAR

    NARCIS (Netherlands)

    Meta, A.; Hoogeboom, P.

    2005-01-01

    For airborne earth observation applications, there is a special interest in lightweight, cost effective, imaging sensors of high resolution. The combination of Frequency Modulated Continuous Wave (FMCW) technology and Synthetic Aperture Radar (SAR) techniques can lead to such a sensor. In this

  19. A neural network detection model of spilled oil based on the texture analysis of SAR image

    Science.gov (United States)

    An, Jubai; Zhu, Lisong

    2006-01-01

    A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

  20. Change detection in polarimetric SAR images using complex Wishart distributed matrices

    DEFF Research Database (Denmark)

    Conradsen, Knut; Nielsen, Allan Aasbjerg; Skriver, Henning

    In surveillance it is important to be able to detect natural or man-made changes e.g. based on sequences of satellite or air borne images of the same area taken at different times. The mapping capability of synthetic aperture radar (SAR) is independent of e.g. cloud cover, and thus this technology...... scattering matrix, and after suitable preprocessing the outcome at each picture element (pixel) may be represented as a 3 by 3 Hermitian matrix following a complex Wishart distribution. One approach to solving the change detection problem based on SAR images is therefore to apply suitable statistical tests...... in the complex Wishart distribution. We propose a set-up for a systematic solution to the (practical) problems using the likelihood ratio test statistics. We show some examples based on a time series of images with 1024 by 1024 pixels....

  1. Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

    Science.gov (United States)

    Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

    2017-12-01

    This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

  2. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Science.gov (United States)

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  3. OPERATIONAL SAR DATA PROCESSING IN GIS ENVIRONMENTS FOR RAPID DISASTER MAPPING

    Directory of Open Access Journals (Sweden)

    A. Meroni

    2013-05-01

    Full Text Available Having access to SAR data can be highly important and critical especially for disaster mapping. Updating a GIS with contemporary information from SAR data allows to deliver a reliable set of geospatial information to advance civilian operations, e.g. search and rescue missions. Therefore, we present in this paper the operational processing of SAR data within a GIS environment for rapid disaster mapping. This is exemplified by the November 2010 flash flood in the Veneto region, Italy. A series of COSMO-SkyMed acquisitions was processed in ArcGIS® using a single-sensor, multi-mode, multi-temporal approach. The relevant processing steps were combined using the ArcGIS ModelBuilder to create a new model for rapid disaster mapping in ArcGIS, which can be accessed both via a desktop and a server environment.

  4. Using SAR images to delineate ocean oil slicks with a texture-classifying neural network algorithm (TCNNA)

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pineda, O.; MacDonald, I.R. [Florida State Univ., Tallahassee, FL (United States). Dept. of Oceanography; Zimmer, B. [Texas A and M Univ., Corpus Christi, TX (United States). Dept. of Mathematics and Statistics; Howard, M. [Texas A and M Univ., College Station, TX (United States). Dept. of Oceanography; Pichel, W. [National Oceanic and Atmospheric Administration, Camp Springs, MD (United States). Center for Satellite Applications and Research, National Environmental Satellite, Data and Information Service; Li, X. [National Oceanic and Atmospheric Administration, Camp Springs, MD (United States). Systems Group, National Environmental Satellite, Data and Information

    2009-10-15

    Synthetic aperture radar (SAR) is used to detect surfactant layers produced by floating oil on the ocean surface. This study presented details of a texture-classifying neural network algorithm (TCNNA) designed to process SAR data from a wide selection of beam modes. Patterns from SAR imagery were extracted in a semi-supervised procedure using a combination of edge-detection filters; texture descriptors; collection information; and environmental data. Various natural oil seeps in the Gulf of Mexico were used as case studies. An analysis of the case studies demonstrated that the TCNNA was able to extract targets and rapidly interpret images collected under a range of environmental conditions. Results presented by the TCNNA were used to evaluate the effects of different environmental conditions on the expressions of oil slicks detected by the data. Optimal incidence angle ranges and wind speed ranges for surfactant film detection were also presented. Results obtained by the TCNNA can be stored and manipulated in geographic information system (GIS) data layers. 26 refs., 1 tab., 7 figs.

  5. RESEARCH ON COORDINATE TRANSFORMATION METHOD OF GB-SAR IMAGE SUPPORTED BY 3D LASER SCANNING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    P. Wang

    2018-04-01

    Full Text Available In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D plane coordinate system with the common three-dimensional (3D terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  6. Research on Coordinate Transformation Method of Gb-Sar Image Supported by 3d Laser Scanning Technology

    Science.gov (United States)

    Wang, P.; Xing, C.

    2018-04-01

    In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D) plane coordinate system with the common three-dimensional (3D) terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  7. Modulation of Tidal Channel Signatures on SAR Images Over Gyeonggi Bay in Relation to Environmental Factors

    Directory of Open Access Journals (Sweden)

    Tae-Sung Kim

    2018-04-01

    Full Text Available In this study, variations of radar backscatter features of the tidal channel in Gyeonggi Bay in the Eastern Yellow Sea were investigated using spaceborne synthetic aperture radar (SAR images. Consistent quasi-linear bright features appeared on the SAR images. Examining the detailed local bathymetry chart, we found that the features were co-located with the major axis of the tidal channel in the region. It was also shown that modulation of the radar backscatter features changed according to the environmental conditions at the time of imaging. For the statistical analysis, the bathymetric features over the tidal channel were extracted by an objective method. In terms of shape, the extracted features had higher variability in width than in length. The analysis of the variation in intensity with the coinciding bathymetric distribution confirmed that the quasi-linear bright features on the SAR images are fundamentally imprinted due to the surface current convergence and divergence caused by the bathymetry-induced tidal current variation. Furthermore, the contribution of environmental factors to the intensity modulation was quantitatively analyzed. A comparison of the variation in normalized radar cross section (NRCS with tidal current showed a positive correlation only with the perpendicular component of tidal current (r= 0.47. This implies that the modulation in intensity of the tidal channel signatures is mainly affected by the interaction with cross-current flow. On the other hand, the modulation of the NRCS over the tidal channel tended to be degraded as wind speed increased (r= −0.65. Considering the environmental circumstances in the study area, it can be inferred that the imaging capability of SAR for the detection of tidal channel signatures mainly relies on wind speed.

  8. Integrated Shoreline Extraction Approach with Use of Rasat MS and SENTINEL-1A SAR Images

    Science.gov (United States)

    Demir, N.; Oy, S.; Erdem, F.; Şeker, D. Z.; Bayram, B.

    2017-09-01

    Shorelines are complex ecosystems and highly important socio-economic environments. They may change rapidly due to both natural and human-induced effects. Determination of movements along the shoreline and monitoring of the changes are essential for coastline management, modeling of sediment transportation and decision support systems. Remote sensing provides an opportunity to obtain rapid, up-to-date and reliable information for monitoring of shoreline. In this study, approximately 120 km of Antalya-Kemer shoreline which is under the threat of erosion, deposition, increasing of inhabitants and urbanization and touristic hotels, has been selected as the study area. In the study, RASAT pansharpened and SENTINEL-1A SAR images have been used to implement proposed shoreline extraction methods. The main motivation of this study is to combine the land/water body segmentation results of both RASAT MS and SENTINEL-1A SAR images to improve the quality of the results. The initial land/water body segmentation has been obtained using RASAT image by means of Random Forest classification method. This result has been used as training data set to define fuzzy parameters for shoreline extraction from SENTINEL-1A SAR image. Obtained results have been compared with the manually digitized shoreline. The accuracy assessment has been performed by calculating perpendicular distances between reference data and extracted shoreline by proposed method. As a result, the mean difference has been calculated around 1 pixel.

  9. Combined DEM Extration Method from StereoSAR and InSAR

    Science.gov (United States)

    Zhao, Z.; Zhang, J. X.; Duan, M. Y.; Huang, G. M.; Yang, S. C.

    2015-06-01

    A pair of SAR images acquired from different positions can be used to generate digital elevation model (DEM). Two techniques exploiting this characteristic have been introduced: stereo SAR and interferometric SAR. They permit to recover the third dimension (topography) and, at the same time, to identify the absolute position (geolocation) of pixels included in the imaged area, thus allowing the generation of DEMs. In this paper, StereoSAR and InSAR combined adjustment model are constructed, and unify DEM extraction from InSAR and StereoSAR into the same coordinate system, and then improve three dimensional positioning accuracy of the target. We assume that there are four images 1, 2, 3 and 4. One pair of SAR images 1,2 meet the required conditions for InSAR technology, while the other pair of SAR images 3,4 can form stereo image pairs. The phase model is based on InSAR rigorous imaging geometric model. The master image 1 and the slave image 2 will be used in InSAR processing, but the slave image 2 is only used in the course of establishment, and the pixels of the slave image 2 are relevant to the corresponding pixels of the master image 1 through image coregistration coefficient, and it calculates the corresponding phase. It doesn't require the slave image in the construction of the phase model. In Range-Doppler (RD) model, the range equation and Doppler equation are a function of target geolocation, while in the phase equation, the phase is also a function of target geolocation. We exploit combined adjustment model to deviation of target geolocation, thus the problem of target solution is changed to solve three unkonwns through seven equations. The model was tested for DEM extraction under spaceborne InSAR and StereoSAR data and compared with InSAR and StereoSAR methods respectively. The results showed that the model delivered a better performance on experimental imagery and can be used for DEM extraction applications.

  10. Two-dimensional Fast ESPRIT Algorithm for Linear Array SAR Imaging

    Directory of Open Access Journals (Sweden)

    Zhao Yi-chao

    2015-10-01

    Full Text Available The linear array Synthetic Aperture Radar (SAR system is a popular research tool, because it can realize three-dimensional imaging. However, owning to limitations of the aircraft platform and actual conditions, resolution improvement is difficult in cross-track and along-track directions. In this study, a twodimensional fast Estimation of Signal Parameters by Rotational Invariance Technique (ESPRIT algorithm for linear array SAR imaging is proposed to overcome these limitations. This approach combines the Gerschgorin disks method and the ESPRIT algorithm to estimate the positions of scatterers in cross and along-rack directions. Moreover, the reflectivity of scatterers is obtained by a modified pairing method based on “region growing”, replacing the least-squares method. The simulation results demonstrate the applicability of the algorithm with high resolution, quick calculation, and good real-time response.

  11. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case.

    Science.gov (United States)

    Ao, Dongyang; Li, Yuanhao; Hu, Cheng; Tian, Weiming

    2017-12-22

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  12. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Sun Xun

    2016-12-01

    Full Text Available In this paper, we propose a supervised classification algorithm for Polarimetric Synthetic Aperture Radar (PolSAR images using multiple-feature fusion and ensemble learning. First, we extract different polarimetric features, including extended polarimetric feature space, Hoekman, Huynen, H/alpha/A, and fourcomponent scattering features of PolSAR images. Next, we randomly select two types of features each time from all feature sets to guarantee the reliability and diversity of later ensembles and use a support vector machine as the basic classifier for predicting classification results. Finally, we concatenate all prediction probabilities of basic classifiers as the final feature representation and employ the random forest method to obtain final classification results. Experimental results at the pixel and region levels show the effectiveness of the proposed algorithm.

  13. Discrimination of Different Water Layers with TerraSAR X Images in "La Albufera de Valencia"

    Science.gov (United States)

    García Fernández, M. A.; Miguelsanz Muñoz, P.

    2009-04-01

    To analyze the capabilities of TerraSAR X Strip Map images in order to discriminate different water layers in the "Parque de la Albufera de Valencia", Spain, a test project was carried out. This place is a rice crop area under European and National Agro environmental regulation which obliges to preserve the habitat and to keep the rice plots flooded out of crop season, from October to January

  14. The Advanced Rapid Imaging and Analysis (ARIA) Project: Providing Standard and On-Demand SAR products for Hazard Science and Hazard Response

    Science.gov (United States)

    Owen, S. E.; Hua, H.; Rosen, P. A.; Agram, P. S.; Webb, F.; Simons, M.; Yun, S. H.; Sacco, G. F.; Liu, Z.; Fielding, E. J.; Lundgren, P.; Moore, A. W.

    2017-12-01

    A new era of geodetic imaging arrived with the launch of the ESA Sentinel-1A/B satellites in 2014 and 2016, and with the 2016 confirmation of the NISAR mission, planned for launch in 2021. These missions assure high quality, freely and openly distributed regularly sampled SAR data into the indefinite future. These unprecedented data sets are a watershed for solid earth sciences as we progress towards the goal of ubiquitous InSAR measurements. We now face the challenge of how to best address the massive volumes of data and intensive processing requirements. Should scientists individually process the same data independently themselves? Should a centralized service provider create standard products that all can use? Are there other approaches to accelerate science that are cost effective and efficient? The Advanced Rapid Imaging and Analysis (ARIA) project, a joint venture co-sponsored by California Institute of Technology (Caltech) and by NASA through the Jet Propulsion Laboratory (JPL), is focused on rapidly generating higher level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. However, there are challenges in defining the optimal InSAR data products for the solid earth science community. In this presentation, we will present our experience with InSAR users, our lessons learned the advantages of on demand and standard products, and our proposal for the most effective path forward.

  15. Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula

    International Nuclear Information System (INIS)

    Mera, David; Cotos, José M.; Varela-Pet, José; Garcia-Pineda, Oscar

    2012-01-01

    Highlights: ► We present an adaptive thresholding algorithm to segment oil spills. ► The segmentation algorithm is based on SAR images and wind field estimations. ► A Database of oil spill confirmations was used for the development of the algorithm. ► Wind field estimations have demonstrated to be useful for filtering look-alikes. ► Parallel programming has been successfully used to minimize processing time. - Abstract: Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean’s surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.

  16. Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region.

    Science.gov (United States)

    Zhou, Tao; Pan, Jianjun; Zhang, Peiyu; Wei, Shanbao; Han, Tao

    2017-05-25

    Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar) images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A) and optical (Landsat-8) data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM) and a random forest (RF) method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure-up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data.

  17. A SAR Ice-Motion Processing Chain in Support of PROMICE (Programme for the Monitoring of the Greenland Ice Sheet)

    DEFF Research Database (Denmark)

    Merryman Boncori, John Peter; Dall, Jørgen; Ahlstrøm, A. P.

    2010-01-01

    This paper reports on the development of a SAR icemotion processing chain developed for the PROMICE project – a long-term program funded by the Danish ministry of Climate and Energy to monitor the mass budget of the Greenland ice sheet. The end goal of the SAR data processing is to output map-pro...

  18. Saharasar: An Interactive SAR Image Database for Desert Mapping

    Science.gov (United States)

    Lopez, S.; Paillou, Ph.

    2017-06-01

    We present a dedicated tool for accessing radar images acquired by the ALOS/PALSAR mission over Sahara and Arabia. We developed a dedicated web site, using the Mapserver web mapping server and the Cesium javascript library.

  19. LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

    Directory of Open Access Journals (Sweden)

    I. Schvartzman

    2016-06-01

    Full Text Available Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010. The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA data.

  20. Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

    Science.gov (United States)

    Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.

    2016-06-01

    Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

  1. Investigation of Joint Visibility Between SAR and Optical Images of Urban Environments

    Science.gov (United States)

    Hughes, L. H.; Auer, S.; Schmitt, M.

    2018-05-01

    In this paper, we present a work-flow to investigate the joint visibility between very-high-resolution SAR and optical images of urban scenes. For this task, we extend the simulation framework SimGeoI to enable a simulation of individual pixels rather than complete images. Using the extended SimGeoI simulator, we carry out a case study using a TerraSAR-X staring spotlight image and a Worldview-2 panchromatic image acquired over the city of Munich, Germany. The results of this study indicate that about 55 % of the scene are visible in both images and are thus suitable for matching and data fusion endeavours, while about 25 % of the scene are affected by either radar shadow or optical occlusion. Taking the image acquisition parameters into account, our findings can provide support regarding the definition of upper bounds for image fusion tasks, as well as help to improve acquisition planning with respect to different application goals.

  2. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  3. Markov Processes in Image Processing

    Science.gov (United States)

    Petrov, E. P.; Kharina, N. L.

    2018-05-01

    Digital images are used as an information carrier in different sciences and technologies. The aspiration to increase the number of bits in the image pixels for the purpose of obtaining more information is observed. In the paper, some methods of compression and contour detection on the basis of two-dimensional Markov chain are offered. Increasing the number of bits on the image pixels will allow one to allocate fine object details more precisely, but it significantly complicates image processing. The methods of image processing do not concede by the efficiency to well-known analogues, but surpass them in processing speed. An image is separated into binary images, and processing is carried out in parallel with each without an increase in speed, when increasing the number of bits on the image pixels. One more advantage of methods is the low consumption of energy resources. Only logical procedures are used and there are no computing operations. The methods can be useful in processing images of any class and assignment in processing systems with a limited time and energy resources.

  4. Aircraft Segmentation in SAR Images Based on Improved Active Shape Model

    Science.gov (United States)

    Zhang, X.; Xiong, B.; Kuang, G.

    2018-04-01

    In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.

  5. Image perception and image processing

    Energy Technology Data Exchange (ETDEWEB)

    Wackenheim, A.

    1987-01-01

    The author develops theoretical and practical models of image perception and image processing, based on phenomenology and structuralism and leading to original perception: fundamental for a positivistic approach of research work for the development of artificial intelligence that will be able in an automated system fo 'reading' X-ray pictures.

  6. Image perception and image processing

    International Nuclear Information System (INIS)

    Wackenheim, A.

    1987-01-01

    The author develops theoretical and practical models of image perception and image processing, based on phenomenology and structuralism and leading to original perception: fundamental for a positivistic approach of research work for the development of artificial intelligence that will be able in an automated system fo 'reading' X-ray pictures. (orig.) [de

  7. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    KAUST Repository

    Wang, Teng; Jonsson, Sigurjon

    2015-01-01

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  8. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    KAUST Repository

    Wang, Teng

    2015-02-03

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  9. Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.

    Science.gov (United States)

    Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

    2017-11-07

    This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

  10. Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

    Directory of Open Access Journals (Sweden)

    Tianzhu Yi

    2017-11-01

    Full Text Available This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR data processing. Several nonlinear chirp scaling (NLCS algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC. However, the azimuth depth of focusing (ADOF is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS algorithm that is proposed in this paper uses the method of series reverse (MSR to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

  11. Rice status and microwave characteristics: Analysis of rice paddy fields at Kojima Bay [Okayama, Japan] using multi-frequency and polarimetric Pi-SAR radar data images

    International Nuclear Information System (INIS)

    Ishitsuka, N.; Saito, G.; Ouchi, K.; Davidson, G.; Mohri, K.; Uratsuka, S.

    2003-01-01

    Abstract South-east Asia has a rainy-season at the crop growing period, and it is difficult to observe agricultural land in this season using optical remote sensing. Synthetic Aperture Radar (SAR) can observe the earth's surface without being influenced by of clouds. However, it is less useful for observing agricultural land, because satellite SAR has only one data band. Recently, SAR is able to provide multi band and multi polarimetric data. Pi-SAR, an airborne SAR developed by NASDA and CRL, can provide L and X bands and fully polarimetric data. Rice is the main crop in Asia, and we studied the characteristic microwave scatter on rice paddy fields using Pi-SAR data. Our study area was the rice paddy fields in Kojima reclaimed land in Japan. We had two fully polarimetric data sets from 13 July 1999 and 4 October 2000. First, we processed the color polarimetric composite image. Next we calibrated the phase of each polarimetric data using river area by the Kimura method. After that we performed decomposition analysis and drew polarimetric signatures for understanding the status of rice paddy fields. At the rice planting period, rice paddy fields are filled with water and rice plants are very small. The SAR microwave scatters on water surfaces like a mirror, called 'mirror (or specular) reflection'. This phenomenon makes backscatter a small value at the water-covered area. The image from July is about one month after trans-planting and rice plants are 20-40 cm in height. X-band microwave scatters on the rice surface, but L-band microwave passes through rice bodies and shows mirror refraction on water surfaces. Some strong backscatter occur on rice paddy fields especially VV polarization because of bragg scattering. The fields where bragg scattering returns strong VV scatter because the space between rice stems cause resonation in the L-band wavelength. We can easily understand bragg scatter by using polarimetric data. Using the image from October at

  12. AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

    Directory of Open Access Journals (Sweden)

    C. Xu

    2016-06-01

    Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  13. Bone scintigraphy in post-SARS patients and compared with magnetic resonance imaging

    International Nuclear Information System (INIS)

    Wang Qian; Huang Lili; Qin Shuling

    2004-01-01

    Objective: To study the characteristics of bone scintigraphy in post-SARS patients and evaluate the usefulness of bone scintigraphy in the prediction of avascular osteonecrosis (AVN) comparing with the MR imaging.. Methods: Our study included 66 patients who were diagnosed as SARS based on the diagnostic criteria issued by the Ministry of Health of China (MHC), including 46 women and 20 men. Their ages ranged from 19 to 63 years (mean, 31.6±0.1 years). All of the patients were treated with methyprednisonlone, rabavirin, broad spectrum antimicrobials and supportive therapy. Dosage of methyprednisonlone was 80∼800 mg/d for 4-72 days. Of them, varied seat of joint pain occurred in 47 patients 3 to 18 weeks after the onset of SARS. Since multiple joints were involved in many patients, bone scintigraphy was performed for screening AVN. The other 19 patients without of evident joint pain were also examined as their demand. Informed consents were obtained in all of the examined patients. No previously joint pain or trauma history was found in this group of patients. Of the 66 patients, planer X-ray was performed in 34 of the symptomatic patients previous to the scintigraphy, but it was negative in all. MR examination was performed in 54 patients before or after the scintigraphy, and the interval between two the tests was average of 8 days (range, 0 to 30 days). In addition, 27 consecutive cases aged lower than 45 years (mean, 40.4±0.8 years) with breast cancer who underwent bone scintigraphy for screening metastastic disease and had negative results were also involved as a control group. Whole body skeletal scintigraphy was performed 3 hours after intravenous administration of technetium-99m methylene-diphosphonate 740 MBq. Increased uptake lesion seen in the limb joints was defined as positive, but 'hot patella' sign was considered to be non diagnostic value. When a lesion was found in the whole body imaging, corresponding regional image was further taken. Two

  14. Decomposition of Polarimetric SAR Images Based on Second- and Third-order Statics Analysis

    Science.gov (United States)

    Kojima, S.; Hensley, S.

    2012-12-01

    There are many papers concerning the research of the decomposition of polerimetric SAR imagery. Most of them are based on second-order statics analysis that Freeman and Durden [1] suggested for the reflection symmetry condition that implies that the co-polarization and cross-polarization correlations are close to zero. Since then a number of improvements and enhancements have been proposed to better understand the underlying backscattering mechanisms present in polarimetric SAR images. For example, Yamaguchi et al. [2] added the helix component into Freeman's model and developed a 4 component scattering model for the non-reflection symmetry condition. In addition, Arii et al. [3] developed an adaptive model-based decomposition method that could estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in a SAR image without the reflection symmetry condition. This purpose of this research is to develop a new decomposition method based on second- and third-order statics analysis to estimate the surface, dihedral, volume and helix scattering components from polarimetric SAR images without the specific assumptions concerning the model for the volume scattering. In addition, we evaluate this method by using both simulation and real UAVSAR data and compare this method with other methods. We express the volume scattering component using the wire formula and formulate the relationship equation between backscattering echo and each component such as the surface, dihedral, volume and helix via linearization based on second- and third-order statics. In third-order statics, we calculate the correlation of the correlation coefficients for each polerimetric data and get one new relationship equation to estimate each polarization component such as HH, VV and VH for the volume. As a result, the equation for the helix component in this method is the same formula as one in Yamaguchi's method. However, the equation for the volume

  15. WEIBULL MULTIPLICATIVE MODEL AND MACHINE LEARNING MODELS FOR FULL-AUTOMATIC DARK-SPOT DETECTION FROM SAR IMAGES

    Directory of Open Access Journals (Sweden)

    A. Taravat

    2013-09-01

    Full Text Available As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method, synthetic aperture radar (SAR can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks. As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  16. Weibull Multiplicative Model and Machine Learning Models for Full-Automatic Dark-Spot Detection from SAR Images

    Science.gov (United States)

    Taravat, A.; Del Frate, F.

    2013-09-01

    As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  17. Hyperspectral image processing methods

    Science.gov (United States)

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

  18. Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images

    Science.gov (United States)

    Yang, C. H.; Pang, Y.; Soergel, U.

    2017-05-01

    Monitoring urban changes is important for city management, urban planning, updating of cadastral map, etc. In contrast to conventional field surveys, which are usually expensive and slow, remote sensing techniques are fast and cost-effective alternatives. Spaceborne synthetic aperture radar (SAR) sensors provide radar images captured rapidly over vast areas at fine spatiotemporal resolution. In addition, the active microwave sensors are capable of day-and-night vision and independent of weather conditions. These advantages make multi-temporal SAR images suitable for scene monitoring. Persistent scatterer interferometry (PSI) detects and analyses PS points, which are characterized by strong, stable, and coherent radar signals throughout a SAR image sequence and can be regarded as substructures of buildings in built-up cities. Attributes of PS points, for example, deformation velocities, are derived and used for further analysis. Based on PSI, a 4D change detection technique has been developed to detect disappearance and emergence of PS points (3D) at specific times (1D). In this paper, we apply this 4D technique to the centre of Berlin, Germany, to investigate its feasibility and application for construction monitoring. The aims of the three case studies are to monitor construction progress, business districts, and single buildings, respectively. The disappearing and emerging substructures of the buildings are successfully recognized along with their occurrence times. The changed substructures are then clustered into single construction segments based on DBSCAN clustering and α-shape outlining for object-based analysis. Compared with the ground truth, these spatiotemporal results have proven able to provide more detailed information for construction monitoring.

  19. Observation of pressure ridges in SAR images of sea ice: Scattering theory and comparison with observations

    Science.gov (United States)

    Vesecky, J. F.; Daida, J. M.; Shuchman, R. A.; Onstott, R. H.; Camiso, J. C.

