WorldWideScience

Sample records for sar image mosaics

  1. Mapping of oil spill environmental sensitivity index (ESI) in western Amazonia, Brazil, using USTC classification of dual season GRFM SAR image mosaics

    Energy Technology Data Exchange (ETDEWEB)

    Miranda, Fernando P. de [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas; Beisl, Carlos H.; Pedroso, Enrico C. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Centro Brasileiro de Recursos - RADARSAT

    2003-07-01

    This study focuses on improving information about oil spill environmental sensitivity in Western Amazonia, Brazil, using a pair of multi seasonal (1995 - low flood to 1996 - high flood) GRFM JERS-1 SAR mosaics. Fuzzy analysis is carried out to extract information about landscape modifications within half hydrological cycle. The oil spill hazard information derived from JERS-1 SAR data is straightforward to interpret and constitutes a representation of the original Environmental Sensitivity Index (ESI) product conceived by PETROBRAS. (author)

  2. A Review of Image Mosaicing Techniques

    OpenAIRE

    Vaghela, Dushyant; Naina, Prof. Kapildev

    2014-01-01

    Image Mosaicing is a method of constructing multiple images of the same scene into a larger image. The output of the image mosaic will be the union of two input images. Image-mosaicing algorithms are used to get mosaiced image. Image Mosaicing processed is basically divided in to 5 phases. Which includes; Feature point extraction, Image registration, Homography computation, Warping and Blending if Image. Various corner detection algorithm is being used for Feature extraction. This corner prod...

  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. Mars Digital Image Mosaic Globe

    Science.gov (United States)

    2000-01-01

    The photomosaic that forms the base for this globe was created by merging two global digital image models (DIM's) of Mars-a medium-resolution monochrome mosaic processed to emphasize topographic features and a lower resolution color mosaic emphasizing color and albedo variations.The medium-resolution (1/256 or roughly 231 m/pixel) monochromatic image model was constructed from about 6,000 images having resolutions of 150-350 m/pixel and oblique illumination (Sun 20 o -45 o above the horizon). Radiometric processing was intended to suppress or remove the effects of albedo variations through the use of a high-pass divide filter, followed by photometric normalization so that the contrast of a given topographic slope would be approximately the same in all images.The global color mosaic was assembled at 1/64 or roughly 864 m/pixel from about 1,000 red- and green-filter images having 500-1,000 m/pixel resolution. These images were first mosaiced in groups, each taken on a single orbit of the Viking spacecraft. The orbit mosaics were then processed to remove spatially and temporally varying atmospheric haze in the overlap regions. After haze removal, the per-orbit mosaics were photometrically normalized to equalize the contrast of albedo features and mosaiced together with cosmetic seam removal. The medium-resolution DIM was used for geometric control of this color mosaic. A green-filter image was synthesized by weighted averaging of the red- and violet-filter mosaics. Finally, the product seen here was obtained by multiplying each color image by the medium-resolution monochrome image. The color balance selected for images in this map series was designed to be close to natural color for brighter, redder regions, such as Arabia Terra and the Tharsis region, but the data have been stretched so that the relatively dark regions appear darker and less red than they actually are.The images are presented in a projection that portrays the entire surface of Mars in a manner

  5. SAR Image Enhancement using Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — In this paper, we propose a novel approach to reduce the noise in Synthetic Aperture Radar (SAR) images using particle filters. Interpretation of SAR images is a...

  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. SAR Image Complex Pixel Representations

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    Complex pixel values for Synthetic Aperture Radar (SAR) images of uniform distributed clutter can be represented as either real/imaginary (also known as I/Q) values, or as Magnitude/Phase values. Generally, these component values are integers with limited number of bits. For clutter energy well below full-scale, Magnitude/Phase offers lower quantization noise than I/Q representation. Further improvement can be had with companding of the Magnitude value.

  8. Spaceborne SAR Imaging Algorithm for Coherence Optimized.

    Directory of Open Access Journals (Sweden)

    Zhiwei Qiu

    Full Text Available This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR research and application.

  9. 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...... for the application of SAR data in the difficult process of map revision and updating....