    1993-01-01

    Ridges and keels (hummocks and bummocks) in sea ice flows are important in sea ice research for both scientific and practical reasons. Sea ice movement and deformation is driven by internal and external stresses on the ice. Ridges and keels play important roles in both cases because they determine the external wind and current stresses via drag coefficients. For example, the drag coefficient over sea ice can vary by a factor of several depending on the fluid mechanical roughness length of the surface. This roughness length is thought to be strongly dependent on the ridge structures present. Thus, variations in ridge and keel structure can cause gradients in external stresses which must be balanced by internal stresses and possibly fracture of the ice. Ridging in sea ice is also a sign of fracture. In a practical sense, large ridges form the biggest impediment to surface travel over the ice or penetration through sea ice by ice-strengthened ships. Ridges also play an important role in the damage caused by sea ice to off-shore structures. Hence, observation and measurement of sea ice ridges is an important component of sea ice remote sensing. The research reported here builds on previous work, estimating the characteristics of ridges and leads in sea ice from SAR images. Our objective is to develop methods for quantitative measurement of sea ice ridges from SAR images. To make further progress, in particular, to estimate ridge height, a scattering model for ridges is needed. Our research approach for a ridge scattering model begins with a survey of the geometrical properties of ridges and a comparison with the characteristics of the surrounding ice. For this purpose we have used airborne optical laser (AOL) data collected during the 1987 Greenland Sea Experiment. These data were used to generate a spatial wavenumber spectrum for height variance for a typical ridge - the typical ridge is the average over 10 large ridges. Our first-order model radar scattering includes

  20. Time Series Analysis OF SAR Image Fractal Maps: The Somma-Vesuvio Volcanic Complex Case Study

    Science.gov (United States)

    Pepe, Antonio; De Luca, Claudio; Di Martino, Gerardo; Iodice, Antonio; Manzo, Mariarosaria; Pepe, Susi; Riccio, Daniele; Ruello, Giuseppe; Sansosti, Eugenio; Zinno, Ivana

    2016-04-01

    The fractal dimension is a significant geophysical parameter describing natural surfaces representing the distribution of the roughness over different spatial scale; in case of volcanic structures, it has been related to the specific nature of materials and to the effects of active geodynamic processes. In this work, we present the analysis of the temporal behavior of the fractal dimension estimates generated from multi-pass SAR images relevant to the Somma-Vesuvio volcanic complex (South Italy). To this aim, we consider a Cosmo-SkyMed data-set of 42 stripmap images acquired from ascending orbits between October 2009 and December 2012. Starting from these images, we generate a three-dimensional stack composed by the corresponding fractal maps (ordered according to the acquisition dates), after a proper co-registration. The time-series of the pixel-by-pixel estimated fractal dimension values show that, over invariant natural areas, the fractal dimension values do not reveal significant changes; on the contrary, over urban areas, it correctly assumes values outside the natural surfaces fractality range and show strong fluctuations. As a final result of our analysis, we generate a fractal map that includes only the areas where the fractal dimension is considered reliable and stable (i.e., whose standard deviation computed over the time series is reasonably small). The so-obtained fractal dimension map is then used to identify areas that are homogeneous from a fractal viewpoint. Indeed, the analysis of this map reveals the presence of two distinctive landscape units corresponding to the Mt. Vesuvio and Gran Cono. The comparison with the (simplified) geological map clearly shows the presence in these two areas of volcanic products of different age. The presented fractal dimension map analysis demonstrates the ability to get a figure about the evolution degree of the monitored volcanic edifice and can be profitably extended in the future to other volcanic systems with

  1. The Intercomparison of X-Band SAR Images from COSMO‑SkyMed and TerraSAR-X Satellites: Case Studies

    Directory of Open Access Journals (Sweden)

    Simone Pettinato

    2013-06-01

    Full Text Available The analysis of experimental data collected by X-band SAR of COSMO-SkyMed (CSK® and TerraSAR-X (TSX images on the same surface types has shown significant differences in the signal level of the two sensors. In order to investigate the possibility of combining data from the two instruments, a study was carried out by comparing images collected with similar orbital and sensor parameters (e.g., incidence angle, polarization, look angle at approximately the same date on two Italian agricultural test sites. Several homogenous agricultural fields within the observed area common to the two sensors were selected. Some forest plots have also been considered and used as a reference target. Direct comparisons were then performed between CSK and TSX images in different acquisition modes. The analysis carried out on the agricultural fields showed that, in general, the backscattering coefficient is higher in TSX Stripmap images with respect to CSK-Himage (about 3 dB, while CSK-Ping Pong data showed values lower than TSX of about 4.8 dB. Finally, a difference in backscattering of about 2.5 dB was pointed out between CSK-Himage and Ping-Pong images on agricultural fields. These results, achieved on bare soils, have also been compared with simulations performed by using the Advanced Integral Equation Model (AIEM.

  2. Increased Efficiencies in the INEEL SAR/TSR/USQ Process

    International Nuclear Information System (INIS)

    Cole, N.E.

    2002-01-01

    The Idaho National Engineering and Environmental Laboratory (INEEL) has implemented a number of efficiencies to reduce the time and cost of preparing safety basis documents. The INEEL is continuing to look at other aspects of the safety basis process to identify other efficiencies that can be implemented and remain in compliance with Title 10 Code of Federal Regulations (CFR) Part 830. A six-sigma approach is used to identify areas to improve efficiencies and develop the action plan for implementation of the new process, as applicable. Three improvement processes have been implemented: The first was the development of standardized Documented Safety Analysis (DSA) and technical safety requirement (TSR) documents that all nuclear facilities use, by adding facility-specific details. The second is a material procurement process, which is based on safety systems specified in the individual safety basis documents. The third is a restructuring of the entire safety basis preparation and approval process. Significant savings in time to prepare safety basis document, cost of materials, and total cost of the documents are currently being realized

  3. The Advanced Rapid Imaging and Analysis (ARIA) Project: Status of SAR products for Earthquakes, Floods, Volcanoes and Groundwater-related Subsidence

    Science.gov (United States)

    Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Sacco, G. F.; Manipon, G.; Linick, J. P.; Fielding, E. J.; Lundgren, P.; Farr, T. G.; Webb, F.; Rosen, P. A.; Simons, M.

    2017-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating high-level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques including Interferometric Synthetic Aperture Radar (InSAR), differential Global Positioning System, and SAR-based change detection have become critical additions to our toolset for understanding and mapping the damage and deformation caused by earthquakes, volcanic eruptions, floods, landslides, and groundwater extraction. Up until recently, processing of these data sets has been handcrafted for each study or event and has not generated products rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by the California Institute of Technology and by NASA through the Jet Propulsion Laboratory, has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition to supporting the growing science and hazard response communities, the ARIA project has developed the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the influx of raw SAR data from geodetic imaging missions such as ESA's Sentinel-1A/B, now operating with repeat intervals as short as 6 days, and the upcoming NASA NISAR mission. We will present the progress and results we have made on automating the analysis of Sentinel-1A/B SAR data for hazard monitoring and response, with emphasis on recent developments and end user engagement in flood extent mapping and deformation time series for both volcano

  4. Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation

    Directory of Open Access Journals (Sweden)

    Maria Daniela Graziano

    2016-06-01

    Full Text Available A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances.

  5. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Directory of Open Access Journals (Sweden)

    Dongyang Ao

    2017-12-01

    Full Text Available The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS in the synthetic aperture radar (SAR images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  6. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Science.gov (United States)

    Ao, Dongyang; Hu, Cheng; Tian, Weiming

    2017-01-01

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures. PMID:29271917

  7. Two-Step Single Slope/SAR ADC with Error Correction for CMOS Image Sensor

    Directory of Open Access Journals (Sweden)

    Fang Tang

    2014-01-01

    Full Text Available Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μm CMOS technology. The chip area of the proposed ADC is 7 μm × 500 μm. The measurement results show that the energy efficiency figure-of-merit (FOM of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k μm2·cycles/sample.

  8. Two-step single slope/SAR ADC with error correction for CMOS image sensor.

    Science.gov (United States)

    Tang, Fang; Bermak, Amine; Amira, Abbes; Amor Benammar, Mohieddine; He, Debiao; Zhao, Xiaojin

    2014-01-01

    Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR) ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μ m CMOS technology. The chip area of the proposed ADC is 7 μ m × 500 μ m. The measurement results show that the energy efficiency figure-of-merit (FOM) of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k  μ m(2) · cycles/sample.

  9. Integrating interferometric SAR data with levelling measurements of land subsidence using geostatistics

    NARCIS (Netherlands)

    Zhou, Y.; Stein, A.; Molenaar, M.

    2003-01-01

    Differential Synthetic Aperture Radar (SAR) interferometric (D-InSAR) data of ground surface deformation are affected by several error sources associated with image acquisitions and data processing. In this paper, we study the use of D-InSAR for quantifying land subsidence due to groundwater

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

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

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

  11. Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

    Science.gov (United States)

    Mcconnell, Ross; Kober, Wolfgang; Kwok, Ronald; Curlander, John C.; Pang, Shirley S.

    1991-01-01

    The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

  12. Processing of medical images

    International Nuclear Information System (INIS)

    Restrepo, A.

    1998-01-01

    Thanks to the innovations in the technology for the processing of medical images, to the high development of better and cheaper computers, and, additionally, to the advances in the systems of communications of medical images, the acquisition, storage and handling of digital images has acquired great importance in all the branches of the medicine. It is sought in this article to introduce some fundamental ideas of prosecution of digital images that include such aspects as their representation, storage, improvement, visualization and understanding

  13. Satellite on-board real-time SAR processor prototype

    Science.gov (United States)

    Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François

    2017-11-01

    A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and

  14. Flood extent and water level estimation from SAR using data-model integration

    Science.gov (United States)

    Ajadi, O. A.; Meyer, F. J.

    2017-12-01

    Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

  15. SAR processing with stepped chirps and phased array antennas.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2006-09-01

    Wideband radar signals are problematic for phased array antennas. Wideband radar signals can be generated from series or groups of narrow-band signals centered at different frequencies. An equivalent wideband LFM chirp can be assembled from lesser-bandwidth chirp segments in the data processing. The chirp segments can be transmitted as separate narrow-band pulses, each with their own steering phase operation. This overcomes the problematic dilemma of steering wideband chirps with phase shifters alone, that is, without true time-delay elements.

  16. AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Q. Zhao

    2016-06-01

    Full Text Available Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

  17. Visual analytics for semantic queries of TerraSAR-X image content

    Science.gov (United States)

    Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

    2015-10-01

    With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain

  18. (Non-) homomorphic approaches to denoise intensity SAR images with non-local means and stochastic distances

    Science.gov (United States)

    Penna, Pedro A. A.; Mascarenhas, Nelson D. A.

    2018-02-01

    The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.

  19. User-friendly InSAR Data Products: Fast and Simple Timeseries (FAST) Processing

    Science.gov (United States)

    Zebker, H. A.

    2017-12-01

    Interferometric Synthetic Aperture Radar (InSAR) methods provide high resolution maps of surface deformation applicable to many scientific, engineering and management studies. Despite its utility, the specialized skills and computer resources required for InSAR analysis remain as barriers for truly widespread use of the technique. Reduction of radar scenes to maps of temporal deformation evolution requires not only detailed metadata describing the exact radar and surface acquisition geometries, but also a software package that can combine these for the specific scenes of interest. Furthermore, the radar range-Doppler radar coordinate system itself is confusing, so that many users find it hard to incorporate even useful products in their customary analyses. And finally, the sheer data volume needed to represent interferogram time series makes InSAR analysis challenging for many analysis systems. We show here that it is possible to deliver radar data products to users that address all of these difficulties, so that the data acquired by large, modern satellite systems are ready to use in more natural coordinates, without requiring further processing, and in as small volume as possible.

  20. An Adaptive Ship Detection Algorithm for Hrws SAR Images Under Complex Background: Application to SENTINEL1A Data

    Science.gov (United States)

    He, G.; Xia, Z.; Chen, H.; Li, K.; Zhao, Z.; Guo, Y.; Feng, P.

    2018-04-01

    Real-time ship detection using synthetic aperture radar (SAR) plays a vital role in disaster emergency and marine security. Especially the high resolution and wide swath (HRWS) SAR images, provides the advantages of high resolution and wide swath synchronously, significantly promotes the wide area ocean surveillance performance. In this study, a novel method is developed for ship target detection by using the HRWS SAR images. Firstly, an adaptive sliding window is developed to propose the suspected ship target areas, based upon the analysis of SAR backscattering intensity images. Then, backscattering intensity and texture features extracted from the training samples of manually selected ship and non-ship slice images, are used to train a support vector machine (SVM) to classify the proposed ship slice images. The approach is verified by using the Sentinl1A data working in interferometric wide swath mode. The results demonstrate the improvement performance of the proposed method over the constant false alarm rate (CFAR) method, where the classification accuracy improved from 88.5 % to 96.4 % and the false alarm rate mitigated from 11.5 % to 3.6 % compared with CFAR respectively.

  1. An Efficient SAR Image Segmentation Framework Using Transformed Nonlocal Mean and Multi-Objective Clustering in Kernel Space

    Directory of Open Access Journals (Sweden)

    Dongdong Yang

    2015-02-01

    Full Text Available Synthetic aperture radar (SAR image segmentation usually involves two crucial issues: suitable speckle noise removing technique and effective image segmentation methodology. Here, an efficient SAR image segmentation method considering both of the two aspects is presented. As for the first issue, the famous nonlocal mean (NLM filter is introduced in this study to suppress the multiplicative speckle noise in SAR image. Furthermore, to achieve a higher denoising accuracy, the local neighboring pixels in the searching window are projected into a lower dimensional subspace by principal component analysis (PCA. Thus, the nonlocal mean filter is implemented in the subspace. Afterwards, a multi-objective clustering algorithm is proposed using the principals of artificial immune system (AIS and kernel-induced distance measures. The multi-objective clustering has been shown to discover the data distribution with different characteristics and the kernel methods can improve its robustness to noise and outliers. Experiments demonstrate that the proposed method is able to partition the SAR image robustly and accurately than the conventional approaches.

  2. STUDY ON LANDSLIDE DISASTER EXTRACTION METHOD BASED ON SPACEBORNE SAR REMOTE SENSING IMAGES – TAKE ALOS PALSAR FOR AN EXAMPLE

    Directory of Open Access Journals (Sweden)

    D. Xue

    2018-04-01

    Full Text Available In this paper, sequence ALOS PALSAR data and airborne SAR data of L-band from June 5, 2008 to September 8, 2015 are used. Based on the research of SAR data preprocessing and core algorithms, such as geocode, registration, filtering, unwrapping and baseline estimation, the improved Goldstein filtering algorithm and the branch-cut path tracking algorithm are used to unwrap the phase. The DEM and surface deformation information of the experimental area were extracted. Combining SAR-specific geometry and differential interferometry, on the basis of composite analysis of multi-source images, a method of detecting landslide disaster combining coherence of SAR image is developed, which makes up for the deficiency of single SAR and optical remote sensing acquisition ability. Especially in bad weather and abnormal climate areas, the speed of disaster emergency and the accuracy of extraction are improved. It is found that the deformation in this area is greatly affected by faults, and there is a tendency of uplift in the southeast plain and western mountainous area, while in the southwest part of the mountain area there is a tendency to sink. This research result provides a basis for decision-making for local disaster prevention and control.

  3. MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA

    Directory of Open Access Journals (Sweden)

    M. Soheili Majd

    2012-09-01

    Full Text Available In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR data, through the modeling of several indices. We concentrate on eight ground classes which have been carried out from amplitudes, co-polarisation ratio, depolarization ratios, and other polarimetric descriptors. To study their different statistical behaviours, we consider Gauss, log- normal, Beta I, Weibull, Gamma, and Fisher statistical models and estimate their parameters using three methods: method of moments (MoM, maximum-likelihood (ML methodology, and log-cumulants method (MoML. Then, we study the opportunity of introducing this information in an adapted supervised classification scheme based on Maximum–Likelihood and Fisher pdf. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA. The results prove the potential of such data to discriminate urban surfaces and show the usefulness of adapting any classical classification algorithm however classification maps present a persistant class confusion between flat gravelled or concrete roofs and trees.

  4. Digital image processing

    National Research Council Canada - National Science Library

    Gonzalez, Rafael C; Woods, Richard E

    2008-01-01

    Completely self-contained-and heavily illustrated-this introduction to basic concepts and methodologies for digital image processing is written at a level that truly is suitable for seniors and first...

  5. Digital image processing

    National Research Council Canada - National Science Library

    Gonzalez, Rafael C; Woods, Richard E

    2008-01-01

    ...-year graduate students in almost any technical discipline. The leading textbook in its field for more than twenty years, it continues its cutting-edge focus on contemporary developments in all mainstream areas of image processing-e.g...

  6. Measurement of pressure ridges in SAR images of sea ice - Preliminary results on scattering theory

    Science.gov (United States)

    Vesecky, J. F.; Smith, M. P.; Daida, J. M.; Samadani, R.; Camiso, J. C.

    1992-01-01

    Sea ice ridges and keels (hummocks and bummocks) are important in sea ice research for both scientific and practical reasons. A long-term objective is to make quantitative measurements of sea ice ridges using synthetic aperture radar (SAR) images. The preliminary results of a scattering model for sea ice ridge are reported. The approach is through the ridge height variance spectrum Psi(K), where K is the spatial wavenumber, and the two-scale scattering model. The height spectrum model is constructed to mimic height statistics observed with an airborne optical laser. The spectrum model is used to drive a two-scale scattering model. Model results for ridges observed at C- and X-band yield normalized radar cross sections that are 10 to 15 dB larger than the observed cross sections of multiyear ice over the range of angles of incidence from 10 to 70 deg.

  7. Medical image processing

    CERN Document Server

    Dougherty, Geoff

    2011-01-01

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

  8. Near Surface Soil Moisture Estimation Using SAR Images: A Case Study in the Mediterranean Area of Catalonia

    Science.gov (United States)

    Reppucci, Antonio; Moreno, Laura

    2010-12-01

    Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.

  9. Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA

    Directory of Open Access Journals (Sweden)

    Qian Sun

    2014-12-01

    Full Text Available Monitoring slope instability is of great significance for understanding landslide kinematics and, therefore, reducing the related geological hazards. In recent years, interferometric synthetic aperture radar (InSAR has been widely applied to this end, especially thanks to the prompt evolution of multi-temporal InSAR (MTInSAR algorithms. In this paper, temporarily-coherent point InSAR (TCPInSAR, a recently-developed MTInSAR technique, is employed to investigate the slow-moving landslides in Oso, U.S., with 13 ALOS/PALSAR images. Compared to other MTInSAR techniques, TCPInSAR can work well with a small amount of data and is immune to unwrapping errors. Furthermore, the severe orbital ramps emanated from the inaccurate determination of the ALOS satellite’s state vector can be jointly estimated by TCPInSAR, resulting in an exhaustive separation between the orbital errors and displacement signals. The TCPInSAR-derived deformation map indicates that the riverside slopes adjacent to the North Fork of the Stillaguamish River, where the 2014 mudslide occurred, were active during 2007 and 2011. Besides, Coal Mountain has been found to be experiencing slow-moving landslides with clear boundaries and considerable magnitudes. The Deer Creek River is also threatened by a potential landslide dam due to the creeps detected in a nearby slope. The slope instability information revealed in this study is helpful to deal with the landslide hazards in Oso.

  10. Biomedical Image Processing

    CERN Document Server

    Deserno, Thomas Martin

    2011-01-01

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

  11. The study of molybdenite types related to the ore processing plant of the Sar Cheshmeh mine

    Directory of Open Access Journals (Sweden)

    Balandeh Aminzadeh

    2010-11-01

    Full Text Available Molybdenite occurs in five forms in the Sar Cheshmeh porphyry copper deposit, namely, (1-veinlets with quartz-molybdenite, (2-veinlets with quartz-molydenite that were filled with pyrite, (3-veinlets with quartz-molybdenite-pyrite–chalcopyrite, (4-Molybdenite veinlets with very low quartz and (5-disseminated molybdenite grains. Because of their large size, the veinlet-related molybdenite grains are easily liberated from the gangue minerals, provided the grinding is properly conducted (74 micron. Because of their fine-grain size, the disseminated molybdenite grains are not liberated from the gangue and enter the tailings during the flotation process.

  12. Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

    Science.gov (United States)

    An, Quanzhi; Pan, Zongxu; You, Hongjian

    2018-01-24

    Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

  13. Methods in Astronomical Image Processing

    Science.gov (United States)

    Jörsäter, S.

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

  14. Experimental validation of hyperthermia SAR treatment planning using MR B1+ imaging

    International Nuclear Information System (INIS)

    Berg, Cornelis A T van den; Bartels, Lambertus W; Leeuw, Astrid A C De; Lagendijk, Jan J W; Kamer, Jeroen B Van de

    2004-01-01

    In this paper the concept of using B 1+ imaging as a means to validate SAR models for radiofrequency hyperthermia is presented. As in radiofrequency hyperthermia, in common clinical MR imaging which applies RF frequencies between 64 and 128 MHz, the RF field distribution inside a patient is largely determined by the dielectric distribution of the anatomy. Modern MR imaging techniques allow measurement of the RF magnetic field component B 1+ making it possible to measure at high resolution the dielectric interaction of the RF field with the patient. Given these considerations, we propose to use MR imaging to verify the validity of our dielectric patient model used for SAR models of radiofrequency hyperthermia. The aim of this study was to investigate the feasibility of this concept by performing B 1+ measurements and simulations on cylindrical split phantoms consisting of materials with dielectric properties similar to human tissue types. Important topics of investigation were the accuracy and sensitivity of B 1+ measurements and the validity of the electric model of the MR body coil. The measurements were performed on a clinical 1.5 T MR scanner with its quadrature body coil operating at 64 MHz. It was shown that even small B 1+ variations of 2 to 5% could be measured reliably in the phantom experiments. An electrical model of the transmit coil was implemented on our FDTD-based hyperthermia treatment planning platform and the RF field distributions were calculated assuming an idealized quadrature current distribution in the coil. A quantitatively good correlation between measurements and simulations was found for phantoms consisting of water and oil, while highly conductive phantoms show considerable deviations. However, assuming linear excitation for these conductive phantoms resulted in good correspondence. As an explanation it is suggested that the coil is being detuned due to the inductive nature of the conductive phantoms, breaking up the phase difference of

  15. SAR Ground Moving Target Indication Based on Relative Residue of DPCA Processing

    Directory of Open Access Journals (Sweden)

    Jia Xu

    2016-10-01

    Full Text Available For modern synthetic aperture radar (SAR, it has much more urgent demands on ground moving target indication (GMTI, which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among the existing GMTI methods, displaced phase center antenna (DPCA can effectively cancel the strong ground clutter and has been widely used. However, its detection performance is closely related to the target’s signal-to-clutter ratio (SCR as well as radial velocity, and it cannot effectively detect the weak large-sized river surfaces in strong ground clutter due to their low SCR caused by specular scattering. This paper proposes a novel method called relative residue of DPCA (RR-DPCA, which jointly utilizes the DPCA cancellation outputs and the multi-look images to improve the detection performance of weak river surfaces. Furthermore, based on the statistics analysis of the RR-DPCA outputs on the homogenous background, the cell average (CA method can be well applied for subsequent constant false alarm rate (CFAR detection. The proposed RR-DPCA method can well detect the point moving targets and distributed moving targets simultaneously. Finally, the results of both simulated and real data are provided to demonstrate the effectiveness of the proposed SAR/GMTI method.

  16. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    KAUST Repository

    Wang, Teng

    2015-09-05

    Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

  17. Estimating Elevation Angles From SAR Crosstalk

    Science.gov (United States)

    Freeman, Anthony

    1994-01-01

    Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.

  18. LOTUS— Preparing Sentinel-3 Ocean and Land SAR Altimetry Processing for Copernicus

    DEFF Research Database (Denmark)

    Knudsen, Per; Andersen, Ole Baltazar; Jain, Maulik

    2014-01-01

    for commercial activities. The main objectives of the LOTUS project is to prepare the take-up of data from Sentinels 3. In the initial phase, LOTUS will develop processing scheme for extracting high-resolution sea surface heights, wave heights and wind speeds from SAR mode data. Over land, the LOTUS will develop...... potential of the new data source, new methods and processing chains need to be developed. Also, new potential Copernicus products should be developed that utilize the improved along-track resolution over both the oceans and over land. Then new operational processing, validation and delivery mechanisms need...... processing scheme for extracting high-resolution river and lake heights, soil moisture, and snow water equivalents. This presentation show some preliminary results based on analyses using CRYOSAT data. Furthermore, new DEMO data sets are presented. These data sets facilitate the development of marine...

  19. SAR (Synthetic Aperture Radar) Data Collection and Processing Summary - 1984 SARSEX (SAR Internal Wave Signature Experiment) Experiment.

    Science.gov (United States)

    1985-03-01

    DIVISION ;! -0 N xr-0 n 0n4 1 1 I- C) 0 Ic 0 C WIx W Qr - - r -r 01............................. I Cq I1 -a I- I X 0’ an w I w kI~r 1 0r- r- r . 0~~~ Cs CW 1...object from the SAR platform . Ground range, the 102 ~RIM RADAR DIVISION 0 0 sc 0’. C4 C4 Xn en % >4-4 441i V-u -- - W 1-11 04 v4 0o 0 4 0 (A~U Go 4J...Rg = rRF -hy ,(3) for the flat earth or low-altitude case, where h is the platform altitude. Because the range and azimuth scales are not the same

  20. Wake-based ship route estimation in high-resolution SAR images

    Science.gov (United States)

    Graziano, M. Daniela; Rufino, Giancarlo; D'Errico, Marco

    2014-10-01

    This paper presents a novel algorithm for wake detection in Synthetic Aperture Radar images of the sea. The algorithm has been conceived as part of a ship traffic monitoring system, in charge of ship detection validation and to estimate ship route features, such as heading and ground speed. In addition, it has been intended to be adequate for inclusion in an automatic procedure without human operator supervision. The algorithm exploits the Radon transform to identify the images ship wake on the basis of the well known theoretical characteristics of the wakes' geometry and components, that are the turbulent wake, the narrow-V wakes, and the Kelvin arms, as well as the typical appearance of such components in Synthetic Aperture Radar images of the sea as bright or dark linear feature. Examples of application to high-resolution X-band Synthetic Aperture Radar products (COSMOSkymed and TerraSAR-X) are reported, both for wake detection and ship route estimation, showing the achieved quality and reliability of wake detection, adequacy to automatic procedures, as well as speed measure accuracy.

  1. LOTUS— Preparing Sentinel-3 SAR Altimetry Processing for Ocean and Land

    DEFF Research Database (Denmark)

    Knudsen, Per; Andersen, Ole Baltazar; Nielsen, Karina

    2016-01-01

    methods and processing chains need to be developed. Subsequently, new potential Copernicus products should be developed that utilize the improved alongtrack resolution over both the oceans and over land. The main objective of the LOTUS project is to prepare the scientific and operational use of data from......The Sentinel-3 satellite mission with its SRAL instrumentation contains new features compared to the conventional radar altimeter mission that form the basis for new innovative scientific analyses of both ocean and inland water levels. To utilize the full potential of the new data source, new...... that they will be used for commercial activities. LOTUS will develop processing scheme for extracting high-resolution sea surface heights, wave heights and wind speeds from SAR mode data. Over land, the LOTUS will develop processing scheme for extracting high-resolution river and lake heights, soil moisture, and snow...

  2. Image processing in radiology

    International Nuclear Information System (INIS)

    Dammann, F.

    2002-01-01

    Medical imaging processing and analysis methods have significantly improved during recent years and are now being increasingly used in clinical applications. Preprocessing algorithms are used to influence image contrast and noise. Three-dimensional visualization techniques including volume rendering and virtual endoscopy are increasingly available to evaluate sectional imaging data sets. Registration techniques have been developed to merge different examination modalities. Structures of interest can be extracted from the image data sets by various segmentation methods. Segmented structures are used for automated quantification analysis as well as for three-dimensional therapy planning, simulation and intervention guidance, including medical modelling, virtual reality environments, surgical robots and navigation systems. These newly developed methods require specialized skills for the production and postprocessing of radiological imaging data as well as new definitions of the roles of the traditional specialities. The aim of this article is to give an overview of the state-of-the-art of medical imaging processing methods, practical implications for the ragiologist's daily work and future aspects. (orig.) [de

  3. Automated Waterline Detection in the Wadden Sea Using High-Resolution TerraSAR-X Images

    Directory of Open Access Journals (Sweden)

    Stefan Wiehle

    2015-01-01

    Full Text Available We present an algorithm for automatic detection of the land-water-line from TerraSAR-X images acquired over the Wadden Sea. In this coastal region of the southeastern North Sea, a strip of up to 20 km of seabed falls dry during low tide, revealing mudflats and tidal creeks. The tidal currents transport sediments and can change the coastal shape with erosion rates of several meters per month. This rate can be strongly increased by storm surges which also cause flooding of usually dry areas. Due to the high number of ships traveling through the Wadden Sea to the largest ports of Germany, frequent monitoring of the bathymetry is also an important task for maritime security. For such an extended area and the required short intervals of a few months, only remote sensing methods can perform this task efficiently. Automating the waterline detection in weather-independent radar images provides a fast and reliable way to spot changes in the coastal topography. The presented algorithm first performs smoothing, brightness thresholding, and edge detection. In the second step, edge drawing and flood filling are iteratively performed to determine optimal thresholds for the edge drawing. In the last step, small misdetections are removed.

  4. Processing Of Binary Images

    Science.gov (United States)

    Hou, H. S.

    1985-07-01

    An overview of the recent progress in the area of digital processing of binary images in the context of document processing is presented here. The topics covered include input scan, adaptive thresholding, halftoning, scaling and resolution conversion, data compression, character recognition, electronic mail, digital typography, and output scan. Emphasis has been placed on illustrating the basic principles rather than descriptions of a particular system. Recent technology advances and research in this field are also mentioned.

  5. Use of ERS-2 Sar and Landsat TM Images for Geological Mapping and Mineral Exploration Of Sol Hamid Area, South Eastern Desert, Egypt

    International Nuclear Information System (INIS)

    Ramadan, T.M.