  10. Refocusing vibrating targets in SAR images

    Science.gov (United States)

    Wang, Qi; Santhanam, Balu; Pepin, Matthew; Atwood, Tom; Hayat, Majeed M.

    2012-06-01

    In synthetic-aperture radar (SAR) returned signals, ground-target vibrations introduce a phase modulation that is linearly proportional to the vibration displacement. Such modulation, termed the micro-Doppler effect, introduces ghost targets along the azimuth direction in reconstructed SAR images that prevents SAR from forming focused images of the vibrating targets. Recently, a discrete fractional Fourier transform (DFrFT) based method was developed to estimate the vibration frequencies and instantaneous vibration accelerations of the vibrating targets from SAR returned signals. In this paper, a demodulation-based algorithm is proposed to reconstruct focused SAR images of vibrating targets by exploiting the estimation results of the DFrFT-based vibration estimation method. For a single-component harmonic vibration, the history of the vibration displacement is first estimated from the estimated vibration frequency and the instantaneous vibration accelerations. Then a reference signal whose phase is modulated by the estimated vibration displacement with a delay of 180 degree is constructed. After that, the SAR phase history from the vibration target is multiplied by the reference signal and the vibration-induced phase modulation is canceled. Finally, the SAR image containing the re-focused vibration target is obtained by applying the 2-D Fourier transform to the demodulated SAR phase history. This algorithm is applied to simulated SAR data and successfully reconstructs the SAR image containing the re-focused vibrating target.

  11. Infrared image mosaic using point feature operators

    Science.gov (United States)

    Huang, Zhen; Sun, Shaoyuan; Shen, Zhenyi; Hou, Junjie; Zhao, Haitao

    2016-10-01

    In this paper, we study infrared image mosaic around a single point of rotation, aiming at expanding the narrow view range of infrared images. We propose an infrared image mosaic method using point feature operators including image registration and image synthesis. Traditional mosaic algorithms usually use global image registration methods to extract the feature points in the global image, which cost too much time as well as considerable matching errors. To address this issue, we first roughly calculate the image shift amount using phase correlation and determine the overlap region between images, and then extract image features in overlap region, which shortens the registration time and increases the quality of feature points. We improve the traditional algorithm through increasing constraints of point matching based on prior knowledge of image shift amount based on which the weighted map is computed using fade in-out method. The experimental results verify that the proposed method has better real time performance and robustness.

  12. Composite SAR imaging using sequential joint sparsity

    Science.gov (United States)

    Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.

    2017-06-01

    This paper investigates accurate and efficient ℓ1 regularization methods for generating synthetic aperture radar (SAR) images. Although ℓ1 regularization algorithms are already employed in SAR imaging, practical and efficient implementation in terms of real time imaging remain a challenge. Here we demonstrate that fast numerical operators can be used to robustly implement ℓ1 regularization methods that are as or more efficient than traditional approaches such as back projection, while providing superior image quality. In particular, we develop a sequential joint sparsity model for composite SAR imaging which naturally combines the joint sparsity methodology with composite SAR. Our technique, which can be implemented using standard, fractional, or higher order total variation regularization, is able to reduce the effects of speckle and other noisy artifacts with little additional computational cost. Finally we show that generalizing total variation regularization to non-integer and higher orders provides improved flexibility and robustness for SAR imaging.

  13. Bistatic SAR: Signal Processing and Image Formation.

    Energy Technology Data Exchange (ETDEWEB)

    Wahl, Daniel E.; Yocky, David A.

    2014-10-01

    This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

  14. Document image mosaicing: A novel approach

    Indian Academy of Sciences (India)

    G Hemantha Kumar; P Shivakumara; D S Guru; P Nagabhushan

    2004-06-01

    There are situations where it is not possible to capture large documents with the given imaging media such as scanners or copying machines in a single stretch because of their inherent limitations. This results in capture of a large document in terms of split components of a document image. Hence, the need is to mosaic the split components into the original and put together the document image. In this paper, we present a novel and simple approach to mosaic two split images of a large document based on pixel value matching. The method compares the values of pixels in the columns of split images to identify the common or overlapping region (OR) in them, which helps in mosaicing of split images of a large document.