    2003-01-01

    Sol hamid area is chiefy occupied by neo proterozoic rocks, partly covered by miocene sediments and recent sand sheets and dunes. The neo proterozoic rocks include ophiolitic ultramafic to mafic rocks, meta volcano-sedimentary rocks, meta volcanics, gabbros-diorite rocks, granodiorites, biotite granites and alkali granites. Magnesite, chromite, iron ores, manganese and barite ore deposits are hosted in different at the study area. ERS-2 SAR data enabled to obtain an image that reveals some buried fluvial features beneath the surface cover of desert sand. These features are not observable in Landsat TM image of similar resolution. In this work, Principal Component Analysis (PCA) technique was used for merging ERS-2 SAR and Landsat TM images to make use of the potential of data fusion technique of image processing in the interpretation of geological features. This procedure has resulted in enhancing subsurface structure such as faults that control distribution of several deposits in the study area. This study represents an example to demonstrate the utility of merging various remote sensing data for exploring mineral deposits in arid region

  6. Design and characterization of a 12-bit 10MS/s 10mW pipelined SAR ADC for CZT-based hard X-ray imager

    Science.gov (United States)

    Xue, F.; Gao, W.; Duan, Y.; Zheng, R.; Hu, Y.

    2018-02-01

    This paper presents a 12-bit pipelined successive approximation register (SAR) ADC for CZT-based hard X-ray Imager. The proposed ADC is comprised of a first-stage 6-bit SAR-based Multiplying Digital Analog Converter (MDAC) and a second-stage 8-bit SAR ADC. A novel MDAC architecture using Vcm-based Switching method is employed to maximize the energy efficiency and improve the linearity of the ADC. Moreover, the unit-capacitor array instead of the binary-weighted capacitor array is adopted to improve the conversion speed and linearity of the ADC in the first-stage MDAC. In addition, a new layout design method for the binary-weighted capacitor array is proposed to reduce the capacitor mismatches and make the routing become easier and less-time-consuming. Finally, several radiation-hardened-by-design technologies are adopted in the layout design against space radiation effects. The prototype chip was fabricated in 0.18 μm mixed-signal 1.8V/3.3V process and operated at 1.8 V supply. The chip occupies a core area of only 0.58 mm2. The proposed pipelined SAR ADC achieves a peak signal-to-noise-and-distortion ratio (SNDR) of 66.7 dB and a peak spurious-free dynamic range (SFDR) of 78.6 dB at 10 MS/s sampling rate and consumes 10 mW. The figure of merit (FOM) of the proposed ADC is 0.56 pJ/conversion-step.

  7. Dual Super-Systolic Core for Real-Time Reconstructive Algorithms of High-Resolution Radar/SAR Imaging Systems

    Science.gov (United States)

    Atoche, Alejandro Castillo; Castillo, Javier Vázquez

    2012-01-01

    A high-speed dual super-systolic core for reconstructive signal processing (SP) operations consists of a double parallel systolic array (SA) machine in which each processing element of the array is also conceptualized as another SA in a bit-level fashion. In this study, we addressed the design of a high-speed dual super-systolic array (SSA) core for the enhancement/reconstruction of remote sensing (RS) imaging of radar/synthetic aperture radar (SAR) sensor systems. The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms. As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene. We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode. PMID:22736964

  8. Simulation-Based Evaluation of Light Posts and Street Signs as 3-D Geolocation Targets in SAR Images

    Science.gov (United States)

    Auer, S.; Balss, U.

    2017-05-01

    The assignment of phase center positions (in 2D or 3D) derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR). For the first time, the appearance of the targets is analyzed in 2D (image plane) and 3D space (world coordinates of scene model) and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  9. Hyperspectral image processing

    CERN Document Server

    Wang, Liguo

    2016-01-01

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

  10. Surface deformation induced by magmatic processes at Pacaya Volcano, Guatemala revealed by InSAR

    Science.gov (United States)

    Wnuk, K.; Wauthier, C.

    2017-09-01

    Pacaya Volcano, Guatemala is a continuously active, basaltic volcano with an unstable western flank. Despite continuous activity since 1961, a lack of high temporal resolution geodetic surveying has prevented detailed modeling of Pacaya's underlying magmatic plumbing system. A new, temporally dense dataset of Interferometric Synthetic Aperture Radar (InSAR) RADARSAT-2 images, spanning December 2012 to March 2014, show magmatic deformation before and during major eruptions in January and March 2014. Inversion of InSAR surface displacements using simple analytical forward models suggest that three magma bodies are responsible for the observed deformation: (1) a 4 km deep spherical reservoir located northwest of the summit, (2) a 0.4 km deep spherical source located directly west of the summit, and (3) a shallow dike below the summit. Periods of heightened volcanic activity are instigated by magma pulses at depth, resulting in rapid inflation of the edifice. We observe an intrusion cycle at Pacaya that consists of deflation of one or both magma reservoirs followed by dike intrusion. Intrusion volumes are proportional to reservoir volume loss and do not always result in an eruption. Periods of increased activity culminate with larger dike-fed eruptions. Large eruptions are followed by inter-eruptive periods marked by a decrease in crater explosions and a lack of detected deformation. Co-eruptive flank motion appears to have initiated a new stage of volcanic rifting at Pacaya defined by repeated NW-SE oriented dike intrusions. This creates a positive feedback relationship whereby magmatic forcing from eruptive dike intrusions induce flank motion.

  11. Integration of InSAR and GIS in the Study of Surface Faults Caused by Subsidence-Creep-Fault Processes in Celaya, Guanajuato, Mexico

    International Nuclear Information System (INIS)

    Avila-Olivera, Jorge A.; Farina, Paolo; Garduno-Monroy, Victor H.

    2008-01-01

    In Celaya city, Subsidence-Creep-Fault Processes (SCFP) began to become visible at the beginning of the 1980s with the sprouting of the crackings that gave rise to the surface faults 'Oriente' and 'Poniente'. At the present time, the city is being affected by five surface faults that display a preferential NNW-SSE direction, parallel to the regional faulting system 'Taxco-San Miguel de Allende'. In order to study the SCFP in the city, the first step was to obtain a map of surface faults, by integrating in a GIS field survey and an urban city plan. The following step was to create a map of the current phreatic level decline in city with the information of deep wells and using the 'kriging' method in order to obtain a continuous surface. Finally the interferograms maps resulted of an InSAR analysis of 9 SAR images covering the time interval between July 12 of 2003 and May 27 of 2006 were integrated to a GIS. All the maps generated, show how the surface faults divide the city from North to South, in two zones that behave in a different way. The difference of the phreatic level decline between these two zones is 60 m; and the InSAR study revealed that the Western zone practically remains stable, while sinkings between the surface faults 'Oriente' and 'Universidad Pedagogica' are present, as well as in portions NE and SE of the city, all of these sinkings between 7 and 10 cm/year

  12. An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

    Directory of Open Access Journals (Sweden)

    Xiangguang Leng

    2016-08-01

    Full Text Available With the rapid development of spaceborne synthetic aperture radar (SAR and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way.

  13. SAR Imaging of Wave Tails: Recognition of Second Mode Internal Wave Patterns and Some Mechanisms of their Formation

    Science.gov (United States)

    da Silva, Jose C. B.; Magalhaes, J. M.; Buijsman, M. C.; Garcia, C. A. E.

    2016-08-01

    Mode-2 internal waves are usually not as energetic as larger mode-1 Internal Solitary Waves (ISWs), but they have attracted a great deal of attention in recent years because they have been identified as playing a significant role in mixing shelf waters [1]. This mixing is particularly effective for mode-2 ISWs because the location of these waves in the middle of the pycnocline plays an important role in eroding the barrier between the base of the surface mixed layer and the stratified deep layer below. An urgent problem in physical oceanography is therefore to account for the magnitude and distribution of ISW-driven mixing, including mode-2 ISWs. Several generation mechanisms of mode-2 ISWs have been identified. These include: (1) mode-1 ISWs propagating onshore (shoaling) and entering the breaking instability stage, or propagating over a steep sill; (2) a mode-1 ISW propagating offshore (antishoaling) over steep slopes of the shelf break, and undergoing modal transformation; (3) intrusion of the whole head of a gravity current into a three-layer fluid; (4) impingement of an internal tidal beam on the pycnocline, itself emanating from critical bathymetry; (5) nonlinear disintegration of internal tide modes; (6) lee wave mechanism. In this paper we provide methods to identify internal wave features denominated "Wave Tails" in SAR images of the ocean surface, which are many times associated with second mode internal waves. The SAR case studies that are presented portray evidence of the aforementioned generation mechanisms, and we further discuss possible methods to discriminate between the various types of mode-2 ISWs in SAR images, that emerge from these physical mechanisms. Some of the SAR images correspond to numerical simulations with the MITgcm in fully nonlinear and nonhydrostatic mode and in a 2D configuration with realistic stratification, bathymetry and other environmental conditions.Results of a global survey with some of these observations are presented

  14. Introduction to computer image processing

    Science.gov (United States)

    Moik, J. G.

    1973-01-01

    Theoretical backgrounds and digital techniques for a class of image processing problems are presented. Image formation in the context of linear system theory, image evaluation, noise characteristics, mathematical operations on image and their implementation are discussed. Various techniques for image restoration and image enhancement are presented. Methods for object extraction and the problem of pictorial pattern recognition and classification are discussed.

  15. Introduction to digital image processing

    CERN Document Server

    Pratt, William K

    2013-01-01

    CONTINUOUS IMAGE CHARACTERIZATION Continuous Image Mathematical Characterization Image RepresentationTwo-Dimensional SystemsTwo-Dimensional Fourier TransformImage Stochastic CharacterizationPsychophysical Vision Properties Light PerceptionEye PhysiologyVisual PhenomenaMonochrome Vision ModelColor Vision ModelPhotometry and ColorimetryPhotometryColor MatchingColorimetry ConceptsColor SpacesDIGITAL IMAGE CHARACTERIZATION Image Sampling and Reconstruction Image Sampling and Reconstruction ConceptsMonochrome Image Sampling SystemsMonochrome Image Reconstruction SystemsColor Image Sampling SystemsImage QuantizationScalar QuantizationProcessing Quantized VariablesMonochrome and Color Image QuantizationDISCRETE TWO-DIMENSIONAL LINEAR PROCESSING Discrete Image Mathematical Characterization Vector-Space Image RepresentationGeneralized Two-Dimensional Linear OperatorImage Statistical CharacterizationImage Probability Density ModelsLinear Operator Statistical RepresentationSuperposition and ConvolutionFinite-Area Superp...

  16. Coral reef detection using SAR/RADARSAT-1 images at Costa dos Corais, PE/AL, Brazil

    Directory of Open Access Journals (Sweden)

    Frederico de Moraes Rudorff

    2008-06-01

    Full Text Available The present work aimed to examine the potentials of SAR RADARSAT-1 images to detect emergent coral reefs at the Environmental Protection Area of "Costa dos Corais". Multi-view filters were applied and tested for speckle noise reduction. A digital unsupervised classification based on image segmentation was performed and the classification accuracy was evaluated by an error matrix built between the SAR image classification and a reference map obtained from a TM Landsat-5 classification. The adaptative filters showed the best results for speckle suppression and border preservation, especially the Kuan, Gamma MAP, Lee, Frost and Enhanced Frost filters. Small similarity and area thresholds (5 and 10, respectively were used for the image segmentation due to the reduced dimensions and the narrow and elongated forms of the reefs. The classification threshold of 99% had a better user's accuracy, but a lower producer's accuracy because it is a more restrictive threshold; therefore, it may be possible that it had a greater omission on reef classification. The results indicate that SAR images have a good potential for the detection of emergent coral reefs.O presente trabalho examinou o potencial de imagens SAR do RADARSAT-1 na detecção de recifes de coral expostos na Área de Proteção Ambiental das Costa dos Corais. Filtros de multi-visada foram aplicados e testados para redução do ruído speckle. Uma classificação não supervisionada baseada em uma imagem segmentada foi realizada e a acurácia da classificação foi avaliada através de uma matriz de erro construída entre a imagem classificada e o mapa de referência. Os filtros adaptativos apresentaram os melhores desempenhos para supressão de speckle e preservação de bordas, especialmente os filtros Kuan, Gamma MAP, Lee, Frost and Enhanced Frost. Os pequenos limiares de similaridade e de área (10 e 5, respectivamente foram melhores devido à forma fina e alongada dos recifes. O limiar de

  17. Oil seepage polarimetric contrast analysis in a time series of TerraSAR-X images

    OpenAIRE

    de Macedo, Carina Regina; Nunziata, Ferdinando; Velotto, Domenico; Migliaccio, Maurizio

    2017-01-01

    Natural hydrocarbon seeps are broadly distributed across the Gulf of Mexico. Such seeps emit oil and gas into the water column, increasing the phytoplankton biomass and impacting regionally the productivity, carbon and nutrient cycling [1]. A fraction of this oil reaches to the sea surface and can be detected by SAR data. Although the ability of SAR data to detect oil features present in ocean's surface is wide exploited in the literature, it is known that the detection of those features is a...

  18. Bistatic SAR: Proof of Concept.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Doren, Neall E.; Bacon, Terry A.; Wahl, Daniel E.; Eichel, Paul H.; Jakowatz, Charles V,; Delaplain, Gilbert G.; Dubbert, Dale F.; Tise, Bertice L.; White, Kyle R.

    2014-10-01

    Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

  19. scikit-image: image processing in Python.

    Science.gov (United States)

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

    2014-01-01

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

  20. scikit-image: image processing in Python

    Directory of Open Access Journals (Sweden)

    Stéfan van der Walt

    2014-06-01

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

  1. Millimeter wave radar system on a rotating platform for combined search and track functionality with SAR imaging

    Science.gov (United States)

    Aulenbacher, Uwe; Rech, Klaus; Sedlmeier, Johannes; Pratisto, Hans; Wellig, Peter

    2014-10-01

    Ground based millimeter wave radar sensors offer the potential for a weather-independent automatic ground surveillance at day and night, e.g. for camp protection applications. The basic principle and the experimental verification of a radar system concept is described, which by means of an extreme off-axis positioning of the antenna(s) combines azimuthal mechanical beam steering with the formation of a circular-arc shaped synthetic aperture (SA). In automatic ground surveillance the function of search and detection of moving ground targets is performed by means of the conventional mechanical scan mode. The rotated antenna structure designed as a small array with two or more RX antenna elements with simultaneous receiver chains allows to instantaneous track multiple moving targets (monopulse principle). The simultaneously operated SAR mode yields areal images of the distribution of stationary scatterers. For ground surveillance application this SAR mode is best suited for identifying possible threats by means of change detection. The feasibility of this concept was tested by means of an experimental radar system comprising of a 94 GHz (W band) FM-CW module with 1 GHz bandwidth and two RX antennas with parallel receiver channels, placed off-axis at a rotating platform. SAR mode and search/track mode were tested during an outdoor measurement campaign. The scenery of two persons walking along a road and partially through forest served as test for the capability to track multiple moving targets. For SAR mode verification an image of the area composed of roads, grassland, woodland and several man-made objects was reconstructed from the measured data.

  2. Wave directional spectrum from SAR imagery

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    Gaussian smoothed SAR image spectra have been evaluated from 512 x 512 pixel subscenes of image mode ERS-1 SAR scenes off Goa, Visakhapatnam, Paradeep and Portugal. The two recently acquired scenes off Portugal showed the signature of swell...

  3. Monitoring Building Deformation with InSAR: Experiments and Validation

    Science.gov (United States)

    Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng

    2016-01-01

    Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated. PMID:27999403

  4. Monitoring Building Deformation with InSAR: Experiments and Validation

    Directory of Open Access Journals (Sweden)

    Kui Yang

    2016-12-01

    Full Text Available Synthetic Aperture Radar Interferometry (InSAR techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.

  5. Exploitation of Amplitude and Phase of Satellite SAR Images for Landslide Mapping: The Case of Montescaglioso (South Italy

    Directory of Open Access Journals (Sweden)

    Federico Raspini

    2015-11-01

    Full Text Available Pre- event and event landslide deformations have been detected and measured for the landslide that occurred on 3 December 2013 on the south-western slope of the Montescaglioso village (Basilicata Region, southern Italy. In this paper, ground displacements have been mapped through an integrated analysis based on a series of high resolution SAR (Synthetic Aperture Radar images acquired by the Italian constellation of satellites COSMO-SkyMed. Analysis has been performed by exploiting both phase (through multi-image SAR interferometry and amplitude information (through speckle tracking techniques of the satellite images. SAR Interferometry, applied to images taken before the event, revealed a general pre-event movement, in the order of a few mm/yr, in the south-western slope of the Montescaglioso village. Highest pre-event velocities, ranging between 8 and 12 mm/yr, have been recorded in the sector of the slope where the first movement of the landslide took place. Speckle tracking, applied to images acquired before and after the event, allowed the retrieval of the 3D deformation field produced by the landslide. It also showed that ground displacements produced by the landslide have a dominant SSW component, with values exceeding 10 m for large sectors of the landslide area, with local peaks of 20 m in its central and deposit areas. Two minor landslides with a dominant SSE direction, which were detected in the upper parts of the slope, likely also occurred as secondary phenomena as consequence of the SSW movement of the main Montescaglioso landslide.

  6. DATA PROCESSING CONCEPTS FOR THE INTEGRATION OF SAR INTO OPERATIONAL VOLCANO MONITORING SYSTEMS

    Directory of Open Access Journals (Sweden)

    F. J. Meyer

    2013-05-01

    Full Text Available Remote Sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and despite its high performance in monitoring change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to (1 the high data costs associated with radar data, (2 the slow data processing and delivery procedures, and (3 the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of the above mentioned limitations and allow for a meaningful integration of radar remote sensing data into operational volcano monitoring systems. The data integration concept presented here combines advanced data processing techniques with fast data access procedures in order to provide high quality radar-based volcano hazard information at improved temporal sampling rates. First performance analyses show that the integration of SAR can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities.

  7. Image processing and recognition for biological images.

    Science.gov (United States)

    Uchida, Seiichi

    2013-05-01

    This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. © 2013 The Author Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

  8. Infrastructure monitoring with spaceborne SAR sensors

    CERN Document Server

    ANGHEL, ANDREI; CACOVEANU, REMUS

    2017-01-01

    This book presents a novel non-intrusive infrastructure monitoring technique based on the detection and tracking of scattering centers in spaceborne SAR images. The methodology essentially consists of refocusing each available SAR image on an imposed 3D point cloud associated to the envisaged infrastructure element and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The methodology described in this book provides a new perspective on infrastructure monitoring with spaceborne SAR images, is based on a standalone processing chain, and brings innovative technical aspects relative to conventional approaches. The book is intended primarily for professionals and researchers working in the area of critical infrastructure monitoring by radar remote sensing.

  9. A SAR-ADC using unit bridge capacitor and with calibration for the front-end electronics of PET imaging

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Wei [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Wei, Tingcun, E-mail: weitc@nwpu.edu.cn [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Li, Bo; Yang, Lifeng; Xue, Feifei [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Hu, Yongcai [Institut Pluridisciplinaire Hubert CURIEN, Strasbourg (France)

    2016-05-11

    This paper presents a 12-bit 1 MS/s successive approximation register-analog to digital converter (SAR-ADC) for the 32-channel front-end electronics of CZT-based PET imaging system. To reduce the capacitance mismatch, instead of the fractional capacitor, the unit capacitor is used as the bridge capacitor in the split-capacitor digital to analog converter (DAC) circuit. In addition, in order to eliminate the periodical DNL errors of −1 LSB which often exists in the SAR-ADC using the charge-redistributed DAC, a calibration algorithm is proposed and verified by the experiments. The proposed 12-bit 1 MS/s SAR-ADC is designed and implemented using a 0.35 μm CMOS technology, it occupies only an active area of 986×956 μm{sup 2}. The measurement results show that, at the power supply of 3.3/5.0 V and the sampling rate of 1 MS/s, the ADC with calibration has a signal-to-noise-and-distortion ratio (SINAD) of 67.98 dB, the power dissipation of 5 mW, and a figure of merit (FOM) of 2.44 pJ/conv.-step. This ADC is with the features of high accuracy, low power and small layout area, it is especially suitable to the one-chip integration of the front-end readout electronics.

  10. Image processing with ImageJ

    CERN Document Server

    Pascau, Javier

    2013-01-01

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

  11. Advanced radar-interpretation of InSAR time series for mapping and characterization of geological processes

    OpenAIRE

    Cigna, F.; Del Ventisette, C.; Liguori, V.; Casagli, N.

    2011-01-01

    We present a new post-processing methodology for the analysis of InSAR (Synthetic Aperture Radar Interferometry) multi-temporal measures, based on the temporal under-sampling of displacement time series, the identification of potential changes occurring during the monitoring period and, eventually, the classification of different deformation behaviours. The potentials of this approach for the analysis of geological processes were tested on the case study of Naro (Italy), specifically selected...

  12. SAR Processing on Demand Service for CryoSat-2 and Sentinel-3 at ESA G-POD

    Science.gov (United States)

    Benveniste, Jérôme; Ambrózio, Américo; Restano, Marco; Dinardo, Salvatore

    2016-04-01

    The scope of this presentation is to feature the G-POD SARvatore service to users for the exploitation of the CryoSat-2 and Sentniel-3 data, which was designed and developed by the Altimetry Team at ESA-ESRIN EOP-SER (Earth Observation - Exploitation, Research and Development). The G-POD service coined SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research & Exploitation) is a web platform that allows any scientist to process on-line, on-demand and with user-selectable configuration CryoSat-2 SAR/SARIN data, from L1a (FBR) data products up to SAR/SARin Level-2 geophysical data products. The Processor takes advantage of the G-POD (Grid Processing On Demand) distributed computing platform (350 CPUs in ~70 Working Nodes) to timely deliver output data products and to interface with ESA-ESRIN FBR data archive (210'000 SAR passes and 120'000 SARin passes). The output data products are generated in standard NetCDF format (using CF Convention), therefore being compatible with the multi-mission Broadview Radar Altimetry Toolbox (BRAT) and other NetCDF tools. By using the G-POD graphical interface, it is straightforward to select a geographical area of interest within the time-frame related to the Cryosat-2 SAR/SARin FBR data products availability in the service catalogue. The processor prototype is versatile, allowing users to customize and to adapt the processing, according to their specific requirements, by setting a list of configurable options. After the task submission, users can follow, in real time, the status of the processing. From the web interface, users can choose to generate experimental SAR data products as stack data and RIP (Range Integrated Power) waveforms. The processing service, initially developed to support the development contracts awarded by confronting the deliverables to ESA's computations, has been made available to the worldwide SAR Altimetry Community for research & development experiments, for hands-on demonstrations/training in

  13. An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

    Science.gov (United States)

    Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

    2017-01-23

    Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

  14. An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS

    Directory of Open Access Journals (Sweden)

    Zhongyu Li

    2017-01-01

    Full Text Available Bistatic forward-looking SAR (BFSAR is a kind of bistatic synthetic aperture radar (SAR system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I large and unknown range cell migration (RCM (including range walk and high-order RCM; (II the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

  15. Processing Visual Images

    International Nuclear Information System (INIS)

    Litke, Alan

    2006-01-01

    The back of the eye is lined by an extraordinary biological pixel detector, the retina. This neural network is able to extract vital information about the external visual world, and transmit this information in a timely manner to the brain. In this talk, Professor Litke will describe a system that has been implemented to study how the retina processes and encodes dynamic visual images. Based on techniques and expertise acquired in the development of silicon microstrip detectors for high energy physics experiments, this system can simultaneously record the extracellular electrical activity of hundreds of retinal output neurons. After presenting first results obtained with this system, Professor Litke will describe additional applications of this incredible technology.

  16. Fundamentals of electronic image processing

    CERN Document Server

    Weeks, Arthur R

    1996-01-01

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

  17. Imaging the complex geometry of a magma reservoir using FEM-based linear inverse modeling of InSAR data: application to Rabaul Caldera, Papua New Guinea

    Science.gov (United States)

    Ronchin, Erika; Masterlark, Timothy; Dawson, John; Saunders, Steve; Martì Molist, Joan

    2017-06-01

    We test an innovative inversion scheme using Green's functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green's function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluid-filled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green's functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the

  18. Post-Eruption Deformation Processes Measured Using ALOS-1 and UAVSAR InSAR at Pacaya Volcano, Guatemala

    Directory of Open Access Journals (Sweden)

    Lauren N. Schaefer

    2016-01-01

    Full Text Available Pacaya volcano is a persistently active basaltic cone complex located in the Central American Volcanic Arc in Guatemala. In May of 2010, violent Volcanic Explosivity Index-3 (VEI-3 eruptions caused significant topographic changes to the edifice, including a linear collapse feature 600 m long originating from the summit, the dispersion of ~20 cm of tephra and ash on the cone, the emplacement of a 5.4 km long lava flow, and ~3 m of co-eruptive movement of the southwest flank. For this study, Interferometric Synthetic Aperture Radar (InSAR images (interferograms processed from both spaceborne Advanced Land Observing Satellite-1 (ALOS-1 and aerial Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR data acquired between 31 May 2010 and 10 April 2014 were used to measure post-eruptive deformation events. Interferograms suggest three distinct deformation processes after the May 2010 eruptions, including: (1 subsidence of the area involved in the co-eruptive slope movement; (2 localized deformation near the summit; and (3 emplacement and subsequent subsidence of about a 5.4 km lava flow. The detection of several different geophysical signals emphasizes the utility of measuring volcanic deformation using remote sensing techniques with broad spatial coverage. Additionally, the high spatial resolution of UAVSAR has proven to be an excellent compliment to satellite data, particularly for constraining motion components. Measuring the rapid initiation and cessation of flank instability, followed by stabilization and subsequent influence on eruptive features, provides a rare glimpse into volcanic slope stability processes. Observing these and other deformation events contributes both to hazard assessment at Pacaya and to the study of the stability of stratovolcanoes.

  19. The retrieval of two-dimensional distribution of the earth's surface aerodynamic roughness using SAR image and TM thermal infrared image

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Renhua; WANG; Jinfeng; ZHU; Caiying; SUN; Xiaomin

    2004-01-01

    After having analyzed the requirement on the aerodynamic earth's surface roughness in two-dimensional distribution in the research field of interaction between land surface and atmosphere, this paper presents a new way to calculate the aerodynamic roughness using the earth's surface geometric roughness retrieved from SAR (Synthetic Aperture Radar) and TM thermal infrared image data. On the one hand, the SPM (Small Perturbation Model) was used as a theoretical SAR backscattering model to describe the relationship between the SAR backscattering coefficient and the earth's surface geometric roughness and its dielectric constant retrieved from the physical model between the soil thermal inertia and the soil surface moisture with the simultaneous TM thermal infrared image data and the ground microclimate data. On the basis of the SAR image matching with the TM image, the non-volume scattering surface geometric information was obtained from the SPM model at the TM image pixel scale, and the ground pixel surface's equivalent geometric roughness-height standard RMS (Root Mean Square) was achieved from the geometric information by the transformation of the typical topographic factors. The vegetation (wheat, tree) height retrieved from spectrum model was also transferred into its equivalent geometric roughness. A completely two-dimensional distribution map of the equivalent geometric roughness over the experimental area was produced by the data mosaic technique. On the other hand, according to the atmospheric eddy currents theory, the aerodynamic surface roughness was iterated out with the atmosphere stability correction method using the wind and the temperature profiles data measured at several typical fields such as bare soil field and vegetation field. After having analyzed the effect of surface equivalent geometric roughness together with dynamic and thermodynamic factors on the aerodynamic surface roughness within the working area, this paper first establishes a scale

  20. Assessment of radargrammetric DSMs from TerraSAR-X Stripmap images in a mountainous relief area of the Amazon region

    Science.gov (United States)

    de Oliveira, Cleber Gonzales; Paradella, Waldir Renato; da Silva, Arnaldo de Queiroz

    The Brazilian Amazon is a vast territory with an enormous need for mapping and monitoring of renewable and non-renewable resources. Due to the adverse environmental condition (rain, cloud, dense vegetation) and difficult access, topographic information is still poor, and when available needs to be updated or re-mapped. In this paper, the feasibility of using Digital Surface Models (DSMs) extracted from TerraSAR-X Stripmap stereo-pair images for detailed topographic mapping was investigated for a mountainous area in the Carajás Mineral Province, located on the easternmost border of the Brazilian Amazon. The quality of the radargrammetric DSMs was evaluated regarding field altimetric measurements. Precise topographic field information acquired from a Global Positioning System (GPS) was used as Ground Control Points (GCPs) for the modeling of the stereoscopic DSMs and as Independent Check Points (ICPs) for the calculation of elevation accuracies. The analysis was performed following two ways: (1) the use of Root Mean Square Error (RMSE) and (2) calculations of systematic error (bias) and precision. The test for significant systematic error was based on the Student's-t distribution and the test of precision was based on the Chi-squared distribution. The investigation has shown that the accuracy of the TerraSAR-X Stripmap DSMs met the requirements for 1:50,000 map (Class A) as requested by the Brazilian Standard for Cartographic Accuracy. Thus, the use of TerraSAR-X Stripmap images can be considered a promising alternative for detailed topographic mapping in similar environments of the Amazon region, where available topographic information is rare or presents low quality.