  15. Controlling Data Collection to Support SAR Image Rotation

    Science.gov (United States)

    Doerry, Armin W.; Cordaro, J. Thomas; Burns, Bryan L.

    2008-10-14

    A desired rotation of a synthetic aperture radar (SAR) image can be facilitated by adjusting a SAR data collection operation based on the desired rotation. The SAR data collected by the adjusted SAR data collection operation can be efficiently exploited to form therefrom a SAR image having the desired rotational orientation.

  16. Ionosphere correction algorithm for spaceborne SAR imaging

    Institute of Scientific and Technical Information of China (English)

    Lin Yang; Mengdao Xing; Guangcai Sun

    2016-01-01

    For spaceborne synthetic aperture radar (SAR) ima-ging, the dispersive ionosphere has significant effects on the pro-pagation of the low frequency (especial y P-band) radar signal. The ionospheric effects can be a significant source of the phase error in the radar signal, which causes a degeneration of the image quality in spaceborne SAR imaging system. The background ionospheric effects on spaceborne SAR through modeling and simulation are analyzed, and the qualitative and quantitative analysis based on the spatio-temporal variability of the ionosphere is given. A novel ionosphere correction algorithm (ICA) is proposed to deal with the ionospheric effects on the low frequency spaceborne SAR radar signal. With the proposed algorithm, the degradation of the image quality caused by the ionosphere is corrected. The simulation re-sults show the effectiveness of the proposed algorithm.

  17. Progress in Circular SAR Imaging Technique

    Directory of Open Access Journals (Sweden)

    Hong Wen

    2012-06-01

    Full Text Available Circular SAR (CSAR is a newly developed all-directional high resolution 3D imaging mode in recent years, to satisfy the demand of finer observation. The National Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences (MITL, IECAS, had the first test flight experiment in Aug. 2011 with a P-band full polarization SAR system, and successfully obtained the all-directional high resolution circular SAR image. The initial results show that CSAR technique has the encouraging potential capability in the fields of high precision mapping, disaster evaluation, resource management and the other related applications. This paper firstly makes a detailed discussion on the progress of circular SAR imaging technique, which emphases on the several airborne experiments performed these years to show CSAR’s attractive features, then studies and illustrates the key techniques, and finally discusses the development trends.

  18. Three-dimensional surface reconstruction from multistatic SAR images.

    Science.gov (United States)

    Rigling, Brian D; Moses, Randolph L

    2005-08-01

    This paper discusses reconstruction of three-dimensional surfaces from multiple bistatic synthetic aperture radar (SAR) images. Techniques for surface reconstruction from multiple monostatic SAR images already exist, including interferometric processing and stereo SAR. We generalize these methods to obtain algorithms for bistatic interferometric SAR and bistatic stereo SAR. We also propose a framework for predicting the performance of our multistatic stereo SAR algorithm, and, from this framework, we suggest a metric for use in planning strategic deployment of multistatic assets.

  19. Optimal Approach to SAR Image Despeckling

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Speckle filtering of synthetic aperture radar (SAR) images while preserving the spatial signal variability (texture and fine structures) still remains a challenge. Many algorithms have been proposed for the SAR imagery despeckling. However,simulated annealing (SA) method is one of excellent choices currently. A critical problem in the study on SA is to provide appropriate cooling schedules that ensure fast convergence to near-optimal solutions. This paper gives a new necessary and sufficient condition for the cooling schedule so that the algorithm state converges in all probability to the set of globally minimum cost states.Moreover, it constructs an appropriate objective function for SAR image despeckling. An experimental result of the actual SAR image processing is obtained.

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

  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...

  2. On Bistatic Forward-looking SAR Imaging

    OpenAIRE

    Vu, Viet Thuy; Pettersson, Mats

    2014-01-01

    Left/right ambiguity and low angular (azimuth) resolution are severe problems for monostatic forward-looking SAR imaging. It is strongly believed that these technical issues can definitely be solved with bistatic forward-looking SAR. The analysis presented in this paper points out that the left/right ambiguity problem still exits. However, an appropriate selection of the position of bistatic base line and antenna beamwidth allows us to conceal it. The paper also gives some recommendations whi...