  1. Trends in medical image processing

    International Nuclear Information System (INIS)

    Robilotta, C.C.

    1987-01-01

    The function of medical image processing is analysed, mentioning the developments, the physical agents, and the main categories, as conection of distortion in image formation, detectability increase, parameters quantification, etc. (C.G.C.) [pt

  2. Methods of digital image processing

    International Nuclear Information System (INIS)

    Doeler, W.

    1985-01-01

    Increasing use of computerized methods for diagnostical imaging of radiological problems will open up a wide field of applications for digital image processing. The requirements set by routine diagnostics in medical radiology point to picture data storage and documentation and communication as the main points of interest for application of digital image processing. As to the purely radiological problems, the value of digital image processing is to be sought in the improved interpretability of the image information in those cases where the expert's experience and image interpretation by human visual capacities do not suffice. There are many other domains of imaging in medical physics where digital image processing and evaluation is very useful. The paper reviews the various methods available for a variety of problem solutions, and explains the hardware available for the tasks discussed. (orig.) [de

  3. Application of accident progression event tree technology to the Savannah River Site Defense Waste Processing Facility SAR analysis

    International Nuclear Information System (INIS)

    Brandyberry, M.D.; Baker, W.H.; Wittman, R.S.; Amos, C.N.

    1993-01-01

    The Accident Analysis in the Safety Analysis Report (SAR) for the Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) has recently undergone an upgrade. Non-reactor SARs at SRS (and other Department of Energy (DOE) sites) use probabilistic techniques to assess the frequency of accidents at their facilities. This paper describes the application of an extension of the Accident Progression Event Tree (APET) approach to accidents at the SRS DWPF. The APET technique allows an integrated model of the facility risk to be developed, where previous probabilistic accident analyses have been limited to the quantification of the frequency and consequences of individual accident scenarios treated independently. Use of an APET allows a more structured approach, incorporating both the treatment of initiators that are common to more than one accident, and of accident progression at the facility

  4. Integration of InSAR and GIS in the Study of Surface Faults Caused by Subsidence-Creep-Fault Processes in Celaya, Guanajuato, Mexico

    Science.gov (United States)

    Avila-Olivera, Jorge A.; Farina, Paolo; Garduño-Monroy, Victor H.

    2008-05-01

    In Celaya city, Subsidence-Creep-Fault Processes (SCFP) began to become visible at the beginning of the 1980s with the sprouting of the crackings that gave rise to the surface faults "Oriente" and "Poniente". At the present time, the city is being affected by five surface faults that display a preferential NNW-SSE direction, parallel to the regional faulting system "Taxco-San Miguel de Allende". In order to study the SCFP in the city, the first step was to obtain a map of surface faults, by integrating in a GIS field survey and an urban city plan. The following step was to create a map of the current phreatic level decline in city with the information of deep wells and using the "kriging" method in order to obtain a continuous surface. Finally the interferograms maps resulted of an InSAR analysis of 9 SAR images covering the time interval between July 12 of 2003 and May 27 of 2006 were integrated to a GIS. All the maps generated, show how the surface faults divide the city from North to South, in two zones that behave in a different way. The difference of the phreatic level decline between these two zones is 60 m; and the InSAR study revealed that the Western zone practically remains stable, while sinkings between the surface faults "Oriente" and "Universidad Pedagógica" are present, as well as in portions NE and SE of the city, all of these sinkings between 7 and 10 cm/year.

  5. SIMULATION-BASED EVALUATION OF LIGHT POSTS AND STREET SIGNS AS 3-D GEOLOCATION TARGETS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    S. Auer

    2017-05-01

    Full Text Available The assignment of phase center positions (in 2D or 3D derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR. For the first time, the appearance of the targets is analyzed in 2D (image plane and 3D space (world coordinates of scene model and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  6. Estimation of the Above Ground Biomass of Tropical Forests using Polarimetric and Tomographic SAR Data Acquired at P Band and 3-D Imaging Techniques

    Science.gov (United States)

    Ferro-Famil, L.; El Hajj Chehade, B.; Ho Tong Minh, D.; Tebaldini, S.; LE Toan, T.

    2016-12-01

    Developing and improving methods to monitor forest biomass in space and time is a timely challenge, especially for tropical forests, for which SAR imaging at larger wavelength presents an interesting potential. Nevertheless, directly estimating tropical forest biomass from classical 2-D SAR images may reveal a very complex and ill-conditioned problem, since a SAR echo is composed of numerous contributions, whose features and importance depend on many geophysical parameters, such has ground humidity, roughness, topography… that are not related to biomass. Recent studies showed that SAR modes of diversity, i.e. polarimetric intensity ratios or interferometric phase centers, do not fully resolve this under-determined problem, whereas Pol-InSAR tree height estimates may be related to biomass through allometric relationships, with, in general over tropical forests, significant levels of uncertainty and lack of robustness. In this context, 3-D imaging using SAR tomography represents an appealing solution at larger wavelengths, for which wave penetration properties ensures a high quality mapping of a tropical forest reflectivity in the vertical direction. This paper presents a series of studies led, in the frame of the preparation of the next ESA mission BIOMASS, on the estimation of biomass over a tropical forest in French Guiana, using Polarimetric SAR Tomographic (Pol-TomSAR) data acquired at P band by ONERA. It is then shown that Pol-TomoSAR significantly improves the retrieval of forest above ground biomass (AGB) in a high biomass forest (200 up to 500 t/ha), with an error of only 10% at 1.5-ha resolution using a reflectivity estimates sampled at a predetermined elevation. The robustness of this technique is tested by applying the same approach over another site, and results show a similar relationship between AGB and tomographic reflectivity over both sites. The excellent ability of Pol-TomSAR to retrieve both canopy top heights and ground topography with an error

  7. A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images

    Directory of Open Access Journals (Sweden)

    Anna Barra

    2017-09-01

    Full Text Available This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1 data and the DInSAR (Differential Interferometric Synthetic Aperture Radar technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago. The main obtained results are discussed.

  8. MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

    Directory of Open Access Journals (Sweden)

    R. Dwivedi

    2016-06-01

    Full Text Available In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS and Small Baseline (SB methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS based PS-InSAR and the Small Baselines Subset (SBAS techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.

  9. Lagrangian-based Backtracking of Oil Spill Dynamics from SAR Images: Application to Montara Case

    Science.gov (United States)

    Gautama, Budhi Gunadharma; Mercier, Gregoire; Fablet, Ronan; Longepe, Nicolas

    2016-08-01

    Within the framework of INDESO project (Infrastructure Development Space Oceanography), we address the issue of oilspill and aim at developing an operational SAR- based system for monitoring this issue in Indonesian waters from space. In this work, we focus on the backtrack- ing of an oilspill detected from SAR observations. As a case-study, we consider one large oil spill event that happened in Indonesian waters in 2009, referred to as the Montara oilspill. On 21 August 2009, the Montara Wellhead Platform had an uncontrolled release of hydrocarbons from one of the platform wells. It was estimated that 400 barrels (or approximately 64 tonnes) of crude oil were being lost per day. The uncontrolled release continued until 3 November 2009 and response operations continued until 3 December 2009. In this work, we develop a Langragian analysis and associated numerical inversion tools with a view to further analyzing the oil spread due to the Montara Wellhead Platform. Our model relies on a 2D Lagrangian transport model developed by CLS (Collecte Localisation Satellite). Our model involves four main parameters : the weights of wind- related and current-related advection, the origin and the duration of the oil leakage. Given SAR oilspill detections, we propose a numerical inversion of the parameters of the Lagrangian model, so that the simulated drift match the SAR observations of the oil spill. We demonstrate the relevance of the proposed model and numerical scheme for the Montara oilspill and further discuss their operational interest for the space-based oilspill backtracking and forecasting.

  10. A new scheme for urban impervious surface classification from SAR images

    Science.gov (United States)

    Zhang, Hongsheng; Lin, Hui; Wang, Yunpeng

    2018-05-01

    Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18.

  11. Imaging irregular magma reservoirs with InSAR and GPS observations: Application to Kilauea and Copahue volcanoes

    Science.gov (United States)

    Lundgren, P.; Camacho, A.; Poland, M. P.; Miklius, A.; Samsonov, S. V.; Milillo, P.

    2013-12-01

    The availability of synthetic aperture radar (SAR) interferometry (InSAR) data has increased our awareness of the complexity of volcano deformation sources. InSAR's spatial completeness helps identify or clarify source process mechanisms at volcanoes (i.e. Mt. Etna east flank motion; Lazufre crustal magma body; Kilauea dike complexity) and also improves potential model realism. In recent years, Bayesian inference methods have gained widespread use because of their ability to constrain not only source model parameters, but also their uncertainties. They are computationally intensive, however, which tends to limit them to a few geometrically rather simple source representations (for example, spheres). An alternative approach involves solving for irregular pressure and/or density sources from a three-dimensional (3-D) grid of source/density cells. This method has the ability to solve for arbitrarily shaped bodies of constant absolute pressure/density difference. We compare results for both Bayesian (a Markov chain Monte Carlo algorithm) and the irregular source methods for two volcanoes: Kilauea, Hawaii, and Copahue, Argentina-Chile border. Kilauea has extensive InSAR and GPS databases from which to explore the results for the irregular method with respect to the Bayesian approach, prior models, and an extensive set of ancillary data. One caveat, however, is the current restriction in the irregular model inversion to volume-pressure sources (and at a single excess pressure change), which limits its application in cases where sources such as faults or dikes are present. Preliminary results for Kilauea summit deflation during the March 2011 Kamoamoa eruption suggests a northeast-elongated magma body lying roughly 1-1.5 km below the surface. Copahue is a southern Andes volcano that has been inflating since early 2012, with intermittent summit eruptive activity since late 2012. We have an extensive InSAR time series from RADARSAT-2 and COSMO-SkyMed data, although both are

  12. Novel Polarimetric SAR Interferometry Algorithms, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Polarimetric radar interferometry (PolInSAR) is a new SAR imaging mode that is rapidly becoming an important technique for bare earth topographic mapping, tree...

  13. Playback system designed for X-Band SAR

    International Nuclear Information System (INIS)

    Yuquan, Liu; Changyong, Dou

    2014-01-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement

  14. Playback system designed for X-Band SAR

    Science.gov (United States)

    Yuquan, Liu; Changyong, Dou

    2014-03-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

  15. Hybrid Pluggable Processing Pipeline (HyP3): Programmatic Access to Cloud-Based Processing of SAR Data

    Science.gov (United States)

    Weeden, R.; Horn, W. B.; Dimarchi, H.; Arko, S. A.; Hogenson, K.

    2017-12-01

    A problem often faced by Earth science researchers is the question of how to scale algorithms that were developed against few datasets and take them to regional or global scales. This problem only gets worse as we look to a future with larger and larger datasets becoming available. One significant hurdle can be having the processing and storage resources available for such a task, not to mention the administration of those resources. As a processing environment, the cloud offers nearly unlimited potential for compute and storage, with limited administration required. The goal of the Hybrid Pluggable Processing Pipeline (HyP3) project was to demonstrate the utility of the Amazon cloud to process large amounts of data quickly and cost effectively. Principally built by three undergraduate students at the ASF DAAC, the HyP3 system relies on core Amazon cloud services such as Lambda, Relational Database Service (RDS), Elastic Compute Cloud (EC2), Simple Storage Service (S3), and Elastic Beanstalk. HyP3 provides an Application Programming Interface (API) through which users can programmatically interface with the HyP3 system; allowing them to monitor and control processing jobs running in HyP3, and retrieve the generated HyP3 products when completed. This presentation will focus on the development techniques and enabling technologies that were used in developing the HyP3 system. Data and process flow, from new subscription through to order completion will be shown, highlighting the benefits of the cloud for each step. Because the HyP3 system can be accessed directly from a user's Python scripts, powerful applications leveraging SAR products can be put together fairly easily. This is the true power of HyP3; allowing people to programmatically leverage the power of the cloud.

  16. Assessing ScanSAR Interferometry for Deformation Studies

    Science.gov (United States)

    Buckley, S. M.; Gudipati, K.

    2007-12-01

    There is a trend in civil satellite SAR mission design to implement an imaging strategy that incorporates both stripmap mode and ScanSAR imaging. This represents a compromise between high resolution data collection and a desire for greater spatial coverage and more frequent revisit times. However, mixed mode imaging can greatly reduce the number of stripmap images available for measuring subtle ground deformation. Although ScanSAR-ScanSAR and ScanSAR-stripmap repeat-pass interferometry have been demonstrated, these approaches are infrequently used for single interferogram formation and nonexistent for InSAR time series analysis. For future mission design, e.g., a dedicated US InSAR mission, the effect of various ScanSAR system parameter choices on InSAR time series analysis also remains unexplored. Our objective is to determine the utility of ScanSAR differential interferometry. We will demonstrate the use of ScanSAR interferograms for several previous deformation studies: localized and broad-scale urban land subsidence, tunneling, volcanic surface movements and several examples associated with the seismic cycle. We also investigate the effect of various ScanSAR burst synchronization levels on our ability to detect and make quality measurements of deformation. To avoid the issues associated with Envisat ScanSAR burst alignment and to exploit a decade of InSAR measurements, we simulate ScanSAR data by bursting (throwing away range lines of) ERS-1/2 data. All the burst mode datasets are processed using a Modified SPECAN algorithm. To investigate the effects of burst misalignment, a number of cases with varying degrees of burst overlap are considered. In particular, we look at phase decorrelation as a function of percentage of burst overlap. Coherence clearly reduces as the percentage of overlap decreases and we find a useful threshold of 40-70% burst overlap depending on the study site. In order to get a more generalized understanding for different surface conditions

  17. Industrial Applications of Image Processing

    Science.gov (United States)

    Ciora, Radu Adrian; Simion, Carmen Mihaela

    2014-11-01

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

  18. [Imaging center - optimization of the imaging process].

    Science.gov (United States)

    Busch, H-P

    2013-04-01

    Hospitals around the world are under increasing pressure to optimize the economic efficiency of treatment processes. Imaging is responsible for a great part of the success but also of the costs of treatment. In routine work an excessive supply of imaging methods leads to an "as well as" strategy up to the limit of the capacity without critical reflection. Exams that have no predictable influence on the clinical outcome are an unjustified burden for the patient. They are useless and threaten the financial situation and existence of the hospital. In recent years the focus of process optimization was exclusively on the quality and efficiency of performed single examinations. In the future critical discussion of the effectiveness of single exams in relation to the clinical outcome will be more important. Unnecessary exams can be avoided, only if in addition to the optimization of single exams (efficiency) there is an optimization strategy for the total imaging process (efficiency and effectiveness). This requires a new definition of processes (Imaging Pathway), new structures for organization (Imaging Center) and a new kind of thinking on the part of the medical staff. Motivation has to be changed from gratification of performed exams to gratification of process quality (medical quality, service quality, economics), including the avoidance of additional (unnecessary) exams. © Georg Thieme Verlag KG Stuttgart · New York.

  19. Building country image process

    Directory of Open Access Journals (Sweden)

    Zubović Jovan

    2005-01-01

    Full Text Available The same branding principles are used for countries as they are used for the products, only the methods are different. Countries are competing among themselves in tourism, foreign investments and exports. Country turnover is at the level that the country's reputation is. The countries that begin as unknown or with a bad image will have limits in operations or they will be marginalized. As a result they will be at the bottom of the international influence scale. On the other hand, countries with a good image, like Germany (despite two world wars will have their products covered with a special "aura".

  20. Digital Data Processing of Images

    African Journals Online (AJOL)

    Digital data processing was investigated to perform image processing. Image smoothing and restoration were explored and promising results obtained. The use of the computer, not only as a data management device, but as an important tool to render quantitative information, was illustrated by lung function determination.

  1. Semi-automated procedures for shoreline extraction using single RADARSAT-1 SAR image

    Science.gov (United States)

    Al Fugura, A.'kif; Billa, Lawal; Pradhan, Biswajeet

    2011-12-01

    Coastline identification is important for surveying and mapping reasons. Coastline serves as the basic point of reference and is used on nautical charts for navigation purposes. Its delineation has become crucial and more important in the wake of the many recent earthquakes and tsunamis resulting in complete change and redraw of some shorelines. In a tropical country like Malaysia, presence of cloud cover hinders the application of optical remote sensing data. In this study a semi-automated technique and procedures are presented for shoreline delineation from RADARSAT-1 image. A scene of RADARSAT-1 satellite image was processed using enhanced filtering technique to identify and extract the shoreline coast of Kuala Terengganu, Malaysia. RADSARSAT image has many advantages over the optical data because of its ability to penetrate cloud cover and its night sensing capabilities. At first, speckles were removed from the image by using Lee sigma filter which was used to reduce random noise and to enhance the image and discriminate the boundary between land and water. The results showed an accurate and improved extraction and delineation of the entire coastline of Kuala Terrenganu. The study demonstrated the reliability of the image averaging filter in reducing random noise over the sea surface especially near the shoreline. It enhanced land-water boundary differentiation, enabling better delineation of the shoreline. Overall, the developed techniques showed the potential of radar imagery for accurate shoreline mapping and will be useful for monitoring shoreline changes during high and low tides as well as shoreline erosion in a tropical country like Malaysia.

  2. Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

    KAUST Repository

    Feng, Guangcai; Jonsson, Sigurjon; Klinger, Yann

    2017-01-01

    The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

  3. Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

    KAUST Repository

    Feng, Guangcai

    2017-03-15

    The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

  4. 基于MRF的多时相SAR影像非监督变化检测%Unsupervised Change Detection in Multitemporal SAR Images Using MRF Models

    Institute of Scientific and Technical Information of China (English)

    江利明; 廖明生; 张路; 林珲

    2007-01-01

    An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.

  5. Microprocessor based image processing system

    International Nuclear Information System (INIS)

    Mirza, M.I.; Siddiqui, M.N.; Rangoonwala, A.

    1987-01-01

    Rapid developments in the production of integrated circuits and introduction of sophisticated 8,16 and now 32 bit microprocessor based computers, have set new trends in computer applications. Nowadays the users by investing much less money can make optimal use of smaller systems by getting them custom-tailored according to their requirements. During the past decade there have been great advancements in the field of computer Graphics and consequently, 'Image Processing' has emerged as a separate independent field. Image Processing is being used in a number of disciplines. In the Medical Sciences, it is used to construct pseudo color images from computer aided tomography (CAT) or positron emission tomography (PET) scanners. Art, advertising and publishing people use pseudo colours in pursuit of more effective graphics. Structural engineers use Image Processing to examine weld X-rays to search for imperfections. Photographers use Image Processing for various enhancements which are difficult to achieve in a conventional dark room. (author)

  6. METH-33 - Performance assessment for the high resolution and wide swath (HRWS) post-Sentinel-1 SAR system

    DEFF Research Database (Denmark)

    Zonno, Mariantonietta; Maria J., Sanjuan-Ferrer,; Lopez-Dekker, Paco

    The next generation, post-Sentinel-1, ESA’s C-band synthetic aperture radar (SAR) system is conceived to provide simultaneously high azimuth resolution and wide swath width (HRWS).There are different ways in which the imaging capabilities of the HRWS SAR system can be exploited, which translate...... or numerical models and, if these are not available, real SAR images as well as numerical algorithms and some explicit simulations of the data and of the inversion process are employed. The tool uses as input the HRWS SAR instrument performance for the different applicable modes and produces as output results...

  7. The study of molybdenite types related to the ore processing plant of the Sar Cheshmeh mine

    OpenAIRE

    Balandeh Aminzadeh; Jamshid Shahabpour; Mortaza Asadipour

    2010-01-01

    Molybdenite occurs in five forms in the Sar Cheshmeh porphyry copper deposit, namely, (1)-veinlets with quartz-molybdenite, (2)-veinlets with quartz-molydenite that were filled with pyrite, (3)-veinlets with quartz-molybdenite-pyrite–chalcopyrite, (4)-Molybdenite veinlets with very low quartz and (5)-disseminated molybdenite grains. Because of their large size, the veinlet-related molybdenite grains are easily liberated from the gangue minerals, provided the grinding is properly conducted (74...

  8. SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

    2010-05-22

    This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

  9. SARS - Diagnosis

    Indian Academy of Sciences (India)

    SARS - Diagnosis. Mainly by exclusion of known causes of atypical pneumonia; * X ray Chest; * PCR on body fluids- primers defined by WHO centres available from website.-ve result does not exclude SARS. * Sequencing of amplicons; * Viral Cultures – demanding; * Antibody tests.

  10. Imaging Formation Algorithm of the Ground and Space-Borne Hybrid BiSAR Based on Parameters Estimation from Direct Signal

    Directory of Open Access Journals (Sweden)

    Qingjun Zhang

    2014-01-01

    Full Text Available This paper proposes a novel image formation algorithm for the bistatic synthetic aperture radar (BiSAR with the configuration of a noncooperative transmitter and a stationary receiver in which the traditional imaging algorithm failed because the necessary imaging parameters cannot be estimated from the limited information from the noncooperative data provider. In the new algorithm, the essential parameters for imaging, such as squint angle, Doppler centroid, and Doppler chirp-rate, will be estimated by full exploration of the recorded direct signal (direct signal is the echo from satellite to stationary receiver directly from the transmitter. The Doppler chirp-rate is retrieved by modeling the peak phase of direct signal as a quadratic polynomial. The Doppler centroid frequency and the squint angle can be derived from the image contrast optimization. Then the range focusing, the range cell migration correction (RCMC, and the azimuth focusing are implemented by secondary range compression (SRC and the range cell migration, respectively. At last, the proposed algorithm is validated by imaging of the BiSAR experiment configured with china YAOGAN 10 SAR as the transmitter and the receiver platform located on a building at a height of 109 m in Jiangsu province. The experiment image with geometric correction shows good accordance with local Google images.

  11. AUTOMATION OF IMAGE DATA PROCESSING

    Directory of Open Access Journals (Sweden)

    Preuss Ryszard

    2014-12-01

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

  12. TECHNOLOGIES OF BRAIN IMAGES PROCESSING

    Directory of Open Access Journals (Sweden)

    O.M. Klyuchko

    2017-12-01

    Full Text Available The purpose of present research was to analyze modern methods of processing biological images implemented before storage in databases for biotechnological purposes. The databases further were incorporated into web-based digital systems. Examples of such information systems were described in the work for two levels of biological material organization; databases for storing data of histological analysis and of whole brain were described. Methods of neuroimaging processing for electronic brain atlas were considered. It was shown that certain pathological features can be revealed in histological image processing. Several medical diagnostic techniques (for certain brain pathologies, etc. as well as a few biotechnological methods are based on such effects. Algorithms of image processing were suggested. Electronic brain atlas was conveniently for professionals in different fields described in details. Approaches of brain atlas elaboration, “composite” scheme for large deformations as well as several methods of mathematic images processing were described as well.

  13. Image Processing: Some Challenging Problems

    Science.gov (United States)

    Huang, T. S.; Aizawa, K.

    1993-11-01

    Image processing can be broadly defined as the manipulation of signals which are inherently multidimensional. The most common such signals are photographs and video sequences. The goals of processing or manipulation can be (i) compression for storage or transmission; (ii) enhancement or restoration; (iii) analysis, recognition, and understanding; or (iv) visualization for human observers. The use of image processing techniques has become almost ubiquitous; they find applications in such diverse areas as astronomy, archaeology, medicine, video communication, and electronic games. Nonetheless, many important problems in image processing remain unsolved. It is the goal of this paper to discuss some of these challenging problems. In Section I, we mention a number of outstanding problems. Then, in the remainder of this paper, we concentrate on one of them: very-low-bit-rate video compression. This is chosen because it involves almost all aspects of image processing.

  14. Bistatic SAR/ISAR/FSR geometry, signal models and imaging algorithms

    CERN Document Server

    Lazarov, Andon Dimitrov

    2013-01-01

    Bistatic radar consists of a radar system which comprises a transmitter and receiver which are separated by a distance comparable to the expected target distance. This book provides a general theoretical description of such bistatic technology in the context of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation as well as processing theory. Signal formation and image reconstruction algorithms are developed with the application of high informative linear frequency and phase code modulating techniques

  15. Biomedical signal and image processing

    CERN Document Server

    Najarian, Kayvan

    2012-01-01

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

  16. Image restoration and processing methods

    International Nuclear Information System (INIS)

    Daniell, G.J.

    1984-01-01

    This review will stress the importance of using image restoration techniques that deal with incomplete, inconsistent, and noisy data and do not introduce spurious features into the processed image. No single image is equally suitable for both the resolution of detail and the accurate measurement of intensities. A good general purpose technique is the maximum entropy method and the basis and use of this will be explained. (orig.)

  17. Image processing in medical ultrasound

    DEFF Research Database (Denmark)

    Hemmsen, Martin Christian

    This Ph.D project addresses image processing in medical ultrasound and seeks to achieve two major scientific goals: First to develop an understanding of the most significant factors influencing image quality in medical ultrasound, and secondly to use this knowledge to develop image processing...... multiple imaging setups. This makes the system well suited for development of new processing methods and for clinical evaluations, where acquisition of the exact same scan location for multiple methods is important. The second project addressed implementation, development and evaluation of SASB using...... methods for enhancing the diagnostic value of medical ultrasound. The project is an industrial Ph.D project co-sponsored by BK Medical ApS., with the commercial goal to improve the image quality of BK Medicals scanners. Currently BK Medical employ a simple conventional delay-and-sum beamformer to generate...

  18. Invitation to medical image processing

    International Nuclear Information System (INIS)

    Kitasaka, Takayuki; Suenaga, Yasuhito; Mori, Kensaku

    2010-01-01

    This medical essay explains the present state of CT image processing technology about its recognition, acquisition and visualization for computer-assisted diagnosis (CAD) and surgery (CAS), and future view. Medical image processing has a series of history of its original start from the discovery of X-ray to its application to diagnostic radiography, its combination with the computer for CT, multi-detector raw CT, leading to 3D/4D images for CAD and CAS. CAD is performed based on the recognition of normal anatomical structure of human body, detection of possible abnormal lesion and visualization of its numerical figure into image. Actual instances of CAD images are presented here for chest (lung cancer), abdomen (colorectal cancer) and future body atlas (models of organs and diseases for imaging), a recent national project: computer anatomy. CAS involves the surgical planning technology based on 3D images, navigation of the actual procedure and of endoscopy. As guidance to beginning technological image processing, described are the national and international community like related academic societies, regularly conducting congresses, textbooks and workshops, and topics in the field like computed anatomy of an individual patient for CAD and CAS, its data security and standardization. In future, protective medicine is in authors' view based on the imaging technology, e.g., daily life CAD of individuals ultimately, as exemplified in the present body thermometer and home sphygmometer, to monitor one's routine physical conditions. (T.T.)

  19. Sentinel-1 data massive processing for large scale DInSAR analyses within Cloud Computing environments through the P-SBAS approach

    Science.gov (United States)

    Lanari, Riccardo; Bonano, Manuela; Buonanno, Sabatino; Casu, Francesco; De Luca, Claudio; Fusco, Adele; Manunta, Michele; Manzo, Mariarosaria; Pepe, Antonio; Zinno, Ivana

    2017-04-01

    The SENTINEL-1 (S1) mission is designed to provide operational capability for continuous mapping of the Earth thanks to its two polar-orbiting satellites (SENTINEL-1A and B) performing C-band synthetic aperture radar (SAR) imaging. It is, indeed, characterized by enhanced revisit frequency, coverage and reliability for operational services and applications requiring long SAR data time series. Moreover, SENTINEL-1 is specifically oriented to interferometry applications with stringent requirements based on attitude and orbit accuracy and it is intrinsically characterized by small spatial and temporal baselines. Consequently, SENTINEL-1 data are particularly suitable to be exploited through advanced interferometric techniques such as the well-known DInSAR algorithm referred to as Small BAseline Subset (SBAS), which allows the generation of deformation time series and displacement velocity maps. In this work we present an advanced interferometric processing chain, based on the Parallel SBAS (P-SBAS) approach, for the massive processing of S1 Interferometric Wide Swath (IWS) data aimed at generating deformation time series in efficient, automatic and systematic way. Such a DInSAR chain is designed to exploit distributed computing infrastructures, and more specifically Cloud Computing environments, to properly deal with the storage and the processing of huge S1 datasets. In particular, since S1 IWS data are acquired with the innovative Terrain Observation with Progressive Scans (TOPS) mode, we could benefit from the structure of S1 data, which are composed by bursts that can be considered as separate acquisitions. Indeed, the processing is intrinsically parallelizable with respect to such independent input data and therefore we basically exploited this coarse granularity parallelization strategy in the majority of the steps of the SBAS processing chain. Moreover, we also implemented more sophisticated parallelization approaches, exploiting both multi-node and multi

  20. Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

    Science.gov (United States)

    Changyong, Dou; Huadong, Guo; Chunming, Han; yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

    2014-03-01

    Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc.

  1. Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

    International Nuclear Information System (INIS)

    Changyong, Dou; Huadong, Guo; Chunming, Han; Yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

    2014-01-01

    Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc

  2. Evaluation of Polarimetric SAR Decomposition for Classifying Wetland Vegetation Types

    Directory of Open Access Journals (Sweden)

    Sang-Hoon Hong

    2015-07-01

    Full Text Available The Florida Everglades is the largest subtropical wetland system in the United States and, as with subtropical and tropical wetlands elsewhere, has been threatened by severe environmental stresses. It is very important to monitor such wetlands to inform management on the status of these fragile ecosystems. This study aims to examine the applicability of TerraSAR-X quadruple polarimetric (quad-pol synthetic aperture radar (PolSAR data for classifying wetland vegetation in the Everglades. We processed quad-pol data using the Hong & Wdowinski four-component decomposition, which accounts for double bounce scattering in the cross-polarization signal. The calculated decomposition images consist of four scattering mechanisms (single, co- and cross-pol double, and volume scattering. We applied an object-oriented image analysis approach to classify vegetation types with the decomposition results. We also used a high-resolution multispectral optical RapidEye image to compare statistics and classification results with Synthetic Aperture Radar (SAR observations. The calculated classification accuracy was higher than 85%, suggesting that the TerraSAR-X quad-pol SAR signal had a high potential for distinguishing different vegetation types. Scattering components from SAR acquisition were particularly advantageous for classifying mangroves along tidal channels. We conclude that the typical scattering behaviors from model-based decomposition are useful for discriminating among different wetland vegetation types.

  3. Large scale rock slope release planes imaged by differential ground based InSAR at Randa, Switzerland

    Science.gov (United States)

    Gischig, V.; Loew, S.; Kos, A.; Raetzo, H.

    2009-04-01

    In April and May of 1991 a steep rock slope above the village of Randa (Valais, Switzerland) failed in two events, releasing a total rock volume of 30 million m3. The rock mass behind the back scarp contains several million cubic meters of unstable gneisses and schists which are moving with a maximum rate of about 2 cm/yr. Different geodetic, geotechnical and geophysical techniques were applied to monitor this new instability and to determine its spatial extent. However, the boundaries of the instability could only be roughly estimated so far. For this reason five ground based differential InSAR surveys (GB-DInSAR) were carried out between 2005 and 2007 from the opposite valley flank at a distance to target of 1.3 to 1.9 km. These surveys provide displacements maps of four different time intervals with a spatial resolution of 2 to 6 m and an accuracy of less than 1 mm. These datasets reveal interesting new insights into the spatial distribution of displacements and significantly contribute to the kinematic interpretation of the ongoing movements. We found that the lower boundary of the instability is a narrow rupture plane which coincides with a primary lithological boundary on the slope. The intersection line between this basal rupture plane and the steep rock cliff extents over at least 200 m meters. It is possible to identify this structure on helicopter-based high resolution images and a LiDAR DTM of the failure surface. The eastern boundary of the instability also presents itself as a sharp line separating stable bedrock from a strongly fractured rock mass moving about 1 cm/yr along the line of sight. This lateral release plane is formed by a steeply east dipping tectonic fault plane, with subhorizontal striations and an exposed surface area of about 10'000 square meters. In the north-east of the instability the lateral boundaries crop out on surfaces that have an acute angle to the line of sight or lie in the shadow of the radar. Here the boundaries of the

  4. SAR matrices: automated extraction of information-rich SAR tables from large compound data sets.

    Science.gov (United States)

    Wassermann, Anne Mai; Haebel, Peter; Weskamp, Nils; Bajorath, Jürgen

    2012-07-23

    We introduce the SAR matrix data structure that is designed to elucidate SAR patterns produced by groups of structurally related active compounds, which are extracted from large data sets. SAR matrices are systematically generated and sorted on the basis of SAR information content. Matrix generation is computationally efficient and enables processing of large compound sets. The matrix format is reminiscent of SAR tables, and SAR patterns revealed by different categories of matrices are easily interpretable. The structural organization underlying matrix formation is more flexible than standard R-group decomposition schemes. Hence, the resulting matrices capture SAR information in a comprehensive manner.

  5. Advanced radar-interpretation of InSAR time series for mapping and characterization of geological processes

    Directory of Open Access Journals (Sweden)

    F. Cigna

    2011-03-01

    Full Text Available We present a new post-processing methodology for the analysis of InSAR (Synthetic Aperture Radar Interferometry multi-temporal measures, based on the temporal under-sampling of displacement time series, the identification of potential changes occurring during the monitoring period and, eventually, the classification of different deformation behaviours. The potentials of this approach for the analysis of geological processes were tested on the case study of Naro (Italy, specifically selected due to its geological setting and related ground instability of unknown causes that occurred in February 2005. The time series analysis of past (ERS1/2 descending data; 1992–2000 and current (RADARSAT-1 ascending data; 2003–2007 ground movements highlighted significant displacement rates (up to 6 mm yr−1 in 2003–2007, followed by a post-event stabilization. The deformational behaviours of instable areas involved in the 2005 event were also detected, clarifying typology and kinematics of ground instability. The urban sectors affected and unaffected by the event were finally mapped, consequently re-defining and enlarging the influenced area previously detected by field observations. Through the integration of InSAR data and conventional field surveys (i.e. geological, geomorphologic and geostructural campaigns, the causes of instability were finally attributed to tectonics.

  6. DARK SPOT DETECTION USING INTENSITY AND THE DEGREE OF POLARIZATION IN FULLY POLARIMETRIC SAR IMAGES FOR OIL POLUTION MONITORING

    Directory of Open Access Journals (Sweden)

    F. Zakeri

    2015-12-01

    Full Text Available Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE 65%, Overall Accuracy 20% and correlation 40% are improved.

  7. Dark SPOT Detection Using Intensity and the Degree of Polarization in Fully Polarimetric SAR Images for Oil Polution Monitoring

    Science.gov (United States)

    Zakeri, F.; Amini, J.

    2015-12-01

    Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR) has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP) is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE) 65%, Overall Accuracy 20% and correlation 40% are improved.

  8. Improved techniques to utilize remotely sensed data from multi-frequency imaging radar polarimeter; Tashuha tahenha SAR data no riyoho no kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Okada, K [Sumitomo Metal Mining Co. Ltd., Osaka (Japan); Maruyama, Y [Earth Remote Sensing Data Analysis Center, Tokyo (Japan); Tapley, I

    1997-05-27

    It was intended to serve for establishing specifications for a next generation SAR such as PALSAR through studying methods for evaluating and utilizing the multi-frequency, multi-polarized wave SAR data. Placing an emphasis on utilization of the NASA`s AIRSAR, identification was made on backscatter amount recorded on the SAR data, terrestrial constitutional substances, patterns of the ground surface, micro-topography and such terrestrial conditions as vegetation and land utilization. Their mutual relationships were also analyzed. A noise reduction method usable on multi-band data can be applied to the AIRSAR data, and can reduce noise effectively. Images with more volume of information can be acquired from multi-band images with the same polarization wave than from multi-polarization wave images with the same band. As a result of estimating terrestrial permitivity by using the method invented by Dubois and van Zyl, most of the subject area is judged to have terrestrial substances dried at the time of having acquired the images. A colluvium rich with exposed rock regions and gravels was identified as an area having higher permitivity than the former area. Images of terrestrial roughness were divided largely into smooth flat lands, sand and gravel distributed regions, exposed rock regions, and plant distributed regions along river basins. 3 refs., 2 figs., 1 tab.

  9. Feature-Based Nonlocal Polarimetric SAR Filtering

    Directory of Open Access Journals (Sweden)

    Xiaoli Xing

    2017-10-01

    Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

  10. Differential morphology and image processing.

    Science.gov (United States)

    Maragos, P

    1996-01-01

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

  11. Computational Intelligence in Image Processing

    CERN Document Server

    Siarry, Patrick

    2013-01-01

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

  12. Detecting and monitoring UCG subsidence with InSAR

    Energy Technology Data Exchange (ETDEWEB)

    Mellors, R J; Foxall, W; Yang, X

    2012-03-23

    The use of interferometric synthetic aperture radar (InSAR) to measure surface subsidence caused by Underground Coal Gasification (UCG) is tested. InSAR is a remote sensing technique that uses Synthetic Aperture Radar images to make spatial images of surface deformation and may be deployed from satellite or an airplane. With current commercial satellite data, the technique works best in areas with little vegetation or farming activity. UCG subsidence is generally caused by roof collapse, which adversely affects UCG operations due to gas loss and is therefore important to monitor. Previous studies have demonstrated the usefulness of InSAR in measuring surface subsidence related to coal mining and surface deformation caused by a coal mining roof collapse in Crandall Canyon, Utah is imaged as a proof-of-concept. InSAR data is collected and processed over three known UCG operations including two pilot plants (Majuba, South Africa and Wulanchabu, China) and an operational plant (Angren, Uzbekistan). A clear f eature showing approximately 7 cm of subsidence is observed in the UCG field in Angren. Subsidence is not observed in the other two areas, which produce from deeper coal seams and processed a smaller volume. The results show that in some cases, InSAR is a useful tool to image UCG related subsidence. Data from newer satellites and improved algorithms will improve effectiveness.

  13. Digital processing of radiographic images

    Science.gov (United States)

    Bond, A. D.; Ramapriyan, H. K.

    1973-01-01

    Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

  14. Crack detection using image processing

    International Nuclear Information System (INIS)

    Moustafa, M.A.A

    2010-01-01

    This thesis contains five main subjects in eight chapters and two appendices. The first subject discus Wiener filter for filtering images. In the second subject, we examine using different methods, as Steepest Descent Algorithm (SDA) and the Wavelet Transformation, to detect and filling the cracks, and it's applications in different areas as Nano technology and Bio-technology. In third subject, we attempt to find 3-D images from 1-D or 2-D images using texture mapping with Open Gl under Visual C ++ language programming. The fourth subject consists of the process of using the image warping methods for finding the depth of 2-D images using affine transformation, bilinear transformation, projective mapping, Mosaic warping and similarity transformation. More details about this subject will be discussed below. The fifth subject, the Bezier curves and surface, will be discussed in details. The methods for creating Bezier curves and surface with unknown distribution, using only control points. At the end of our discussion we will obtain the solid form, using the so called NURBS (Non-Uniform Rational B-Spline); which depends on: the degree of freedom, control points, knots, and an evaluation rule; and is defined as a mathematical representation of 3-D geometry that can accurately describe any shape from a simple 2-D line, circle, arc, or curve to the most complex 3-D organic free-form surface or (solid) which depends on finding the Bezier curve and creating family of curves (surface), then filling in between to obtain the solid form. Another representation for this subject is concerned with building 3D geometric models from physical objects using image-based techniques. The advantage of image techniques is that they require no expensive equipment; we use NURBS, subdivision surface and mesh for finding the depth of any image with one still view or 2D image. The quality of filtering depends on the way the data is incorporated into the model. The data should be treated with

  15. SAR target recognition using behaviour library of different shapes in different incidence angles and polarisations

    Science.gov (United States)

    Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas

    2018-05-01

    Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.

  16. FITS Liberator: Image processing software

    Science.gov (United States)

    Lindberg Christensen, Lars; Nielsen, Lars Holm; Nielsen, Kaspar K.; Johansen, Teis; Hurt, Robert; de Martin, David

    2012-06-01

    The ESA/ESO/NASA FITS Liberator makes it possible to process and edit astronomical science data in the FITS format to produce stunning images of the universe. Formerly a plugin for Adobe Photoshop, the current version of FITS Liberator is a stand-alone application and no longer requires Photoshop. This image processing software makes it possible to create color images using raw observations from a range of telescopes; the FITS Liberator continues to support the FITS and PDS formats, preferred by astronomers and planetary scientists respectively, which enables data to be processed from a wide range of telescopes and planetary probes, including ESO's Very Large Telescope, the NASA/ESA Hubble Space Telescope, NASA's Spitzer Space Telescope, ESA's XMM-Newton Telescope and Cassini-Huygens or Mars Reconnaissance Orbiter.

  17. Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

    Science.gov (United States)

    LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

  18. Landslide precursory deformation interpretation using ALOS-2/PALSAR-2 InSAR image along Min River in Maoxien, Sichuan Province, China

    Science.gov (United States)

    Sato, H. P.

    2017-12-01

    Maoxien area in Sichuan Province, China has many landslide. For example, landslide (rock avalanche) occurred on the slope in Xinmocun Village in Maoxeien on 24 June 2017. I produced and interpreetd InSAR image using ALOS/PALSAR data observed on 19 Jul 2007-3 Sep 2007 and on 27 Jan 2011-14 Mar 2011, and ALOS-2/PALSAR-2 data observed on 26 Jul 2015-13 Dec 2015 and on 13 Dec 2015-11 Dec 2016. These images give good coherence and it was easy to identify local landslide surface deformation. As a result, e.g., two slopes were estimated to have local landslide surface deformation; one is at 103.936587 deg E and 32.04462 deg N, another is at 103.674754 deg E and 31.852838 N. However, the slope in Xinmocun Village was not identified as landslide precursory deformation. In the poster I will present more InSAR image observed after 11 Dec 2016 and discuss the possibility of local landslide surface deformaton using InSAR image. ALOS/PALSAR and ALOS-2/PALSAR-2 data were provided by JAXA through Landslide Working Group in JAXA and through Special Research 2015-B-02 of Earthquake Research Institute/Tokyo University. This study was supported by KAKENHI (17H02973).

  19. Estimation of Bridge Height over Water from Polarimetric SAR Image Data Using Mapping and Projection Algorithm and De-Orientation Theory

    Science.gov (United States)

    Wang, Haipeng; Xu, Feng; Jin, Ya-Qiu; Ouchi, Kazuo

    An inversion method of bridge height over water by polarimetric synthetic aperture radar (SAR) is developed. A geometric ray description to illustrate scattering mechanism of a bridge over water surface is identified by polarimetric image analysis. Using the mapping and projecting algorithm, a polarimetric SAR image of a bridge model is first simulated and shows that scattering from a bridge over water can be identified by three strip lines corresponding to single-, double-, and triple-order scattering, respectively. A set of polarimetric parameters based on the de-orientation theory is applied to analysis of three types scattering, and the thinning-clustering algorithm and Hough transform are then employed to locate the image positions of these strip lines. These lines are used to invert the bridge height. Fully polarimetric image data of airborne Pi-SAR at X-band are applied to inversion of the height and width of the Naruto Bridge in Japan. Based on the same principle, this approach is also applicable to spaceborne ALOSPALSAR single-polarization data of the Eastern Ocean Bridge in China. The results show good feasibility to realize the bridge height inversion.

  20. The InSAeS4 Airborne X-Band Interferometric SAR System: A First Assessment on Its Imaging and Topographic Mapping Capabilities

    Directory of Open Access Journals (Sweden)

    Stefano Perna

    2016-01-01

    Full Text Available We present in this work a first assessment of the imaging and topographic mapping capabilities of the InSAeS4 system, which is a single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR. In particular, we first provide a brief description of the InSAeS4 sensor. Then, we discuss the results of our analysis on the SAR and interferometric SAR products relevant to the first flight-test campaign. More specifically, we have exploited as reference the GPS measurements relevant to nine Corner Reflectors (CRs deployed over the illuminated area during the campaign and a laser scanner Digital Elevation Model (DEM. From the analysis carried out on the CRs we achieved a mean geometric resolution, for the SAR products, of about 0.14 m in azimuth and 0.49 m in range, a positioning misalignment with standard deviation of 0.07 m in range and 0.08 m in azimuth, and a height error with standard deviation of 0.51 m. From the comparison with the laser scanner DEM we estimated a height error with standard deviation of 1.57 m.

  1. Multimedia image and video processing

    CERN Document Server

    Guan, Ling

    2012-01-01

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

  2. Linear Algebra and Image Processing

    Science.gov (United States)

    Allali, Mohamed

    2010-01-01

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

  3. Mathematical problems in image processing

    International Nuclear Information System (INIS)

    Chidume, C.E.

    2000-01-01

    This is the second volume of a new series of lecture notes of the Abdus Salam International Centre for Theoretical Physics. This volume contains the lecture notes given by A. Chambolle during the School on Mathematical Problems in Image Processing. The school consisted of two weeks of lecture courses and one week of conference

  4. Motion-compensated processing of image signals

    NARCIS (Netherlands)

    2010-01-01

    In a motion-compensated processing of images, input images are down-scaled (scl) to obtain down-scaled images, the down-scaled images are subjected to motion- compensated processing (ME UPC) to obtain motion-compensated images, the motion- compensated images are up-scaled (sc2) to obtain up-scaled

  5. CryoSat Processing Prototype, how to generate LRM like echoes with SAR data and a Comparison to DUACS SLA over high latitudes

    Science.gov (United States)

    Picot, N.; Boy, F.; Desjonqueres, J.

    2012-12-01

    Like CryoSat, Sentinel3 embarks a doppler altimeter. While there is a long experience of LRM processing, SAR nadir looking data are new and will need in depth validation. Thanks to CryoSat data, the processing of SAR data can be experienced in orbit. The continuity to current altimeter data set (based on LRM acquisitions) has also to be analysed with details. A Cryosat Processing Prototype (C2P) has been developed on CNES side to prepare the CNES SAR ocean retracking study. this prototype allows to process SAR data in order to generate LRM like echoes on ground. Those CryoSat ocean products are routinely processed on CNES side and ingested in the SALP/DUACS system. CryoSat data have proved to be very accurate and very valuable for the ocean user community in the past monthes. For example, it has allowed to largely reduce the impact of the lost of the ESA ENVISAT mission as well as the long non availability of Jason-1 data. This paper will describe the system set up in place early 2012 to feed CryoSat data in the SALP/DUACS products and will present the routine data analysis . C2P CryoSat products will be compared with DUACS SLA estimates and a specific focus will be given over high latitudes knowing that CryoSat is the oinly mission providing sea surface estimates over latitudes above 66 degrees since the lost of the ESA ENVISAT mission.

  6. Musashi dynamic image processing system

    International Nuclear Information System (INIS)

    Murata, Yutaka; Mochiki, Koh-ichi; Taguchi, Akira

    1992-01-01

    In order to produce transmitted neutron dynamic images using neutron radiography, a real time system called Musashi dynamic image processing system (MDIPS) was developed to collect, process, display and record image data. The block diagram of the MDIPS is shown. The system consists of a highly sensitive, high resolution TV camera driven by a custom-made scanner, a TV camera deflection controller for optimal scanning, which adjusts to the luminous intensity and the moving speed of an object, a real-time corrector to perform the real time correction of dark current, shading distortion and field intensity fluctuation, a real time filter for increasing the image signal to noise ratio, a video recording unit and a pseudocolor monitor to realize recording in commercially available products and monitoring by means of the CRTs in standard TV scanning, respectively. The TV camera and the TV camera deflection controller utilized for producing still images can be applied to this case. The block diagram of the real-time corrector is shown. Its performance is explained. Linear filters and ranked order filters were developed. (K.I.)

  7. Iterative Redeployment of Illumination and Sensing (IRIS): Application to STW-SAR Imaging

    National Research Council Canada - National Science Library

    Marble, Jay; Raich, Raviv; Hero, Alfred O

    2006-01-01

    .... The IRIS algorithm has the following features: (1) use of a sparse Bayesian image model that captures the free-space dominated propagation characteristics of interiors of man-made structures such as caves and residences; (2...

  8. Area-efficient readout with 14-bit SAR-ADC for CMOS image sensors

    Directory of Open Access Journals (Sweden)

    Aziza Sassi Ben

    2016-01-01

    Full Text Available This paper proposes a readout design for CMOS image sensors. It has been squeezed into a 7.5um pitch under a 0.28um 1P3M technology. The ADC performs one 14-bit conversion in only 1.5us and targets a theoretical DNL feature about +1.3/-1 at 14-bit accuracy. Correlated Double Sampling (CDS is performed both in the analog and digital domains to preserve the image quality.

  9. Validation and operational measurements with SUSIE – A sar ice motion processing chain developed within promice (Programme for monitoring of Greenland ice-sheet)

    DEFF Research Database (Denmark)

    Merryman Boncori, John Peter; Dall, Jørgen; Ahlstrøm, A. P.

    2010-01-01

    This paper describes the validation of an ice-motion processing chain developed for the PROMICE project – a long-term program funded by the Danish ministry of Climate and Energy to monitor the mass budget of the Greenland ice-sheet. The processor, named SUSIE, (Scripts and Utilities for SAR Ice...

  10. Comparing Accuracy of Airborne Laser Scanning and TerraSAR-X Radar Images in the Estimation of Plot-Level Forest Variables

    Directory of Open Access Journals (Sweden)

    Juha Hyyppä

    2010-01-01

    Full Text Available In this study we compared the accuracy of low-pulse airborne laser scanning (ALS data, multi-temporal high-resolution noninterferometric TerraSAR-X radar data and a combined feature set derived from these data in the estimation of forest variables at plot level. The TerraSAR-X data set consisted of seven dual-polarized (HH/HV or VH/VV Stripmap mode images from all seasons of the year. We were especially interested in distinguishing between the tree species. The dependent variables estimated included mean volume, basal area, mean height, mean diameter and tree species-specific mean volumes. Selection of best possible feature set was based on a genetic algorithm (GA. The nonparametric k-nearest neighbour (k-NN algorithm was applied to the estimation. The research material consisted of 124 circular plots measured at tree level and located in the vicinity of Espoo, Finland. There are large variations in the elevation and forest structure in the study area, making it demanding for image interpretation. The best feature set contained 12 features, nine of them originating from the ALS data and three from the TerraSAR-X data. The relative RMSEs for the best performing feature set were 34.7% (mean volume, 28.1% (basal area, 14.3% (mean height, 21.4% (mean diameter, 99.9% (mean volume of Scots pine, 61.6% (mean volume of Norway spruce and 91.6% (mean volume of deciduous tree species. The combined feature set outperformed an ALS-based feature set marginally; in fact, the latter was better in the case of species-specific volumes. Features from TerraSAR-X alone performed poorly. However, due to favorable temporal resolution, satellite-borne radar imaging is a promising data source for updating large-area forest inventories based on low-pulse ALS.

  11. Analysis of the Effect of Radio Frequency Interference on Repeat Track Airborne InSAR System

    Directory of Open Access Journals (Sweden)

    Ding Bin

    2012-03-01

    Full Text Available The SAR system operating at low frequency is susceptible to Radio Frequency Interference (RFI from television station, radio station, and some other civil electronic facilities. The presence of RFI degrades the SAR image quality, and obscures the targets in the scene. Furthermore, RFI can cause interferometric phase error in repeat track InSAR system. In order to analyze the effect of RFI on interferometric phase of InSAR, real measured RFI signal are added on cone simulated SAR echoes. The imaging and interferometric processing results of both the RFI-contaminated and raw data are given. The effect of real measured RFI signal on repeat track InSAR system is analyzed. Finally, the imaging and interferometric processing results of both with and without RFI suppressed of the P band airborne repeat track InSAR real data are presented, which demonstrates the efficiency of the RFI suppression method in terms of decreasing the interferometric phase errors caused by RFI.

  12. ROADS CENTRE-AXIS EXTRACTION IN AIRBORNE SAR IMAGES: AN APPROACH BASED ON ACTIVE CONTOUR MODEL WITH THE USE OF SEMI-AUTOMATIC SEEDING

    Directory of Open Access Journals (Sweden)

    R. G. Lotte

    2013-05-01

    Full Text Available Research works dealing with computational methods for roads extraction have considerably increased in the latest two decades. This procedure is usually performed on optical or microwave sensors (radar imagery. Radar images offer advantages when compared to optical ones, for they allow the acquisition of scenes regardless of atmospheric and illumination conditions, besides the possibility of surveying regions where the terrain is hidden by the vegetation canopy, among others. The cartographic mapping based on these images is often manually accomplished, requiring considerable time and effort from the human interpreter. Maps for detecting new roads or updating the existing roads network are among the most important cartographic products to date. There are currently many studies involving the extraction of roads by means of automatic or semi-automatic approaches. Each of them presents different solutions for different problems, making this task a scientific issue still open. One of the preliminary steps for roads extraction can be the seeding of points belonging to roads, what can be done using different methods with diverse levels of automation. The identified seed points are interpolated to form the initial road network, and are hence used as an input for an extraction method properly speaking. The present work introduces an innovative hybrid method for the extraction of roads centre-axis in a synthetic aperture radar (SAR airborne image. Initially, candidate points are fully automatically seeded using Self-Organizing Maps (SOM, followed by a pruning process based on specific metrics. The centre-axis are then detected by an open-curve active contour model (snakes. The obtained results were evaluated as to their quality with respect to completeness, correctness and redundancy.

  13. Study on monitoring ecological restoration in Jiuli mining area by SAR image

    Science.gov (United States)

    Wei, Na; Chen, Fu; Tang, Qian

    2011-10-01

    The ecological restoration in mining area is one of the study hot spots in the field of resources and environment at present. The vegetation biomass is used as the ecological restoration evaluation index in mining area in the paper. The synthetic aperture radar image after ecological restoration in mining area is used to classify different kinds of vegetation covers. Integrating the field data and the data of L band, the average total backward scattering coefficient which corresponds to the synthetic aperture radar image is calculated and the relation model between the average total backward scattering coefficient and vegetation biomass is established. At last the vegetation biomass is assessed in Jiuli mining area. The results show that the vegetation biomass characteristics which are assessed by using synthetic aperture radar image data and the field data of vegetation biomass characteristics have better consistency in Jiuli mining area. The effects of ecological restoration can be evaluated by using this relation model effectively and accurately.

  14. New Processing of Spaceborne Imaging Radar-C (SIR-C) Data

    Science.gov (United States)

    Meyer, F. J.; Gracheva, V.; Arko, S. A.; Labelle-Hamer, A. L.

    2017-12-01

    The Spaceborne Imaging Radar-C (SIR-C) was a radar system, which successfully operated on two separate shuttle missions in April and October 1994. During these two missions, a total of 143 hours of radar data were recorded. SIR-C was the first multifrequency and polarimetric spaceborne radar system, operating in dual frequency (L- and C- band) and with quad-polarization. SIR-C had a variety of different operating modes, which are innovative even from today's point of view. Depending on the mode, it was possible to acquire data with different polarizations and carrier frequency combinations. Additionally, different swaths and bandwidths could be used during the data collection and it was possible to receive data with two antennas in the along-track direction.The United States Geological Survey (USGS) distributes the synthetic aperture radar (SAR) images as single-look complex (SLC) and multi-look complex (MLC) products. Unfortunately, since June 2005 the SIR-C processor has been inoperable and not repairable. All acquired SLC and MLC images were processed with a course resolution of 100 m with the goal of generating a quick look. These images are however not well suited for scientific analysis. Only a small percentage of the acquired data has been processed as full resolution SAR images and the unprocessed high resolution data cannot be processed any more at the moment.At the Alaska Satellite Facility (ASF) a new processor was developed to process binary SIR-C data to full resolution SAR images. ASF is planning to process the entire recoverable SIR-C archive to full resolution SLCs, MLCs and high resolution geocoded image products. ASF will make these products available to the science community through their existing data archiving and distribution system.The final paper will describe the new processor and analyze the challenges of reprocessing the SIR-C data.