  3. A modified algorithm for SAR parallel imaging

    Institute of Scientific and Technical Information of China (English)

    HU Ju-rong; WANG Fei; CAO Ning; LU Hao

    2009-01-01

    Synthetic aperture radar can provide two dimension images by converting the acquired echoed SAR signal to targets coordinate and reflectivity. With the advancement of sophisticated SAR signal processing, more and more SAR imaging methods have been proposed for synthetic aperture radar which works at near field and the Fresnel approximation is not appropriate. Time domain correlation is a kind of digital reconstruction method based on processing the synthetic aperture radar data in the two-dimensional frequency domain via Fourier transform. It reconstructs SAR image via simply correlation without any need for approximation or interpolation. But its high computational cost for correlation makes it unsuitable for real time imaging. In order to reduce the computational burden a modified algorithm about time domain correlation was given in this paper. It also can take full advantage of parallel computations of the imaging processor. Its practical implementation was proposed and the preliminary simulation results were presented. Simulation results show that the proposed algorithm is a computationally efficient way of implementing the reconstruction in real time SAR image processing.

  4. Estimating IMU heading error from SAR images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2009-03-01

    Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.

  5. Simulation Analysis of Cylindrical Panoramic Image Mosaic

    Directory of Open Access Journals (Sweden)

    ZHU Ningning

    2017-04-01

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

  6. The Landsat Image Mosaic of Antarctica

    Science.gov (United States)

    Bindschadler, R.; Vornberger, P.; Fleming, A.; Fox, A.; Mullins, J.; Binnie, D.; Paulsen, S.J.; Granneman, B.; Gorodetzky, D.

    2008-01-01

    The Landsat Image Mosaic of Antarctica (LIMA) is the first true-color, high-spatial-resolution image of the seventh continent. It is constructed from nearly 1100 individually selected Landsat-7 ETM+ scenes. Each image was orthorectified and adjusted for geometric, sensor and illumination variations to a standardized, almost seamless surface reflectance product. Mosaicing to avoid clouds produced a high quality, nearly cloud-free benchmark data set of Antarctica for the International Polar Year from images collected primarily during 1999-2003. Multiple color composites and enhancements were generated to illustrate additional characteristics of the multispectral data including: the true appearance of the surface; discrimination between snow and bare ice; reflectance variations within bright snow; recovered reflectance values in regions of sensor saturation; and subtle topographic variations associated with ice flow. LIMA is viewable and individual scenes or user defined portions of the mosaic are downloadable at http://lima.usgs.gov. Educational materials associated with LIMA are available at http://lima.nasa.gov.

  7. 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 sections...... of the object using a CAD-model. The raw measurements are input to a SAR system and terrain model, which models thermal noise, terrain clutter, and SAR focusing to produce synthetic SAR images. Examples of SAR images at 0.3m and 0.1m resolution, and a comparison with real SAR imagery from the MSTAR dataset...

  8. Fast SAR Imaging Algorithm for FLGPR

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A fast SAR imaging algorithm for near- field subsurface forward-looking ground penetrating radar (FLGPR) is presented. By using nonstationary convolution filter, the refocused image spectrum can be reconstructed directly from the backscattered signal spectrum of target area. The experimental results show the proposed method can fast achieve image refocusing. Also it has higher computational efficiency than the phase-shift migration approach and the delay-and-sum (DAS) approach.

  9. Multichannel imaging with the AMBER FMCW SAR

    NARCIS (Netherlands)

    Otten, M.P.G.; Rossum, W.L. van; Graaf, M.W. van der; Vlothuizen, W.J.; Tan, R.G.

    2014-01-01

    An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to achieve low power and advanced imaging SAR capabilities on small platform

  10. Multichannel imaging with the AMBER FMCW SAR

    NARCIS (Netherlands)

    Otten, M.P.G.; Rossum, W.L. van; Graaf, M.W. van der; Vlothuizen, W.J.; Tan, R.G.