  15. using fuzzy logic in image processing

    International Nuclear Information System (INIS)

    Ashabrawy, M.A.F.

    2002-01-01

    due to the unavoidable merge between computer and mathematics, the signal processing in general and the processing in particular have greatly improved and advanced. signal processing deals with the processing of any signal data for use by a computer, while image processing deals with all kinds of images (just images). image processing involves the manipulation of image data for better appearance and viewing by people; consequently, it is a rapidly growing and exciting field to be involved in today . this work takes an applications - oriented approach to image processing .the applications; the maps and documents of the first egyptian research reactor (ETRR-1), the x-ray medical images and the fingerprints image. since filters, generally, work continuous ranges rather than discrete values, fuzzy logic techniques are more convenient.thee techniques are powerful in image processing and can deal with one- dimensional, 1-D and two - dimensional images, 2-D images as well

  16. Image processing with ImageJ

    NARCIS (Netherlands)

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

    2004-01-01

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

  17. a Method for the Extraction of Long-Term Deformation Characteristics of Long-Span High-Speed Railway Bridges Using High-Resolution SAR Images

    Science.gov (United States)

    Jia, H. G.; Liu, L. Y.

    2016-06-01

    Natural causes and high-speed train load will result in the structural deformation of long-span bridges, which greatly influence the safety operation of high-speed railway. Hence it is necessary to conduct the deformation monitoring and regular status assessment for long-span bridges. However for some traditional surveying technique, e.g. control-point-based surveying techniques, a lot of human and material resources are needed to perform the long-term monitoring for the whole bridge. In this study we detected the long-term bridge deformation time-series by persistent scatterer interferometric synthetic aperture radar (PSInSAR) technique using the high-resolution SAR images and external digital elevation model. A test area in Nanjing city in China is chosen and TerraSAR-X images and Tandem-X for this area have been used. There is the Dashengguan bridge in high speed railway in this area as study object to evaluate this method. Experiment results indicate that the proposed method can effectively extract the long-term deformation of long-span high-speed railway bridge with higher accuracy.

  18. A METHOD FOR THE EXTRACTION OF LONG-TERM DEFORMATION CHARACTERISTICS OF LONG-SPAN HIGH-SPEED RAILWAY BRIDGES USING HIGH-RESOLUTION SAR IMAGES

    Directory of Open Access Journals (Sweden)

    H. G. Jia

    2016-06-01

    Full Text Available Natural causes and high-speed train load will result in the structural deformation of long-span bridges, which greatly influence the safety operation of high-speed railway. Hence it is necessary to conduct the deformation monitoring and regular status assessment for long-span bridges. However for some traditional surveying technique, e.g. control-point-based surveying techniques, a lot of human and material resources are needed to perform the long-term monitoring for the whole bridge. In this study we detected the long-term bridge deformation time-series by persistent scatterer interferometric synthetic aperture radar (PSInSAR technique using the high-resolution SAR images and external digital elevation model. A test area in Nanjing city in China is chosen and TerraSAR-X images and Tandem-X for this area have been used. There is the Dashengguan bridge in high speed railway in this area as study object to evaluate this method. Experiment results indicate that the proposed method can effectively extract the long-term deformation of long-span high-speed railway bridge with higher accuracy.

  19. On the classification of mixed floating pollutants on the Yellow Sea of China by using a quad-polarized SAR image

    Science.gov (United States)

    Wang, Xiaochen; Shao, Yun; Tian, Wei; Li, Kun

    2018-06-01

    This study explored different methodologies using a C-band RADARSAT-2 quad-polarized Synthetic Aperture Radar (SAR) image located over China's Yellow Sea to investigate polarization decomposition parameters for identifying mixed floating pollutants from a complex ocean background. It was found that solitary polarization decomposition did not meet the demand for detecting and classifying multiple floating pollutants, even after applying a polarized SAR image. Furthermore, considering that Yamaguchi decomposition is sensitive to vegetation and the algal variety Enteromorpha prolifera, while H/A/alpha decomposition is sensitive to oil spills, a combination of parameters which was deduced from these two decompositions was proposed for marine environmental monitoring of mixed floating sea surface pollutants. A combination of volume scattering, surface scattering, and scattering entropy was the best indicator for classifying mixed floating pollutants from a complex ocean background. The Kappa coefficients for Enteromorpha prolifera and oil spills were 0.7514 and 0.8470, respectively, evidence that the composite polarized parameters based on quad-polarized SAR imagery proposed in this research is an effective monitoring method for complex marine pollution.

  20. Image quality dependence on image processing software in ...

    African Journals Online (AJOL)

    Image quality dependence on image processing software in computed radiography. ... Agfa CR readers use MUSICA software, and an upgrade with significantly different image ... Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

  1. Global Rapid Flood Mapping System with Spaceborne SAR Data

    Science.gov (United States)

    Yun, S. H.; Owen, S. E.; Hua, H.; Agram, P. S.; Fattahi, H.; Liang, C.; Manipon, G.; Fielding, E. J.; Rosen, P. A.; Webb, F.; Simons, M.

    2017-12-01

    As part of the Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards, at NASA's Jet Propulsion Laboratory and California Institute of Technology, we have developed an automated system that produces derived products for flood extent map generation using spaceborne SAR data. The system takes user's input of area of interest polygons and time window for SAR data search (pre- and post-event). Then the system automatically searches and downloads SAR data, processes them to produce coregistered SAR image pairs, and generates log amplitude ratio images from each pair. Currently the system is automated to support SAR data from the European Space Agency's Sentinel-1A/B satellites. We have used the system to produce flood extent maps from Sentinel-1 SAR data for the May 2017 Sri Lanka floods, which killed more than 200 people and displaced about 600,000 people. Our flood extent maps were delivered to the Red Cross to support response efforts. Earlier we also responded to the historic August 2016 Louisiana floods in the United States, which claimed 13 people's lives and caused over $10 billion property damage. For this event, we made synchronized observations from space, air, and ground in close collaboration with USGS and NOAA. The USGS field crews acquired ground observation data, and NOAA acquired high-resolution airborne optical imagery within the time window of +/-2 hours of the SAR data acquisition by JAXA's ALOS-2 satellite. The USGS coordinates of flood water boundaries were used to calibrate our flood extent map derived from the ALOS-2 SAR data, and the map was delivered to FEMA for estimating the number of households affected. Based on the lessons learned from this response effort, we customized the ARIA system automation for rapid flood mapping and developed a mobile friendly web app that can easily be used in the field for data collection. Rapid automatic generation of SAR-based global flood maps calibrated with independent observations from

  2. Fast processing of foreign fiber images by image blocking

    OpenAIRE

    Yutao Wu; Daoliang Li; Zhenbo Li; Wenzhu Yang

    2014-01-01

    In the textile industry, it is always the case that cotton products are constitutive of many types of foreign fibers which affect the overall quality of cotton products. As the foundation of the foreign fiber automated inspection, image process exerts a critical impact on the process of foreign fiber identification. This paper presents a new approach for the fast processing of foreign fiber images. This approach includes five main steps, image block, image pre-decision, image background extra...

  3. An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3.

    Science.gov (United States)

    Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le

    2018-02-12

    The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.

  4. Fast processing of foreign fiber images by image blocking

    Directory of Open Access Journals (Sweden)

    Yutao Wu

    2014-08-01

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

  5. Biomedical signal and image processing.

    Science.gov (United States)

    Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

    2011-01-01

    Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

  6. Measurement and imaging of infragravity waves in sea ice using InSAR

    Science.gov (United States)

    Mahoney, Andrew R.; Dammann, Dyre O.; Johnson, Mark A.; Eicken, Hajo; Meyer, Franz J.

    2016-06-01

    Using short-temporal baseline interferometric synthetic aperture radar, we capture instantaneous images of a persistent field of infragravity waves propagating through sea ice near Barrow, Alaska, during January 2015. We estimate wave amplitudes to be between 1.2 and 1.8 mm. Curvature of wavefronts is consistent with refraction of waves entering shallow water from a source region north of Barrow. A shallow water wave model indicates that the geometry of the wavefronts is relatively insensitive to the source location, but other evidence suggests the waves may have originated in the North Atlantic, making this perhaps the longest observed propagation path for waves through ice. We also note that steepening of the waves entering shallow water can increase the peak strain by an order of magnitude, suggesting that infragravity waves may play a role in determining the location of the landfast ice edge with respect to water depth.

  7. Review of Biomedical Image Processing

    Directory of Open Access Journals (Sweden)

    Ciaccio Edward J

    2011-11-01

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

  8. SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks

    OpenAIRE

    Zhang, Fan; Hu, Chen; Yin, Qiang; Li, Wei; Li, Hengchao; Hong, Wen

    2017-01-01

    The outstanding pattern recognition performance of deep learning brings new vitality to the synthetic aperture radar (SAR) automatic target recognition (ATR). However, there is a limitation in current deep learning based ATR solution that each learning process only handle one SAR image, namely learning the static scattering information, while missing the space-varying information. It is obvious that multi-aspect joint recognition introduced space-varying scattering information should improve ...

  9. Image processing with personal computer

    International Nuclear Information System (INIS)

    Hara, Hiroshi; Handa, Madoka; Watanabe, Yoshihiko

    1990-01-01

    The method of automating the judgement works using photographs in radiation nondestructive inspection with a simple type image processor on the market was examined. The software for defect extraction and making binary and the software for automatic judgement were made for trial, and by using the various photographs on which the judgement was already done as the object, the accuracy and the problematic points were tested. According to the state of the objects to be photographed and the condition of inspection, the accuracy of judgement from 100% to 45% was obtained. The criteria for judgement were in conformity with the collection of reference photographs made by Japan Cast Steel Association. In the non-destructive inspection by radiography, the number and size of the defect images in photographs are visually judged, the results are collated with the standard, and the quality is decided. Recently, the technology of image processing with personal computers advanced, therefore by utilizing this technology, the automation of the judgement of photographs was attempted to improve the accuracy, to increase the inspection efficiency and to realize labor saving. (K.I.)

  10. Infrared thermography quantitative image processing

    Science.gov (United States)

    Skouroliakou, A.; Kalatzis, I.; Kalyvas, N.; Grivas, TB

    2017-11-01

    Infrared thermography is an imaging technique that has the ability to provide a map of temperature distribution of an object’s surface. It is considered for a wide range of applications in medicine as well as in non-destructive testing procedures. One of its promising medical applications is in orthopaedics and diseases of the musculoskeletal system where temperature distribution of the body’s surface can contribute to the diagnosis and follow up of certain disorders. Although the thermographic image can give a fairly good visual estimation of distribution homogeneity and temperature pattern differences between two symmetric body parts, it is important to extract a quantitative measurement characterising temperature. Certain approaches use temperature of enantiomorphic anatomical points, or parameters extracted from a Region of Interest (ROI). A number of indices have been developed by researchers to that end. In this study a quantitative approach in thermographic image processing is attempted based on extracting different indices for symmetric ROIs on thermograms of the lower back area of scoliotic patients. The indices are based on first order statistical parameters describing temperature distribution. Analysis and comparison of these indices result in evaluating the temperature distribution pattern of the back trunk expected in healthy, regarding spinal problems, subjects.

  11. Radar image and data fusion for natural hazards characterisation

    Science.gov (United States)

    Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

    2010-01-01

    Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

  12. Digital image processing mathematical and computational methods

    CERN Document Server

    Blackledge, J M

    2005-01-01

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

  13. Radiology image orientation processing for workstation display

    Science.gov (United States)

    Chang, Chung-Fu; Hu, Kermit; Wilson, Dennis L.

    1998-06-01

    Radiology images are acquired electronically using phosphor plates that are read in Computed Radiology (CR) readers. An automated radiology image orientation processor (RIOP) for determining the orientation for chest images and for abdomen images has been devised. In addition, the chest images are differentiated as front (AP or PA) or side (Lateral). Using the processing scheme outlined, hospitals will improve the efficiency of quality assurance (QA) technicians who orient images and prepare the images for presentation to the radiologists.

  14. Digital Data Processing of Images

    African Journals Online (AJOL)

    be concerned with the image enhancement of scintigrams. Two applications of image ... obtained from scintigraphic equipment, image enhance- ment by computer was ... used as an example. ..... Using video-tape display, areas of interest are ...

  15. Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Simon Plank

    2014-12-01

    Full Text Available In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies’ contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads—rectangular features of bare land covering an area of approximately 50–60 m × 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery and the possibility of detailed land use classification (vs. single-pol SAR. The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user’s accuracy of the methodology by an order of a magnitude. The final achieved user’s and producer’s accuracy is 59%–71% in each case (area based accuracy assessment. Considering only the numbers of correctly/falsely detected oil well pads, the user’s and producer’s accuracies increase to even 74%–89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are

  16. Statistical image processing and multidimensional modeling

    CERN Document Server

    Fieguth, Paul

    2010-01-01

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

  17. Image Processing and Features Extraction of Fingerprint Images ...

    African Journals Online (AJOL)

    To demonstrate the importance of the image processing of fingerprint images prior to image enrolment or comparison, the set of fingerprint images in databases (a) and (b) of the FVC (Fingerprint Verification Competition) 2000 database were analyzed using a features extraction algorithm. This paper presents the results of ...

  18. Use of time series of optical and SAR images in the estimation of snow cover for the optimization of water use in the Andes of Argentina and Chile

    Science.gov (United States)

    Salinas de Salmuni, Graciela; Cabezas Cartes, Ricardo; Menicocci, Felix

    2014-05-01

    operational application because it is simple and easy to implement. From the analysis of multitemporal study in the region using COSMO SkyMed images, it is observed that the values of wet snow coverage, obtained along the 2012 hydrological cycle, are consistent with the dynamics of the same: The study area has a high rise and steep relief (up to 6400m), therefore the shadows loom large, processing optical and SAR images improve the results. The behavior of the accumulation process (winter) and snowmelt (summer), is influenced by the elevation of the different study areas. A high percentage (49%) of surface snow at higher elevations to 3000 m. This is due to the accumulation of snow increases with elevation, by the combined effect of low temperatures and increased precipitation snowy orographic effect. In studies of wet meadows with optical images, a high correspondence between the spectral classes and vigor of vegetation and soil moisture (seen in the field) so are considered as indicators of degradation of these ecosystems was observed

  19. Scilab and SIP for Image Processing

    OpenAIRE

    Fabbri, Ricardo; Bruno, Odemir Martinez; Costa, Luciano da Fontoura

    2012-01-01

    This paper is an overview of Image Processing and Analysis using Scilab, a free prototyping environment for numerical calculations similar to Matlab. We demonstrate the capabilities of SIP -- the Scilab Image Processing Toolbox -- which extends Scilab with many functions to read and write images in over 100 major file formats, including PNG, JPEG, BMP, and TIFF. It also provides routines for image filtering, edge detection, blurring, segmentation, shape analysis, and image recognition. Basic ...

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

    Directory of Open Access Journals (Sweden)

    Carlos Santamaria

    2017-07-01

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

  1. Rupture process of the 2016 Mw 7.8 Ecuador earthquake from joint inversion of InSAR data and teleseismic P waveforms

    Science.gov (United States)

    Yi, Lei; Xu, Caijun; Wen, Yangmao; Zhang, Xu; Jiang, Guoyan

    2018-01-01

    The 2016 Ecuador earthquake ruptured the Ecuador-Colombia subduction interface where several historic megathrust earthquakes had occurred. In order to determine a detailed rupture model, Interferometric Synthetic Aperture Radar (InSAR) images and teleseismic data sets were objectively weighted by using a modified Akaika's Bayesian Information Criterion (ABIC) method to jointly invert for the rupture process of the earthquake. In modeling the rupture process, a constrained waveform length method, unlike the traditional subjective selected waveform length method, was used since the lengths of inverted waveforms were strictly constrained by the rupture velocity and rise time (the slip duration time). The optimal rupture velocity and rise time of the earthquake were estimated from grid search, which were determined to be 2.0 km/s and 20 s, respectively. The inverted model shows that the event is dominated by thrust movement and the released moment is 5.75 × 1020 Nm (Mw 7.77). The slip distribution extends southward along the Ecuador coast line in an elongated stripe at a depth between 10 and 25 km. The slip model is composed of two asperities and slipped over 4 m. The source time function is approximate 80 s that separated into two segments corresponding to the two asperities. The small magnitude of the slip occurred in the updip section of the fault plane resulted in small tsunami waves that were verified by observations near the coast. We suggest a possible situation that the rupture zone of the 2016 earthquake is likely not overlapped with that of the 1942 earthquake.

  2. UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

    Directory of Open Access Journals (Sweden)

    S. Havivi

    2016-06-01

    Full Text Available Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD for SAR data and Covariance Equalization (CE for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a

  3. Autonomous control systems: applications to remote sensing and image processing

    Science.gov (United States)

    Jamshidi, Mohammad

    2001-11-01

    One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.

  4. Image processing technology for nuclear facilities

    International Nuclear Information System (INIS)

    Lee, Jong Min; Lee, Yong Beom; Kim, Woong Ki; Park, Soon Young

    1993-05-01

    Digital image processing technique is being actively studied since microprocessors and semiconductor memory devices have been developed in 1960's. Now image processing board for personal computer as well as image processing system for workstation is developed and widely applied to medical science, military, remote inspection, and nuclear industry. Image processing technology which provides computer system with vision ability not only recognizes nonobvious information but processes large information and therefore this technique is applied to various fields like remote measurement, object recognition and decision in adverse environment, and analysis of X-ray penetration image in nuclear facilities. In this report, various applications of image processing to nuclear facilities are examined, and image processing techniques are also analysed with the view of proposing the ideas for future applications. (Author)

  5. MM wave SAR sensor design: Concept for an airborne low level reconnaissance system

    Science.gov (United States)

    Boesswetter, C.

    1986-07-01

    The basic system design considerations for a high resolution SAR system operating at 35 GHz or 94 GHz are given. First it is shown that only the focussed SAR concept in the side looking configuration matches the requirements and constraints. After definition of illumination geometry and airborne modes the fundamental SAR parameters in range and azimuth direction are derived. A review of the performance parameters of some critical mm wave components (coherent pulsed transmitters, front ends, antennas) establish the basis for further analysis. The power and contrast budget in the processed SAR image shows the feasibility of a 35/94 GHz SAR sensor design. The discussion of the resulting system parameters points out that this unusual system design implies both benefits and new risk areas. One of the benefits besides the compactness of sensor hardware turns out to be the short synthetic aperture length simplifying the design of the digital SAR processor, preferably operating in real time. A possible architecture based on current state-of-the-art correlator hardware is shown. One of the potential risk areas in achieving high resolution SAR imagery in the mm wave frequency band is motion compensation. However, it is shown that the short range and short synthetic aperture lengths ease the problem so that correction of motion induced phase errors and thus focussed synthetic aperture processing should be possible.

  6. Nuclear medicine imaging and data processing

    International Nuclear Information System (INIS)

    Bell, P.R.; Dillon, R.S.

    1978-01-01

    The Oak Ridge Imaging System (ORIS) is a software operating system structure around the Digital Equipment Corporation's PDP-8 minicomputer which provides a complete range of image manipulation procedures. Through its modular design it remains open-ended for easy expansion to meet future needs. Already included in the system are image access routines for use with the rectilinear scanner or gamma camera (both static and flow studies); display hardware design and corresponding software; archival storage provisions; and, most important, many image processing techniques. The image processing capabilities include image defect removal, smoothing, nonlinear bounding, preparation of functional images, and transaxial emission tomography reconstruction from a limited number of views

  7. Signal processing issues for the exploitation of pulse-to-pulse encoding SAR transponders

    DEFF Research Database (Denmark)

    Merryman Boncori, John Peter; Schiavon, Giovanni

    2008-01-01

    -encoding point scatterers and distributed ones. A time-domain processing algorithm and a code synchronization procedure are proposed and validated on simulated data and on a European Remote Sensing Satellite-2 data set containing prototypes of such a device. The interaction of the transponder signal with terrain...

  8. Eliminating "Hotspots" in Digital Image Processing

    Science.gov (United States)

    Salomon, P. M.

    1984-01-01

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

  9. Image processing unit with fall-back.

    NARCIS (Netherlands)

    2011-01-01

    An image processing unit ( 100,200,300 ) for computing a sequence of output images on basis of a sequence of input images, comprises: a motion estimation unit ( 102 ) for computing a motion vector field on basis of the input images; a quality measurement unit ( 104 ) for computing a value of a

  10. Sentinel-3 SAR Altimetry Toolbox

    Science.gov (United States)

    Benveniste, Jerome; Lucas, Bruno; DInardo, Salvatore

    2015-04-01

    The prime objective of the SEOM (Scientific Exploitation of Operational Missions) element is to federate, support and expand the large international research community that the ERS, ENVISAT and the Envelope programmes have build up over the last 20 years for the future European operational Earth Observation missions, the Sentinels. Sentinel-3 builds directly on a proven heritage of ERS-2 and Envisat, and CryoSat-2, with a dual-frequency (Ku and C band) advanced Synthetic Aperture Radar Altimeter (SRAL) that provides measurements at a resolution of ~300m in SAR mode along track. Sentinel-3 will provide exact measurements of sea-surface height along with accurate topography measurements over sea ice, ice sheets, rivers and lakes. The first of the two Sentinels is expected to be launched in early 2015. The current universal altimetry toolbox is BRAT (Basic Radar Altimetry Toolbox) which can read all previous and current altimetry mission's data, but it does not have the capabilities to read the upcoming Sentinel-3 L1 and L2 products. ESA will endeavour to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats, the BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with Matlab/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as netCDF, ASCII text files, KML (Google Earth

  11. Tensors in image processing and computer vision

    CERN Document Server

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

    2009-01-01

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

  12. Optoelectronic imaging of speckle using image processing method

    Science.gov (United States)

    Wang, Jinjiang; Wang, Pengfei

    2018-01-01

    A detailed image processing of laser speckle interferometry is proposed as an example for the course of postgraduate student. Several image processing methods were used together for dealing with optoelectronic imaging system, such as the partial differential equations (PDEs) are used to reduce the effect of noise, the thresholding segmentation also based on heat equation with PDEs, the central line is extracted based on image skeleton, and the branch is removed automatically, the phase level is calculated by spline interpolation method, and the fringe phase can be unwrapped. Finally, the imaging processing method was used to automatically measure the bubble in rubber with negative pressure which could be used in the tire detection.

  13. Fuzzy image processing and applications with Matlab

    CERN Document Server

    Chaira, Tamalika

    2009-01-01

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

  14. High-Level Performance Modeling of SAR Systems

    Science.gov (United States)

    Chen, Curtis

    2006-01-01

    SAUSAGE (Still Another Utility for SAR Analysis that s General and Extensible) is a computer program for modeling (see figure) the performance of synthetic- aperture radar (SAR) or interferometric synthetic-aperture radar (InSAR or IFSAR) systems. The user is assumed to be familiar with the basic principles of SAR imaging and interferometry. Given design parameters (e.g., altitude, power, and bandwidth) that characterize a radar system, the software predicts various performance metrics (e.g., signal-to-noise ratio and resolution). SAUSAGE is intended to be a general software tool for quick, high-level evaluation of radar designs; it is not meant to capture all the subtleties, nuances, and particulars of specific systems. SAUSAGE was written to facilitate the exploration of engineering tradeoffs within the multidimensional space of design parameters. Typically, this space is examined through an iterative process of adjusting the values of the design parameters and examining the effects of the adjustments on the overall performance of the system at each iteration. The software is designed to be modular and extensible to enable consideration of a variety of operating modes and antenna beam patterns, including, for example, strip-map and spotlight SAR acquisitions, polarimetry, burst modes, and squinted geometries.

  15. UAVSAR and TerraSAR-X Based InSAR Detection of Localized Subsidence in the New Orleans Area

    Science.gov (United States)

    Blom, R. G.; An, K.; Jones, C. E.; Latini, D.

    2014-12-01

    Vulnerability of the US Gulf coast to inundation has received increased attention since hurricanes Katrina and Rita. Compounding effects of sea level rise, wetland loss, and regional and local subsidence makes flood protection a difficult challenge, and particularly for the New Orleans area. Key to flood protection is precise knowledge of elevations and elevation changes. Analysis of historical and continuing geodetic measurements show surprising complexity, including locations subsiding more rapidly than considered during planning of hurricane protection and coastal restoration projects. Combining traditional, precise geodetic data with interferometric synthetic aperture radar (InSAR) observations can provide geographically dense constraints on surface deformation. The Gulf Coast environment is challenging for InSAR techniques, especially with systems not designed for interferometry. We use two InSAR capable systems, the L- band (24 cm wavelength) airborne JPL/NASA UAVSAR, and the DLR/EADS Astrium spaceborne TerraSAR X-band (3 cm wavelength), and compare results. First, we are applying pair-wise InSAR to the longer wavelength UAVSAR data to detect localized elevation changes potentially impacting flood protection infrastructure from 2009 - 2014. We focus on areas on and near flood protection infrastructure to identify changes indicative of subsidence, structural deformation, and/or seepage. The Spaceborne TerraSAR X-band SAR system has relatively frequent observations, and dense persistent scatterers in urban areas, enabling measurement of very small displacements. We compare L-band UAVSAR results with permanent scatterer (PS-InSAR) and Short Baseline Subsets (SBAS) interferometric analyses of a stack composed by 28 TerraSAR X-band images acquired over the same period. Thus we can evaluate results from the different radar frequencies and analyses techniques. Preliminary results indicate subsidence features potentially of a variety of causes, including ground water

  16. Near-Space TOPSAR Large-Scene Full-Aperture Imaging Scheme Based on Two-Step Processing

    Directory of Open Access Journals (Sweden)

    Qianghui Zhang

    2016-07-01

    Full Text Available Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS, which is a novel wide-swath imaging mode and allows the beam of SAR to scan along the azimuth, can reduce the time of echo acquisition for large scene. Thus, near-space TOPS-mode SAR (NS-TOPSAR provides a new opportunity for sustained large-scene imaging. An efficient full-aperture imaging scheme for NS-TOPSAR is proposed in this paper. In this scheme, firstly, two-step processing (TSP is adopted to eliminate the Doppler aliasing of the echo. Then, the data is focused in two-dimensional frequency domain (FD based on Stolt interpolation. Finally, a modified TSP (MTSP is performed to remove the azimuth aliasing. Simulations are presented to demonstrate the validity of the proposed imaging scheme for near-space large-scene imaging application.

  17. Digital image processing techniques in archaeology

    Digital Repository Service at National Institute of Oceanography (India)

    Santanam, K.; Vaithiyanathan, R.; Tripati, S.

    Digital image processing involves the manipulation and interpretation of digital images with the aid of a computer. This form of remote sensing actually began in the 1960's with a limited number of researchers analysing multispectral scanner data...

  18. 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....

  19. Generation and assessment of turntable SAR data for the support of ATR development

    Science.gov (United States)

    Cohen, Marvin N.; Showman, Gregory A.; Sangston, K. James; Sylvester, Vincent B.; Gostin, Lamar; Scheer, C. Ruby

    1998-10-01

    Inverse synthetic aperture radar (ISAR) imaging on a turntable-tower test range permits convenient generation of high resolution two-dimensional images of radar targets under controlled conditions for testing SAR image processing and for supporting automatic target recognition (ATR) algorithm development. However, turntable ISAR images are often obtained under near-field geometries and hence may suffer geometric distortions not present in airborne SAR images. In this paper, turntable data collected at Georgia Tech's Electromagnetic Test Facility are used to begin to assess the utility of two- dimensional ISAR imaging algorithms in forming images to support ATR development. The imaging algorithms considered include a simple 2D discrete Fourier transform (DFT), a 2-D DFT with geometric correction based on image domain resampling, and a computationally-intensive geometric matched filter solution. Images formed with the various algorithms are used to develop ATR templates, which are then compared with an eye toward utilization in an ATR algorithm.

  20. Enhancement of image contrast in linacgram through image processing

    International Nuclear Information System (INIS)

    Suh, Hyun Suk; Shin, Hyun Kyo; Lee, Re Na

    2000-01-01

    Conventional radiation therapy portal images gives low contrast images. The purpose of this study was to enhance image contrast of a linacgram by developing a low--cost image processing method. Chest linacgram was obtained by irradiating humanoid phantom and scanned using Diagnostic-Pro scanner for image processing. Several types of scan method were used in scanning. These include optical density scan, histogram equalized scan, linear histogram based scan, linear histogram independent scan, linear optical density scan, logarithmic scan, and power square root scan. The histogram distribution of the scanned images were plotted and the ranges of the gray scale were compared among various scan types. The scanned images were then transformed to the gray window by pallette fitting method and the contrast of the reprocessed portal images were evaluated for image improvement. Portal images of patients were also taken at various anatomic sites and the images were processed by Gray Scale Expansion (GSE) method. The patient images were analyzed to examine the feasibility of using the GSE technique in clinic. The histogram distribution showed that minimum and maximum gray scale ranges of 3192 and 21940 were obtained when the image was scanned using logarithmic method and square root method, respectively. Out of 256 gray scale, only 7 to 30% of the steps were used. After expanding the gray scale to full range, contrast of the portal images were improved. Experiment performed with patient image showed that improved identification of organs were achieved by GSE in portal images of knee joint, head and neck, lung, and pelvis. Phantom study demonstrated that the GSE technique improved image contrast of a linacgram. This indicates that the decrease in image quality resulting from the dual exposure, could be improved by expanding the gray scale. As a result, the improved technique will make it possible to compare the digitally reconstructed radiographs (DRR) and simulation image for

  1. Image processing for medical diagnosis using CNN

    International Nuclear Information System (INIS)

    Arena, Paolo; Basile, Adriano; Bucolo, Maide; Fortuna, Luigi

    2003-01-01

    Medical diagnosis is one of the most important area in which image processing procedures are usefully applied. Image processing is an important phase in order to improve the accuracy both for diagnosis procedure and for surgical operation. One of these fields is tumor/cancer detection by using Microarray analysis. The research studies in the Cancer Genetics Branch are mainly involved in a range of experiments including the identification of inherited mutations predisposing family members to malignant melanoma, prostate and breast cancer. In bio-medical field the real-time processing is very important, but often image processing is a quite time-consuming phase. Therefore techniques able to speed up the elaboration play an important rule. From this point of view, in this work a novel approach to image processing has been developed. The new idea is to use the Cellular Neural Networks to investigate on diagnostic images, like: Magnetic Resonance Imaging, Computed Tomography, and fluorescent cDNA microarray images

  2. Image processing in diabetic related causes

    CERN Document Server

    Kumar, Amit

    2016-01-01

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

  3. Synthetic aperture radar imaging simulator for pulse envelope evaluation

    Science.gov (United States)

    Balster, Eric J.; Scarpino, Frank A.; Kordik, Andrew M.; Hill, Kerry L.

    2017-10-01

    A simulator for spotlight synthetic aperture radar (SAR) image formation is presented. The simulator produces radar returns from a virtual radar positioned at an arbitrary distance and altitude. The radar returns are produced from a source image, where the return is a weighted summation of linear frequency-modulated (LFM) pulse signals delayed by the distance of each pixel in the image to the radar. The imagery is resampled into polar format to ensure consistent range profiles to the position of the radar. The SAR simulator provides a capability enabling the objective analysis of formed SAR imagery, comparing it to an original source image. This capability allows for analysis of various SAR signal processing techniques previously determined by impulse response function (IPF) analysis. The results suggest that IPF analysis provides results that may not be directly related to formed SAR image quality. Instead, the SAR simulator uses image quality metrics, such as peak signal-to-noise ratio (PSNR) and structured similarity index (SSIM), for formed SAR image quality analysis. To showcase the capability of the SAR simulator, it is used to investigate the performance of various envelopes applied to LFM pulses. A power-raised cosine window with a power p=0.35 and roll-off factor of β=0.15 is shown to maximize the quality of the formed SAR images by improving PSNR by 0.84 dB and SSIM by 0.06 from images formed utilizing a rectangular pulse, on average.

  4. A Performance Comparison Of A CFAR Ship Detection Algorithm Using Envisat, RadarSat, COSMO-SkyMed and Terra SAR-X Images

    Science.gov (United States)

    Lorenzzetti, Joao A.; Paes, Rafael L.; Gheradi, Douglas M.

    2010-04-01

    In this paper we discuss the results of a CFAR ship detection algorithm for a series of SAR images of the Brazilian coast. The following configuration for the CFAR target/buffer/background windows gave the best results: 3x3/5x5/13x13 for a PFA of 0.1% for pixel spacing greater than 50m. For pixel spacing less than 50m, best results were achieved for PFA of 1% and windows sizes of 5x5/7x7/15x15. Results indicate that CFAR as implemented gave good results as measured by the Figure of Merit, as defined by Foulkes and Booth (2000), which varied from 0.79 for CosmoSkymed to 0.88 for Envisat. Results obtained should be taken so far only as an indication of the performance of the implemented CFAR due to the limited sample of images.

  5. Organization of bubble chamber image processing

    International Nuclear Information System (INIS)

    Gritsaenko, I.A.; Petrovykh, L.P.; Petrovykh, Yu.L.; Fenyuk, A.B.

    1985-01-01

    A programme of bubble chamber image processing is described. The programme is written in FORTRAN, it is developed for the DEC-10 computer and is designed for operation of semi-automation processing-measurement projects PUOS-2 and PUOS-4. Fornalization of the image processing permits to use it for different physical experiments

  6. SAR data for the analysis of forest features: current Brazilian experiences

    Directory of Open Access Journals (Sweden)

    Fábio Guimarães Gonçalves

    2007-06-01

    Full Text Available This article presents some applications of airborne polarimetric and/or interferometric microwave data to improve the knowledge of forest structures. Three airborne SAR (Synthetic Aperture Radar experiments were done in the Amazon tropical forest: (a to study the spatial distribution of very large trees (VLTs in the primary forest using local maximum filtering and a series of Markov processes; (b to model the estimation of biomass variations in primary and secondary forests; (c to analyze the retrieval timber volume over selective logging areas. Another experiment (d was to investigate the relation among SAR data and the volumetric configuration in stands of Eucalyptus sp done by an airborne SAR imaging mission in SE-Brazil. To perform the objectives (b, (c and (d we carry out regression techniques, using variables got from multipolarimetric and/or interferometric SAR attributes and biophysical parameters from the forest cover. All data from the experiments were calibrated radiometrically to extract information during digital processing, besides an exhaustive field survey which was done simultaneously to SAR imaging, to know the physiognomy/structure of forest typology and to support the models produced for each case. The results of this series of experiments show advances at the techniques to treat SAR data, focusing on models of stand architecture and forest stock density. This will be helpful to increase the regional inventory and surveying procedures of forest conversion in the Brazilian territory in the near future.

  7. SAR data for the analysis of forest features: current Brazilian experiences

    Directory of Open Access Journals (Sweden)

    Fábio Guimarães Gonçalves

    2006-12-01

    Full Text Available This article presents some applications of airborne polarimetric and/or interferometric microwave data to improve the knowledge of forest structures. Three airborne SAR (Synthetic Aperture Radar experiments were done in the Amazon tropical forest: (a to study the spatial distribution of very large trees (VLTs in the primary forest using local maximum filtering and a series of Markov processes; (b to model the estimation of biomass variations in primary and secondary forests; (c to analyze the retrieval of timber volume over selective logging areas. Another experiment (d was to investigate the relation among SAR data and the volumetric configuration in stands of Eucalyptus sp. done by an airborne SAR imaging mission in SE-Brazil. To perform the objectives (b, (c and (d we carry out regression techniques, using variables got from multipolarimetric and/or interferometric SAR attributes and biophysical parameters from the forest cover. All data from the experiments were calibrated radiometrically to extract information during digital processing, besides an exhaustive field survey which was done simultaneously to SAR imaging, to know the physiognomy/structure of forest typology and to support the models produced for each case. The results of this series of experiments show advances at the techniques to treat SAR data, focusing on models of stand architecture and forest stock density. This will be helpful to increase the regional inventory and surveying procedures of forest conversion in the Brazilian territory in the near future.

  8. An Applied Image Processing for Radiographic Testing

    International Nuclear Information System (INIS)

    Ratchason, Surasak; Tuammee, Sopida; Srisroal Anusara

    2005-10-01

    An applied image processing for radiographic testing (RT) is desirable because it decreases time-consuming, decreases the cost of inspection process that need the experienced workers, and improves the inspection quality. This paper presents the primary study of image processing for RT-films that is the welding-film. The proposed approach to determine the defects on weld-images. The BMP image-files are opened and developed by computer program that using Borland C ++ . The software has five main methods that are Histogram, Contrast Enhancement, Edge Detection, Image Segmentation and Image Restoration. Each the main method has the several sub method that are the selected options. The results showed that the effective software can detect defects and the varied method suit for the different radiographic images. Furthermore, improving images are better when two methods are incorporated

  9. Application of spaceborne SAR data to uranium metallogenetic environment, condition and prognosis

    International Nuclear Information System (INIS)

    Huang Xianfang; Huang Shutao; Dong Wenming; Pan Wei; Fang Maolong; Xuan Yanxiu

    2001-01-01

    JERS-1 SAR data processing and data fusion with TM, airborne radioactive and magnetic survey data have been elaborated and image effects have been described in the paper. By means of the analysis of the processed images, the stratigraphy, structures (including faults and folds) and ore-controlling factors in the study area have successfully been interpreted; the underground water mobile characteristics have been discussed; and the metallogenetic environment and condition have been summarized. Based on above research results, the prospecting criteria have been provided and favorable sections have been suggested. The practice has indicated that the application of spaceborne SAR data to uranium reconnaissance and exploration has potential prospects

  10. Detection of Oil near Shorelines during the Deepwater Horizon Oil Spill Using Synthetic Aperture Radar (SAR

    Directory of Open Access Journals (Sweden)

    Oscar Garcia-Pineda

    2017-06-01

    Full Text Available During any marine oil spill, floating oil slicks that reach shorelines threaten a wide array of coastal habitats. To assess the presence of oil near shorelines during the Deepwater Horizon (DWH oil spill, we scanned the library of Synthetic Aperture Radar (SAR imagery collected during the event to determine which images intersected shorelines and appeared to contain oil. In total, 715 SAR images taken during the DWH spill were analyzed and processed, with 188 of the images clearly showing oil. Of these, 156 SAR images showed oil within 10 km of the shoreline with appropriate weather conditions for the detection of oil on SAR data. We found detectable oil in SAR images within 10 km of the shoreline from west Louisiana to west Florida, including near beaches, marshes, and islands. The high number of SAR images collected in Barataria Bay, Louisiana in 2010 allowed for the creation of a nearshore oiling persistence map. This analysis shows that, in some areas inside Barataria Bay, floating oil was detected on as many as 29 different days in 2010. The nearshore areas with persistent floating oil corresponded well with areas where ground survey crews discovered heavy shoreline oiling. We conclude that satellite-based SAR imagery can detect oil slicks near shorelines, even in sheltered areas. These data can help assess potential shoreline oil exposure without requiring boats or aircraft. This method can be particularly helpful when shoreline assessment crews are hampered by difficult access or, in the case of DWH, a particularly large spatial and temporal spill extent.

  11. Image processing on the image with pixel noise bits removed

    Science.gov (United States)

    Chuang, Keh-Shih; Wu, Christine

    1992-06-01

    Our previous studies used statistical methods to assess the noise level in digital images of various radiological modalities. We separated the pixel data into signal bits and noise bits and demonstrated visually that the removal of the noise bits does not affect the image quality. In this paper we apply image enhancement techniques on noise-bits-removed images and demonstrate that the removal of noise bits has no effect on the image property. The image processing techniques used are gray-level look up table transformation, Sobel edge detector, and 3-D surface display. Preliminary results show no noticeable difference between original image and noise bits removed image using look up table operation and Sobel edge enhancement. There is a slight enhancement of the slicing artifact in the 3-D surface display of the noise bits removed image.

  12. Emergency product generation for disaster management using RISAT and DMSAR quick look SAR processors

    Science.gov (United States)

    Desai, Nilesh; Sharma, Ritesh; Kumar, Saravana; Misra, Tapan; Gujraty, Virendra; Rana, SurinderSingh

    2006-12-01

    Since last few years, ISRO has embarked upon the development of two complex Synthetic Aperture Radar (SAR) missions, viz. Spaceborne Radar Imaging Satellite (RISAT) and Airborne SAR for Disaster Mangement (DMSAR), as a capacity building measure under country's Disaster Management Support (DMS) Program, for estimating the extent of damage over large areas (~75 Km) and also assess the effectiveness of the relief measures undertaken during natural disasters such as cyclones, epidemics, earthquakes, floods and landslides, forest fires, crop diseases etc. Synthetic Aperture Radar (SAR) has an unique role to play in mapping and monitoring of large areas affected by natural disasters especially floods, owing to its unique capability to see through clouds as well as all-weather imaging capability. The generation of SAR images with quick turn around time is very essential to meet the above DMS objectives. Thus the development of SAR Processors, for these two SAR systems poses considerable challenges and design efforts. Considering the growing user demand and inevitable necessity for a full-fledged high throughput processor, to process SAR data and generate image in real or near-real time, the design and development of a generic SAR Processor has been taken up and evolved, which will meet the SAR processing requirements for both Airborne and Spaceborne SAR systems. This hardware SAR processor is being built, to the extent possible, using only Commercial-Off-The-Shelf (COTS) DSP and other hardware plug-in modules on a Compact PCI (cPCI) platform. Thus, the major thrust has been on working out Multi-processor Digital Signal Processor (DSP) architecture and algorithm development and optimization rather than hardware design and fabrication. For DMSAR, this generic SAR Processor operates as a Quick Look SAR Processor (QLP) on-board the aircraft to produce real time full swath DMSAR images and as a ground based Near-Real Time high precision full swath Processor (NRTP). It will

  13. Seismic imaging beneath an InSAR anomaly in eastern Washington State: Shallow faulting associated with an earthquake swarm in a low-hazard area

    Science.gov (United States)

    Stephenson, William J.; Odum, Jackson K.; Wicks, Chuck; Pratt, Thomas L.; Blakely, Richard J.

    2016-01-01

    In 2001, a rare swarm of small, shallow earthquakes beneath the city of Spokane, Washington, caused ground shaking as well as audible booms over a five‐month period. Subsequent Interferometric Synthetic Aperture Radar (InSAR) data analysis revealed an area of surface uplift in the vicinity of the earthquake swarm. To investigate the potential faults that may have caused both the earthquakes and the topographic uplift, we collected ∼3  km of high‐resolution seismic‐reflection profiles to image the upper‐source region of the swarm. The two profiles reveal a complex deformational pattern within Quaternary alluvial, fluvial, and flood deposits, underlain by Tertiary basalts and basin sediments. At least 100 m of arching on a basalt surface in the upper 500 m is interpreted from both the seismic profiles and magnetic modeling. Two west‐dipping faults deform Quaternary sediments and project to the surface near the location of the Spokane fault defined from modeling of the InSAR data.

  14. The July 11, 1995 Myanmar-China earthquake: A representative event in the bookshelf faulting system of southeastern Asia observed from JERS-1 SAR images

    Science.gov (United States)

    Ji, Lingyun; Wang, Qingliang; Xu, Jing; Ji, Cunwei

    2017-03-01

    On July 11, 1995, an Mw 6.8 earthquake struck eastern Myanmar near the Chinese border; hereafter referred to as the 1995 Myanmar-China earthquake. Coseismic surface displacements associated with this event are identified from JERS-1 (Japanese Earth Resources Satellite-1) SAR (Synthetic Aperture Radar) images. The largest relative displacement reached 60 cm in the line-of-sight direction. We speculate that a previously unrecognized dextral strike-slip subvertical fault striking NW-SE was responsible for this event. The coseismic slip distribution on the fault planes is inverted based on the InSAR-derived deformation. The results indicate that the fault slip was confined to two lobes. The maximum slip reached approximately 2.5 m at a depth of 5 km in the northwestern part of the focal region. The inverted geodetic moment was approximately Mw = 6.69, which is consistent with seismological results. The 1995 Myanmar-China earthquake is one of the largest recorded earthquakes that has occurred around the "bookshelf faulting" system between the Sagaing fault in Myanmar and the Red River fault in southwestern China.

  15. Matching rendered and real world images by digital image processing

    Science.gov (United States)

    Mitjà, Carles; Bover, Toni; Bigas, Miquel; Escofet, Jaume

    2010-05-01

    Recent advances in computer-generated images (CGI) have been used in commercial and industrial photography providing a broad scope in product advertising. Mixing real world images with those rendered from virtual space software shows a more or less visible mismatching between corresponding image quality performance. Rendered images are produced by software which quality performance is only limited by the resolution output. Real world images are taken with cameras with some amount of image degradation factors as lens residual aberrations, diffraction, sensor low pass anti aliasing filters, color pattern demosaicing, etc. The effect of all those image quality degradation factors can be characterized by the system Point Spread Function (PSF). Because the image is the convolution of the object by the system PSF, its characterization shows the amount of image degradation added to any taken picture. This work explores the use of image processing to degrade the rendered images following the parameters indicated by the real system PSF, attempting to match both virtual and real world image qualities. The system MTF is determined by the slanted edge method both in laboratory conditions and in the real picture environment in order to compare the influence of the working conditions on the device performance; an approximation to the system PSF is derived from the two measurements. The rendered images are filtered through a Gaussian filter obtained from the taking system PSF. Results with and without filtering are shown and compared measuring the contrast achieved in different final image regions.

  16. Applied medical image processing a basic course

    CERN Document Server

    Birkfellner, Wolfgang

    2014-01-01

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

  17. Satellite SAR interferometric techniques applied to emergency mapping

    Science.gov (United States)

    Stefanova Vassileva, Magdalena; Riccardi, Paolo; Lecci, Daniele; Giulio Tonolo, Fabio; Boccardo Boccardo, Piero; Chiesa, Giuliana; Angeluccetti, Irene

    2017-04-01

    This paper aim to investigate the capabilities of the currently available SAR interferometric algorithms in the field of emergency mapping. Several tests have been performed exploiting the Copernicus Sentinel-1 data using the COTS software ENVI/SARscape 5.3. Emergency Mapping can be defined as "creation of maps, geo-information products and spatial analyses dedicated to providing situational awareness emergency management and immediate crisis information for response by means of extraction of reference (pre-event) and crisis (post-event) geographic information/data from satellite or aerial imagery". The conventional differential SAR interferometric technique (DInSAR) and the two currently available multi-temporal SAR interferometric approaches, i.e. Permanent Scatterer Interferometry (PSI) and Small BAseline Subset (SBAS), have been applied to provide crisis information useful for the emergency management activities. Depending on the considered Emergency Management phase, it may be distinguished between rapid mapping, i.e. fast provision of geospatial data regarding the area affected for the immediate emergency response, and monitoring mapping, i.e. detection of phenomena for risk prevention and mitigation activities. In order to evaluate the potential and limitations of the aforementioned SAR interferometric approaches for the specific rapid and monitoring mapping application, five main factors have been taken into account: crisis information extracted, input data required, processing time and expected accuracy. The results highlight that DInSAR has the capacity to delineate areas affected by large and sudden deformations and fulfills most of the immediate response requirements. The main limiting factor of interferometry is the availability of suitable SAR acquisition immediately after the event (e.g. Sentinel-1 mission characterized by 6-day revisiting time may not always satisfy the immediate emergency request). PSI and SBAS techniques are suitable to produce

  18. Image processing in nondestructive testing

    International Nuclear Information System (INIS)

    Janney, D.H.

    1976-01-01

    In those applications where the principal desire is for higher throughput, the problem often becomes one of automatic feature extraction and mensuration. Classically these problems can be approached by means of either an optical image processor or an analysis in the digital computer. Optical methods have the advantages of low cost and very high speed, but are often inflexible and are sometimes very difficult to implement due to practical problems. Computerized methods can be very flexible, they can use very powerful mathematical techniques, but usually are difficult to implement for very high throughput. Recent technological developments in microprocessors and in electronic analog image analyzers may furnish the key to resolving the shortcomings of the two classical methods of image analysis

  19. How Digital Image Processing Became Really Easy

    Science.gov (United States)

    Cannon, Michael

    1988-02-01

    In the early and mid-1970s, digital image processing was the subject of intense university and corporate research. The research lay along two lines: (1) developing mathematical techniques for improving the appearance of or analyzing the contents of images represented in digital form, and (2) creating cost-effective hardware to carry out these techniques. The research has been very effective, as evidenced by the continued decline of image processing as a research topic, and the rapid increase of commercial companies to market digital image processing software and hardware.

  20. Hybrid Pluggable Processing Pipeline (HyP3): A cloud-based infrastructure for generic processing of SAR data

    Science.gov (United States)

    Hogenson, K.; Arko, S. A.; Buechler, B.; Hogenson, R.; Herrmann, J.; Geiger, A.

    2016-12-01

    A problem often faced by Earth science researchers is how to scale algorithms that were developed against few datasets and take them to regional or global scales. One significant hurdle can be the processing and storage resources available for such a task, not to mention the administration of those resources. As a processing environment, the cloud offers nearly unlimited potential for compute and storage, with limited administration required. The goal of the Hybrid Pluggable Processing Pipeline (HyP3) project was to demonstrate the utility of the Amazon cloud to process large amounts of data quickly and cost effectively, while remaining generic enough to incorporate new algorithms with limited administration time or expense. Principally built by three undergraduate students at the ASF DAAC, the HyP3 system relies on core Amazon services such as Lambda, the Simple Notification Service (SNS), Relational Database Service (RDS), Elastic Compute Cloud (EC2), Simple Storage Service (S3), and Elastic Beanstalk. The HyP3 user interface was written using elastic beanstalk, and the system uses SNS and Lamdba to handle creating, instantiating, executing, and terminating EC2 instances automatically. Data are sent to S3 for delivery to customers and removed using standard data lifecycle management rules. In HyP3 all data processing is ephemeral; there are no persistent processes taking compute and storage resources or generating added cost. When complete, HyP3 will leverage the automatic scaling up and down of EC2 compute power to respond to event-driven demand surges correlated with natural disaster or reprocessing efforts. Massive simultaneous processing within EC2 will be able match the demand spike in ways conventional physical computing power never could, and then tail off incurring no costs when not needed. This presentation will focus on the development techniques and technologies that were used in developing the HyP3 system. Data and process flow will be shown

  1. Quantitative image processing in fluid mechanics

    Science.gov (United States)

    Hesselink, Lambertus; Helman, James; Ning, Paul

    1992-01-01

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

  2. Empirical wind retrieval model based on SAR spectrum measurements

    Science.gov (United States)

    Panfilova, Maria; Karaev, Vladimir; Balandina, Galina; Kanevsky, Mikhail; Portabella, Marcos; Stoffelen, Ad

    ambiguity from polarimetric SAR. A criterion based on the complex correlation coefficient between the VV and VH signals sign is applied to select the wind direction. An additional quality control on the wind speed value retrieved with the spectral method is applied. Here, we use the direction obtained with the spectral method and the backscattered signal for CMOD wind speed estimate. The algorithm described above may be refined by the use of numerous SAR data and wind measurements. In the present preliminary work the first results of SAR images combined with in situ data processing are presented. Our results are compared to the results obtained using previously developed models CMOD, C-2PO for VH polarization and statistical wind retrieval approaches [1]. Acknowledgments. This work is supported by the Russian Foundation of Basic Research (grants 13-05-00852-a). [1] M. Portabella, A. Stoffelen, J. A. Johannessen, Toward an optimal inversion method for synthetic aperture radar wind retrieval, Journal of geophysical research, V. 107, N C8, 2002

  3. SAR Subsets for Selected Field Sites, 2007-2010

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks...

  4. SAR Subsets for Selected Field Sites, 2007-2010

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including...

  5. Image processing techniques for remote sensing data

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.

    interpretation and for processing of scene data for autonomous machine perception. The technique of digital image processing are used for' automatic character/pattern recognition, industrial robots for product assembly and inspection, military recognizance... and spatial co-ordinates into discrete components. The mathematical concepts involved are the sampling and transform theory. Two dimensional transforms are used for image enhancement, restoration, encoding and description too. The main objective of the image...

  6. Detection of moving humans in UHF wideband SAR

    Science.gov (United States)

    Sjögren, Thomas K.; Ulander, Lars M. H.; Frölind, Per-Olov; Gustavsson, Anders; Stenström, Gunnar; Jonsson, Tommy

    2014-06-01

    In this paper, experimental results for UHF wideband SAR imaging of humans on an open field and inside a forest is presented. The results show ability to detect the humans and suggest possible ways to improve the results. In the experiment, single channel wideband SAR mode of the UHF UWB system LORA developed by Swedish Defence Research Agency (FOI). The wideband SAR mode used in the experiment was from 220 to 450 MHz, thus with a fractional bandwidth of 0.68. Three humans walking and one stationary were available in the scene with one of the walking humans in the forest. The signature of the human in the forest appeared on the field, due to azimuth shift from the positive range speed component. One human on the field and the one in the forest had approximately the same speed and walking direction. The signatures in the SAR image were compared as a function of integration time based on focusing using the average relative speed of these given by GPS logs. A signal processing gain was obtained for the human in forest until approximately 15 s and 35 s for the human on the field. This difference is likely explained by uneven terrain and trees in the way, causing a non-straight walking path.

  7. Intelligent medical image processing by simulated annealing

    International Nuclear Information System (INIS)

    Ohyama, Nagaaki

    1992-01-01

    Image processing is being widely used in the medical field and already has become very important, especially when used for image reconstruction purposes. In this paper, it is shown that image processing can be classified into 4 categories; passive, active, intelligent and visual image processing. These 4 classes are explained at first through the use of several examples. The results show that the passive image processing does not give better results than the others. Intelligent image processing, then, is addressed, and the simulated annealing method is introduced. Due to the flexibility of the simulated annealing, formulated intelligence is shown to be easily introduced in an image reconstruction problem. As a practical example, 3D blood vessel reconstruction from a small number of projections, which is insufficient for conventional method to give good reconstruction, is proposed, and computer simulation clearly shows the effectiveness of simulated annealing method. Prior to the conclusion, medical file systems such as IS and C (Image Save and Carry) is pointed out to have potential for formulating knowledge, which is indispensable for intelligent image processing. This paper concludes by summarizing the advantages of simulated annealing. (author)

  8. AUTOMATED WETLAND DELINEATION FROM MULTI-FREQUENCY AND MULTI-POLARIZED SAR IMAGES IN HIGH TEMPORAL AND SPATIAL RESOLUTION

    Directory of Open Access Journals (Sweden)

    L. Moser

    2016-06-01

    Full Text Available Water scarcity is one of the main challenges posed by the changing climate. Especially in semi-arid regions where water reservoirs are filled during the very short rainy season, but have to store enough water for the extremely long dry season, the intelligent handling of water resources is vital. This study focusses on Lac Bam in Burkina Faso, which is the largest natural lake of the country and of high importance for the local inhabitants for irrigated farming, animal watering, and extraction of water for drinking and sanitation. With respect to the competition for water resources an independent area-wide monitoring system is essential for the acceptance of any decision maker. The following contribution introduces a weather and illumination independent monitoring system for the automated wetland delineation with a high temporal (about two weeks and a high spatial sampling (about five meters. The similarities of the multispectral and multi-polarized SAR acquisitions by RADARSAT-2 and TerraSAR-X are studied as well as the differences. The results indicate that even basic approaches without pre-classification time series analysis or post-classification filtering are already enough to establish a monitoring system of prime importance for a whole region.

  9. Alteration zone Mapping in the Meiduk and Sar Cheshmeh Porphyry Copper Mining Districts of Iran using Advanced Land Imager (ALI Satellite Data

    Directory of Open Access Journals (Sweden)

    A. Beiranvand Pour

    2015-10-01

    Full Text Available This study evaluates the capability of Earth Observing-1 (EO1 Advanced Land Imager (ALI data for hydrothermal alteration mapping in the Meiduk and Sar Cheshmeh porphyry copper mining districts, SE Iran. Feature-oriented principal components selection, 4/2, 8/9, 5/4 band ratioing were applied to ALI data for enhancing the hydrothermally altered rocks associated with porphyry copper mineralization, lithological units and vegetation. Mixture-tuned matched-filtering (MTMF was tested to discriminate the hydrothermal alteration areas of porphyry copper mineralization from surrounding environment using the shortwave infrared bands of ALI. Results indicate that the tested methods are able to yield spectral information for identifying vegetation, iron oxide/hydroxide and clay minerals, lithological units and the discrimination of hydrothermally altered rocks from unaltered rocks using ALI data.