    2014-01-01

    An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to achieve low power and advanced imaging SAR capabilities on small platform

  11. Multichannel imaging with the AMBER FMCW SAR

    NARCIS (Netherlands)

    Otten, M.P.G.; Rossum, W.L. van; Graaf, M.W. van der; Vlothuizen, W.J.; Tan, R.G.

    2014-01-01

    An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to achieve low power and advanced imaging SAR capabilities on small

  12. 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.

  13. Image Mosaicing Algorithm for Rolled Fingerprint Construction

    Institute of Scientific and Technical Information of China (English)

    贺迪; 荣钢; 周杰

    2002-01-01

    Fingerprint identification is one of the most important biometric authentication methods. However, current devices for recording digital fingerprints can only capture plain-touch fingerprints. Rolled fingerprints have much more information for recognition, so a method is needed to construct a rolled fingerprint from a series of plain-touch fingerprints. This paper presents a novel algorithm for image mosaicing for real time rolled fingerprint construction in which the images are assembled with corrections to create a smooth, non-fragmented rolled fingerprint in real time. Experimental results demonstrate its effectiveness by comparing it with other conventional algorithms.

  14. InSAR Forensics: Tracing InSAR Scatterers in High Resolution Optical Image

    Science.gov (United States)

    Wang, Yuanyuan; Zhu, XiaoXiang

    2015-05-01

    This paper presents a step towards a better interpretation of the scattering mechanism of different objects and their deformation histories in SAR interferometry (InSAR). The proposed technique traces individual SAR scatterer in high resolution optical images where their geometries, materials, and other properties can be better analyzed and classified. And hence scatterers of a same object can be analyzed in group, which brings us to a new level of InSAR deformation monitoring.

  15. SAR-SIFT: A SIFT-LIKE ALGORITHM FOR SAR IMAGES

    OpenAIRE

    Dellinger, Flora; Delon, Julie; Gousseau, Yann; Michel, Julien; Tupin, Florence

    2015-01-01

    International audience; The Scale Invariant Feature Transform (SIFT) algorithm is widely used in computer vision to match features between images or to localize and recognize objets. However, mostly because of speckle noise, it does not perform well on synthetic aperture radar (SAR) images. We present here an improvement of this algorithm for SAR images, named SAR-SIFT. A new gradient computation, yielding an orientation and a magnitude robust to speckle noise, is first introduced. It is then...

  16. Non-parametric partitioning of SAR images

    Science.gov (United States)

    Delyon, G.; Galland, F.; Réfrégier, Ph.

    2006-09-01

    We describe and analyse a generalization of a parametric segmentation technique adapted to Gamma distributed SAR images to a simple non parametric noise model. The partition is obtained by minimizing the stochastic complexity of a quantized version on Q levels of the SAR image and lead to a criterion without parameters to be tuned by the user. We analyse the reliability of the proposed approach on synthetic images. The quality of the obtained partition will be studied for different possible strategies. In particular, one will discuss the reliability of the proposed optimization procedure. Finally, we will precisely study the performance of the proposed approach in comparison with the statistical parametric technique adapted to Gamma noise. These studies will be led by analyzing the number of misclassified pixels, the standard Hausdorff distance and the number of estimated regions.

  17. NOAA-AVHRR image mosaics applied to vegetation identification

    Science.gov (United States)

    de Almeida, Maria d. G.; Ruddorff, Bernardo F.; Shimabukuro, Yosio E.

    2001-06-01

    In this paper, the maximum-value composite of images procedure from Normalized Difference Vegetation Index is used to get a cloud free image mosaic. The image mosaic is used to identify vegetation targets such as tropical forest, savanna and caatinga as well to make the vegetation cover mapping of Minas Gerais state, Brazil.