  10. Analysis of Variance in Statistical Image Processing

    Science.gov (United States)

    Kurz, Ludwik; Hafed Benteftifa, M.

    1997-04-01

    A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

  11. SAR Raw Data Generation for Complex Airport Scenes

    Directory of Open Access Journals (Sweden)

    Jia Li

    2014-10-01

    Full Text Available The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method.

  12. Change Detection with Polarimetric SAR Imagery for Nuclear Verification

    International Nuclear Information System (INIS)

    Canty, M.

    2015-01-01

    This paper investigates the application of multivariate statistical change detection with high-resolution polarimetric SAR imagery acquired from commercial satellite platforms for observation and verification of nuclear activities. A prototype software tool comprising a processing chain starting from single look complex (SLC) multitemporal data through to change detection maps is presented. Multivariate change detection algorithms applied to polarimetric SAR data are not common. This is because, up until recently, not many researchers or practitioners have had access to polarimetric data. However with the advent of several spaceborne polarimetric SAR instruments such as the Japanese ALOS, the Canadian Radarsat-2, the German TerraSAR-X, the Italian COSMO-SkyMed missions and the European Sentinal SAR platform, the situation has greatly improved. There is now a rich source of weather-independent satellite radar data which can be exploited for Nuclear Safeguards purposes. The method will also work for univariate data, that is, it is also applicable to scalar or single polarimetric SAR data. The change detection procedure investigated here exploits the complex Wishart distribution of dual and quad polarimetric imagery in look-averaged covariance matrix format in order to define a per-pixel change/no-change hypothesis test. It includes approximations for the probability distribution of the test statistic, and so permits quantitative significance levels to be quoted for change pixels. The method has been demonstrated previously with polarimetric images from the airborne EMISAR sensor, but is applied here for the first time to satellite platforms. In addition, an improved multivariate method is used to estimate the so-called equivalent number of looks (ENL), which is a critical parameter of the hypothesis test. (author)

  13. Stable image acquisition for mobile image processing applications

    Science.gov (United States)

    Henning, Kai-Fabian; Fritze, Alexander; Gillich, Eugen; Mönks, Uwe; Lohweg, Volker

    2015-02-01

    Today, mobile devices (smartphones, tablets, etc.) are widespread and of high importance for their users. Their performance as well as versatility increases over time. This leads to the opportunity to use such devices for more specific tasks like image processing in an industrial context. For the analysis of images requirements like image quality (blur, illumination, etc.) as well as a defined relative position of the object to be inspected are crucial. Since mobile devices are handheld and used in constantly changing environments the challenge is to fulfill these requirements. We present an approach to overcome the obstacles and stabilize the image capturing process such that image analysis becomes significantly improved on mobile devices. Therefore, image processing methods are combined with sensor fusion concepts. The approach consists of three main parts. First, pose estimation methods are used to guide a user moving the device to a defined position. Second, the sensors data and the pose information are combined for relative motion estimation. Finally, the image capturing process is automated. It is triggered depending on the alignment of the device and the object as well as the image quality that can be achieved under consideration of motion and environmental effects.

  14. Cellular automata in image processing and geometry

    CERN Document Server

    Adamatzky, Andrew; Sun, Xianfang

    2014-01-01

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

  15. ARTIP: Automated Radio Telescope Image Processing Pipeline

    Science.gov (United States)

    Sharma, Ravi; Gyanchandani, Dolly; Kulkarni, Sarang; Gupta, Neeraj; Pathak, Vineet; Pande, Arti; Joshi, Unmesh

    2018-02-01

    The Automated Radio Telescope Image Processing Pipeline (ARTIP) automates the entire process of flagging, calibrating, and imaging for radio-interferometric data. ARTIP starts with raw data, i.e. a measurement set and goes through multiple stages, such as flux calibration, bandpass calibration, phase calibration, and imaging to generate continuum and spectral line images. Each stage can also be run independently. The pipeline provides continuous feedback to the user through various messages, charts and logs. It is written using standard python libraries and the CASA package. The pipeline can deal with datasets with multiple spectral windows and also multiple target sources which may have arbitrary combinations of flux/bandpass/phase calibrators.

  16. Observation of a Large Landslide on La Reunion Island Using Differential Sar Interferometry (JERS and Radarsat and Correlation of Optical (Spot5 and Aerial Images

    Directory of Open Access Journals (Sweden)

    Christophe Delacourt

    2009-01-01

    Full Text Available Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C–band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr-1 was measured.

  17. Process-related deformation monitoring by PSI using high resolution space-based SAR data: a case study in Düsseldorf, Germany

    Science.gov (United States)

    Liu, D.; Sowter, A.; Niemeier, W.

    2014-07-01

    TerraSAR-X satellite SAR (Synthetic Aperture Radar) scenes have been analysed using Persistent Scatter Interferometry (PSI) approach to monitor a tunnelling process in Düsseldorf, Germany. The aim of this work is to detect the deformation of ground surface and structures above the tunnelling line during the tunnel excavation. In this study, the PSI approach integrated in the open source software package Stanford Method for Persistent Scatterers (StaMPS) was employed since it has shown significant advantages in obtaining Persistent Scatterers (PS). In order to protect the historic buildings in this region from subsidence-induced damages, a Tunnel Boring Machine (TBM) was used to restrain serious displacements during the tunnelling excavation, as well as compensation injections. Both surface uplifting and subsidence were observed during this tunnelling process, by a levelling survey and a validated PSI observation. It is concluded that sub-centimetre accuracy observations are achievable for process-related monitoring in urban areas, using the open source software package.

  18. On some applications of diffusion processes for image processing

    International Nuclear Information System (INIS)

    Morfu, S.

    2009-01-01

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

  19. The Groningen image processing system

    International Nuclear Information System (INIS)

    Allen, R.J.; Ekers, R.D.; Terlouw, J.P.

    1985-01-01

    This paper describes an interactive, integrated software and hardware computer system for the reduction and analysis of astronomical images. A short historical introduction is presented before some examples of the astonomical data currently handled by the system are shown. A description is given of the present hardware and software structure. The system is illustrated by describing its appearance to the user, to the applications programmer, and to the system manager. Some quantitative information on the size and cost of the system is given, and its good and bad features are discussed

  20. Process perspective on image quality evaluation

    Science.gov (United States)

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

    2008-01-01

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

  1. Multispectral image enhancement processing for microsat-borne imager

    Science.gov (United States)

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

    2017-10-01

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

  2. Imaging process and VIP engagement

    Directory of Open Access Journals (Sweden)

    Starčević Slađana

    2007-01-01

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

  3. Design for embedded image processing on FPGAs

    CERN Document Server

    Bailey, Donald G

    2011-01-01

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

  4. Crack Length Detection by Digital Image Processing

    DEFF Research Database (Denmark)

    Lyngbye, Janus; Brincker, Rune

    1990-01-01

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

  5. Crack Detection by Digital Image Processing

    DEFF Research Database (Denmark)

    Lyngbye, Janus; Brincker, Rune

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

  6. Algorithms for image processing and computer vision

    CERN Document Server

    Parker, J R

    2010-01-01

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

  7. Image processing and analysis software development

    International Nuclear Information System (INIS)

    Shahnaz, R.

    1999-01-01

    The work presented in this project is aimed at developing a software 'IMAGE GALLERY' to investigate various image processing and analysis techniques. The work was divided into two parts namely the image processing techniques and pattern recognition, which further comprised of character and face recognition. Various image enhancement techniques including negative imaging, contrast stretching, compression of dynamic, neon, diffuse, emboss etc. have been studied. Segmentation techniques including point detection, line detection, edge detection have been studied. Also some of the smoothing and sharpening filters have been investigated. All these imaging techniques have been implemented in a window based computer program written in Visual Basic Neural network techniques based on Perception model have been applied for face and character recognition. (author)

  8. Evaluation of the Wishart test statistics for polarimetric SAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    2003-01-01

    A test statistic for equality of two covariance matrices following the complex Wishart distribution has previously been used in new algorithms for change detection, edge detection and segmentation in polarimetric SAR images. Previously, the results for change detection and edge detection have been...... quantitatively evaluated. This paper deals with the evaluation of segmentation. A segmentation performance measure originally developed for single-channel SAR images has been extended to polarimetric SAR images, and used to evaluate segmentation for a merge-using-moment algorithm for polarimetric SAR data....

  9. Signal and image processing in medical applications

    CERN Document Server

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

    2016-01-01

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

  10. MR imaging of abnormal synovial processes

    International Nuclear Information System (INIS)

    Quinn, S.F.; Sanchez, R.; Murray, W.T.; Silbiger, M.L.; Ogden, J.; Cochran, C.

    1987-01-01

    MR imaging can directly image abnormal synovium. The authors reviewed over 50 cases with abnormal synovial processes. The abnormalities include Baker cysts, semimembranous bursitis, chronic shoulder bursitis, peroneal tendon ganglion cyst, periarticular abscesses, thickened synovium from rheumatoid and septic arthritis, and synovial hypertrophy secondary to Legg-Calve-Perthes disease. MR imaging has proved invaluable in identifying abnormal synovium, defining the extent and, to a limited degree, characterizing its makeup

  11. Earth Observation Services (Image Processing Software)

    Science.gov (United States)

    1992-01-01

    San Diego State University and Environmental Systems Research Institute, with other agencies, have applied satellite imaging and image processing techniques to geographic information systems (GIS) updating. The resulting images display land use and are used by a regional planning agency for applications like mapping vegetation distribution and preserving wildlife habitats. The EOCAP program provides government co-funding to encourage private investment in, and to broaden the use of NASA-developed technology for analyzing information about Earth and ocean resources.

  12. Morphology and probability in image processing

    International Nuclear Information System (INIS)

    Fabbri, A.G.

    1985-01-01

    The author presents an analysis of some concepts which relate morphological attributes of digital objects to statistically meaningful measures. Some elementary transformations of binary images are described and examples of applications are drawn from the geological and image analysis domains. Some of the morphological models applicablle in astronomy are discussed. It is shown that the development of new spatially oriented computers leads to more extensive applications of image processing in the geosciences

  13. Image processing with a cellular nonlinear network

    International Nuclear Information System (INIS)

    Morfu, S.

    2005-01-01

    A cellular nonlinear network (CNN) based on uncoupled nonlinear oscillators is proposed for image processing purposes. It is shown theoretically and numerically that the contrast of an image loaded at the nodes of the CNN is strongly enhanced, even if this one is initially weak. An image inversion can be also obtained without reconfiguration of the network whereas a gray levels extraction can be performed with an additional threshold filtering. Lastly, an electronic implementation of this CNN is presented

  14. Keynote presentation : SAR systems

    NARCIS (Netherlands)

    Halsema, D. van; Otten, M.P.G.; Maas, A.P.M.; Bolt, R.J.; Anitori, L.

    2011-01-01

    Synthetic Aperture Radar (SAR) systems are becoming increasingly important sensors in as well the military environment as in the civilian market. In this keynote presentation an overview will be given over more than 2 decades of SAR system∼ and SAR application development at TNO in the Netherlands.

  15. Selections from 2017: Image Processing with AstroImageJ

    Science.gov (United States)

    Kohler, Susanna

    2017-12-01

    Editors note:In these last two weeks of 2017, well be looking at a few selections that we havent yet discussed on AAS Nova from among the most-downloaded paperspublished in AAS journals this year. The usual posting schedule will resume in January.AstroImageJ: Image Processing and Photometric Extraction for Ultra-Precise Astronomical Light CurvesPublished January2017The AIJ image display. A wide range of astronomy specific image display options and image analysis tools are available from the menus, quick access icons, and interactive histogram. [Collins et al. 2017]Main takeaway:AstroImageJ is a new integrated software package presented in a publication led byKaren Collins(Vanderbilt University,Fisk University, andUniversity of Louisville). Itenables new users even at the level of undergraduate student, high school student, or amateur astronomer to quickly start processing, modeling, and plotting astronomical image data.Why its interesting:Science doesnt just happen the momenta telescope captures a picture of a distantobject. Instead, astronomical images must firstbe carefully processed to clean up thedata, and this data must then be systematically analyzed to learn about the objects within it. AstroImageJ as a GUI-driven, easily installed, public-domain tool is a uniquelyaccessible tool for thisprocessing and analysis, allowing even non-specialist users to explore and visualizeastronomical data.Some features ofAstroImageJ:(as reported by Astrobites)Image calibration:generate master flat, dark, and bias framesImage arithmetic:combineimages viasubtraction, addition, division, multiplication, etc.Stack editing:easily perform operations on a series of imagesImage stabilization and image alignment featuresPrecise coordinate converters:calculate Heliocentric and Barycentric Julian DatesWCS coordinates:determine precisely where atelescope was pointed for an image by PlateSolving using Astronomy.netMacro and plugin support:write your own macrosMulti-aperture photometry

  16. A gamma cammera image processing system

    International Nuclear Information System (INIS)

    Chen Weihua; Mei Jufang; Jiang Wenchuan; Guo Zhenxiang

    1987-01-01

    A microcomputer based gamma camera image processing system has been introduced. Comparing with other systems, the feature of this system is that an inexpensive microcomputer has been combined with specially developed hardware, such as, data acquisition controller, data processor and dynamic display controller, ect. Thus the process of picture processing has been speeded up and the function expense ratio of the system raised

  17. Mapping spatial patterns with morphological image processing

    Science.gov (United States)

    Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

    2006-01-01

    We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

  18. Apodized RFI filtering of synthetic aperture radar images

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2014-02-01

    Fine resolution Synthetic Aperture Radar (SAR) systems necessarily require wide bandwidths that often overlap spectrum utilized by other wireless services. These other emitters pose a source of Radio Frequency Interference (RFI) to the SAR echo signals that degrades SAR image quality. Filtering, or excising, the offending spectral contaminants will mitigate the interference, but at a cost of often degrading the SAR image in other ways, notably by raising offensive sidelobe levels. This report proposes borrowing an idea from nonlinear sidelobe apodization techniques to suppress interference without the attendant increase in sidelobe levels. The simple post-processing technique is termed Apodized RFI Filtering (ARF).

  19. Digital image processing in art conservation

    Czech Academy of Sciences Publication Activity Database

    Zitová, Barbara; Flusser, Jan

    č. 53 (2003), s. 44-45 ISSN 0926-4981 Institutional research plan: CEZ:AV0Z1075907 Keywords : art conservation * digital image processing * change detection Subject RIV: JD - Computer Applications, Robotics

  20. Dictionary of computer vision and image processing

    National Research Council Canada - National Science Library

    Fisher, R. B

    2014-01-01

    ... been identified for inclusion since the current edition was published. Revised to include an additional 1000 new terms to reflect current updates, which includes a significantly increased focus on image processing terms, as well as machine learning terms...

  1. Advanced Secure Optical Image Processing for Communications

    Science.gov (United States)

    Al Falou, Ayman

    2018-04-01

    New image processing tools and data-processing network systems have considerably increased the volume of transmitted information such as 2D and 3D images with high resolution. Thus, more complex networks and long processing times become necessary, and high image quality and transmission speeds are requested for an increasing number of applications. To satisfy these two requests, several either numerical or optical solutions were offered separately. This book explores both alternatives and describes research works that are converging towards optical/numerical hybrid solutions for high volume signal and image processing and transmission. Without being limited to hybrid approaches, the latter are particularly investigated in this book in the purpose of combining the advantages of both techniques. Additionally, pure numerical or optical solutions are also considered since they emphasize the advantages of one of the two approaches separately.

  2. Imaging partons in exclusive scattering processes

    Energy Technology Data Exchange (ETDEWEB)

    Diehl, Markus

    2012-06-15

    The spatial distribution of partons in the proton can be probed in suitable exclusive scattering processes. I report on recent performance estimates for parton imaging at a proposed Electron-Ion Collider.

  3. Fragmentation measurement using image processing

    Directory of Open Access Journals (Sweden)

    Farhang Sereshki

    2016-12-01

    Full Text Available In this research, first of all, the existing problems in fragmentation measurement are reviewed for the sake of its fast and reliable evaluation. Then, the available methods used for evaluation of blast results are mentioned. The produced errors especially in recognizing the rock fragments in computer-aided methods, and also, the importance of determination of their sizes in the image analysis methods are described. After reviewing the previous work done, an algorithm is proposed for the automated determination of rock particles’ boundary in the Matlab software. This method can determinate automatically the particles boundary in the minimum time. The results of proposed method are compared with those of Split Desktop and GoldSize software in two automated and manual states. Comparing the curves extracted from different methods reveals that the proposed approach is accurately applicable in measuring the size distribution of laboratory samples, while the manual determination of boundaries in the conventional software is very time-consuming, and the results of automated netting of fragments are very different with the real value due to the error in separation of the objects.

  4. On Processing Hexagonally Sampled Images

    Science.gov (United States)

    2011-07-01

    A. Approved for public release, distribution unlimited. (96ABW-2011-0325) Neuromorphic Infrared Sensor (NIFS) 31 DISTRIBUTION A. Approved...J ••• • Drawn chip size Focal plane size Focal plane resolution Pixel type Pixel pit ch Post -pixel circuitry Interface Process Chip ...analog out 12-bit command bus in two 6-bit words 8-bit digital out Optional 3 input chip select Optional analog out Alternat ive 12 bit input

  5. Processing of space images and geologic interpretation

    Energy Technology Data Exchange (ETDEWEB)

    Yudin, V S

    1981-01-01

    Using data for standard sections, a correlation was established between natural formations in geologic/geophysical dimensions and the form they take in the imaging. With computer processing, important data can be derived from the image. Use of the above correlations has allowed to make a number of preliminary classifications of tectonic structures, and to determine certain ongoing processes in the given section. The derived data may be used for search of useful minerals.

  6. Study on Processing Method of Image Shadow

    Directory of Open Access Journals (Sweden)

    Wang Bo

    2014-07-01

    Full Text Available In order to effectively remove disturbance of shadow and enhance robustness of information processing of computer visual image, this paper makes study on inspection and removal of image shadow. It makes study the continual removal algorithm of shadow based on integration, the illumination surface and texture, it respectively introduces their work principles and realization method, it can effectively carrying processing for shadow by test.

  7. Wave directional spectrum from SAR imagery

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    < 2m and the zero-crossing period during the satellite overpass is small (< 6s, �O�O < 60m). We therefore utilized the visit of one of the authors (Sarma) to the Southampton Oceanographic Centre, U.K., to procure two ERS-1 digital image mode SAR...-dimensional FFT as well as a computer program for downloading SAR data from CCT. Finally we owe a debt of gratitude to J C da Silva, Southampton Oceanographic Centre, U K for sharing some of his SAR data with us. References Allan T. D. (Ed) (1983...

  8. The InSAR Scientific Computing Environment (ISCE): A Python Framework for Earth Science

    Science.gov (United States)

    Rosen, P. A.; Gurrola, E. M.; Agram, P. S.; Sacco, G. F.; Lavalle, M.

    2015-12-01

    The InSAR Scientific Computing Environment (ISCE, funded by NASA ESTO) provides a modern computing framework for geodetic image processing of InSAR data from a diverse array of radar satellites and aircraft. ISCE is both a modular, flexible, and extensible framework for building software components and applications as well as a toolbox of applications for processing raw or focused InSAR and Polarimetric InSAR data. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. Components are independently configurable in a layered manner to provide maximum control. Polymorphism is used to define a workflow in terms of abstract facilities for each processing step that are realized by specific components at run-time. This enables a single workflow to work on either raw or focused data from all sensors. ISCE can serve as the core of a production center to process Level-0 radar data to Level-3 products, but is amenable to interactive processing approaches that allow scientists to experiment with data to explore new ways of doing science with InSAR data. The NASA-ISRO SAR (NISAR) Mission will deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystems. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these new data. NISAR will be but one mission in a constellation of radar satellites in the future delivering such data. ISCE currently supports all publicly available strip map mode space-borne SAR data since ERS and is expected to include support for upcoming missions. ISCE has been incorporated into two prototype cloud-based systems that have demonstrated its elasticity in addressing larger data processing problems in a "production" context and its ability to be

  9. Early skin tumor detection from microscopic images through image processing

    International Nuclear Information System (INIS)

    Siddiqi, A.A.; Narejo, G.B.; Khan, A.M.

    2017-01-01

    The research is done to provide appropriate detection technique for skin tumor detection. The work is done by using the image processing toolbox of MATLAB. Skin tumors are unwanted skin growth with different causes and varying extent of malignant cells. It is a syndrome in which skin cells mislay the ability to divide and grow normally. Early detection of tumor is the most important factor affecting the endurance of a patient. Studying the pattern of the skin cells is the fundamental problem in medical image analysis. The study of skin tumor has been of great interest to the researchers. DIP (Digital Image Processing) allows the use of much more complex algorithms for image processing, and hence, can offer both more sophisticated performance at simple task, and the implementation of methods which would be impossibly by analog means. It allows much wider range of algorithms to be applied to the input data and can avoid problems such as build up of noise and signal distortion during processing. The study shows that few works has been done on cellular scale for the images of skin. This research allows few checks for the early detection of skin tumor using microscopic images after testing and observing various algorithms. After analytical evaluation the result has been observed that the proposed checks are time efficient techniques and appropriate for the tumor detection. The algorithm applied provides promising results in lesser time with accuracy. The GUI (Graphical User Interface) that is generated for the algorithm makes the system user friendly. (author)

  10. Corner-point criterion for assessing nonlinear image processing imagers

    Science.gov (United States)

    Landeau, Stéphane; Pigois, Laurent; Foing, Jean-Paul; Deshors, Gilles; Swiathy, Greggory

    2017-10-01

    Range performance modeling of optronics imagers attempts to characterize the ability to resolve details in the image. Today, digital image processing is systematically used in conjunction with the optoelectronic system to correct its defects or to exploit tiny detection signals to increase performance. In order to characterize these processing having adaptive and non-linear properties, it becomes necessary to stimulate the imagers with test patterns whose properties are similar to the actual scene image ones, in terms of dynamic range, contours, texture and singular points. This paper presents an approach based on a Corner-Point (CP) resolution criterion, derived from the Probability of Correct Resolution (PCR) of binary fractal patterns. The fundamental principle lies in the respectful perception of the CP direction of one pixel minority value among the majority value of a 2×2 pixels block. The evaluation procedure considers the actual image as its multi-resolution CP transformation, taking the role of Ground Truth (GT). After a spatial registration between the degraded image and the original one, the degradation is statistically measured by comparing the GT with the degraded image CP transformation, in terms of localized PCR at the region of interest. The paper defines this CP criterion and presents the developed evaluation techniques, such as the measurement of the number of CP resolved on the target, the transformation CP and its inverse transform that make it possible to reconstruct an image of the perceived CPs. Then, this criterion is compared with the standard Johnson criterion, in the case of a linear blur and noise degradation. The evaluation of an imaging system integrating an image display and a visual perception is considered, by proposing an analysis scheme combining two methods: a CP measurement for the highly non-linear part (imaging) with real signature test target and conventional methods for the more linear part (displaying). The application to

  11. Rotation Covariant Image Processing for Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Henrik Skibbe

    2013-01-01

    Full Text Available With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

  12. Fingerprint image enhancement by differential hysteresis processing.

    Science.gov (United States)

    Blotta, Eduardo; Moler, Emilce

    2004-05-10

    A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

  13. Image processing system for flow pattern measurements

    International Nuclear Information System (INIS)

    Ushijima, Satoru; Miyanaga, Yoichi; Takeda, Hirofumi

    1989-01-01

    This paper describes the development and application of an image processing system for measurements of flow patterns occuring in natural circulation water flows. In this method, the motions of particles scattered in the flow are visualized by a laser light slit and they are recorded on normal video tapes. These image data are converted to digital data with an image processor and then transfered to a large computer. The center points and pathlines of the particle images are numerically analized, and velocity vectors are obtained with these results. In this image processing system, velocity vectors in a vertical plane are measured simultaneously, so that the two dimensional behaviors of various eddies, with low velocity and complicated flow patterns usually observed in natural circulation flows, can be determined almost quantitatively. The measured flow patterns, which were obtained from natural circulation flow experiments, agreed with photographs of the particle movements, and the validity of this measuring system was confirmed in this study. (author)

  14. Image processing for HTS SQUID probe microscope

    International Nuclear Information System (INIS)

    Hayashi, T.; Koetitz, R.; Itozaki, H.; Ishikawa, T.; Kawabe, U.

    2005-01-01

    An HTS SQUID probe microscope has been developed using a high-permeability needle to enable high spatial resolution measurement of samples in air even at room temperature. Image processing techniques have also been developed to improve the magnetic field images obtained from the microscope. Artifacts in the data occur due to electromagnetic interference from electric power lines, line drift and flux trapping. The electromagnetic interference could successfully be removed by eliminating the noise peaks from the power spectrum of fast Fourier transforms of line scans of the image. The drift between lines was removed by interpolating the mean field value of each scan line. Artifacts in line scans occurring due to flux trapping or unexpected noise were removed by the detection of a sharp drift and interpolation using the line data of neighboring lines. Highly detailed magnetic field images were obtained from the HTS SQUID probe microscope by the application of these image processing techniques

  15. The Dark Energy Survey Image Processing Pipeline

    Energy Technology Data Exchange (ETDEWEB)

    Morganson, E.; et al.

    2018-01-09

    The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a 5000 square degree survey of the southern sky in five optical bands (g,r,i,z,Y) to a depth of ~24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g,r,i,z) over 27 square degrees. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

  16. Brain's tumor image processing using shearlet transform

    Science.gov (United States)

    Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin; Korneeva, Anna; Kruglyakov, Alexey; Legalov, Alexander; Romanenko, Alexey; Zotin, Alexander

    2017-09-01

    Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

  17. SAR Ambiguity Study for the Cassini Radar

    Science.gov (United States)

    Hensley, Scott; Im, Eastwood; Johnson, William T. K.

    1993-01-01

    The Cassini Radar's synthetic aperture radar (SAR) ambiguity analysis is unique with respect to other spaceborne SAR ambiguity analyses owing to the non-orbiting spacecraft trajectory, asymmetric antenna pattern, and burst mode of data collection. By properly varying the pointing, burst mode timing, and radar parameters along the trajectory this study shows that the signal-to-ambiguity ratio of better than 15 dB can be achieved for all images obtained by the Cassini Radar.

  18. Training Convolutional Neural Networks for Translational Invariance on SAR ATR

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Engholm, Rasmus; Østergaard Pedersen, Morten

    2016-01-01

    In this paper we present a comparison of the robustness of Convolutional Neural Networks (CNN) to other classifiers in the presence of uncertainty of the objects localization in SAR image. We present a framework for simulating simple SAR images, translating the object of interest systematically...

  19. PSInSAR technology and its use for monitoring of the Earth's surface deformation; Technologia PSInSAR a jej vyuzitie na monitorovanie deformacii zemskeho povrchu

    Energy Technology Data Exchange (ETDEWEB)

    Batorova, K [Univerzita Komenskeho v Bratislave, Prirodovedecka fakulta, Katedra inzinierskej geologie, 84215 Bratislava (Slovakia)

    2012-04-25

    Method of permanent reflex points (PSInSAR) allows to monitor the time evolution of deformations of the Earth's surface with a millimeter precision. For deformation size determination there are used the maps of movement speed or time delay of line set of data that are obtained by evaluating of SAR images. SAR files must be processed using the basic mathematical calculation presented in the work, with an emphasis on the parameters used in geology. Extensive processing of multiple SAR imagery showed that they can be used during monitoring of the field with an accurate identification of the objects on the Earth's surface, which provide a stable reflection of radar rays transmitted from the satellite. These objects are known as permanent reflection points (PS). PS can be geo-referenced, allowing accurate determination of the movement size of the Earth's surface deformation. In this paper an example of using of PSInSAR technology for monitoring of slope movements on the territory of Slovakia is presented. (authors)

  20. Architecture Of High Speed Image Processing System

    Science.gov (United States)

    Konishi, Toshio; Hayashi, Hiroshi; Ohki, Tohru

    1988-01-01

    One of architectures for a high speed image processing system which corresponds to a new algorithm for a shape understanding is proposed. And the hardware system which is based on the archtecture was developed. Consideration points of the architecture are mainly that using processors should match with the processing sequence of the target image and that the developed system should be used practically in an industry. As the result, it was possible to perform each processing at a speed of 80 nano-seconds a pixel.