  18. Image blending techniques and their application in underwater mosaicing

    CERN Document Server

    Prados, Ricard; Neumann, László

    2014-01-01

    This work proposes strategies and solutions to tackle the problem of building photo-mosaics of very large underwater optical surveys, presenting contributions to the image preprocessing, enhancing and blending steps, and resulting in an improved visual quality of the final photo-mosaic. The text opens with a comprehensive review of mosaicing and blending techniques, before proposing an approach for large scale underwater image mosaicing and blending. In the image preprocessing step, a depth dependent illumination compensation function is used to solve the non-uniform illumination appearance du

  19. SAR Image Texture Analysis of Oil Spill

    Science.gov (United States)

    Ma, Long; Li, Ying; Liu, Yu

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

  20. Unparallel trajectory bistatic spotlight SAR imaging

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; JING Wei; XING MengDao; BAO Zheng

    2009-01-01

    A new approach for unparallel trajectory bistatic spotlight SAR imaging is proposed. The approach utilizes the concept of instantaneous Doppler wavenumber and introduces two variants, the sum-range and subtraction-range, to develop the 2D frequency analytical formula. Based on the assumption of plane wavefront, the transmitting and receiving Doppler are separated and formulated via series reversion. And frequency scaling is applied to focus image. The algorithm is with high computational efficiency, and provides well focus for limited scene imaging. Simulation result confirms the validity of the approach.

  1. Coastline detection in SAR images using discriminant cuts segmentation

    Science.gov (United States)

    Ding, Xianwen; Zou, Xiaolin; Yu, Tan

    2016-11-01

    The discriminant cut algorithm is used to detect coastlines in synthetic aperture radar (SAR) images. The proposed approach is a region-based one, which is able to capture and utilize spatial information in the image. The real SAR images, e.g. ALOS-1 PALSAR and COSMO-SkyMed SAR images, together with in-situ GPS data were collected and used to validate the performance of the proposed approach for coastline detection in SAR images. The accuracy is better than 4 times the image resolution. The efficiency is also tested.

  2. Image mosaic method based on SIFT features of line segment.

    Science.gov (United States)

    Zhu, Jun; Ren, Mingwu

    2014-01-01

    This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

  3. The first Sentinel-1 SAR image of a typhoon

    Institute of Scientific and Technical Information of China (English)

    LI Xiaofeng

    2015-01-01

    In this note, we present the first Sentinel-1 synthetic aperture radar (SAR) typhoon image acquired in the northwest Pacific on October 4, 2014. The eye shape and sea surface wind patterns associated with Typhoon Phanfone are clearly shown in the high-quality SAR image. SAR winds retrieval procedure was given but the actual wind estimates will only be available after the European Space Agency (ESA) releases the official calibration coefficients in order to accurately derive the SAR-measured normalized radar cross section. This study demonstrates the advantage of Sentinel-1 SAR with regards to imaging fine scale typhoon patterns on the sea surface beneath storm clouds. This paper also advocates the use of Sentinel-1 SAR data that is made freely and openly available worldwide for the first time in civilian SAR history.

  4. 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

  5. SAR-PC: Edge Detection in SAR Images via an Advanced Phase Congruency Model

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2017-02-01

    Full Text Available Edge detection in Synthetic Aperture Radar (SAR images has been a challenging task due to the speckle noise. Ratio-based edge detectors are robust operators for SAR images that provide constant false alarm rates, but they are only optimal for step edges. Edge detectors developed by the phase congruency model provide the identification of different types of edge features, but they suffer from speckle noise. By combining the advantages of the two edge detectors, we propose a SAR phase congruency detector (SAR-PC. Firstly, an improved local energy model for SAR images is obtained by replacing the convolution of raw image and the quadrature filters by the ratio responses. Secondly, a new noise level is estimated for the multiplicative noise. Substituting the SAR local energy and the new noise level into the phase congruency model, SAR-PC is derived. Edge response corresponds to the max moment of SAR-PC. We compare the proposed detector with the ratio-based edge detectors and the phase congruency edge detectors. Receiver Operating Characteristic (ROC curves and visual effects are used to evaluate the performance. Experimental results of simulated images and real-world images show that the proposed edge detector is robust to speckle noise and it provides a consecutive edge response.

  6. Granular computing in mosaicing of images from capsule endoscopy

    OpenAIRE

    Maciura, Lukasz; Bazan, Jan G.

    2015-01-01

    This article introduces methods for modeling compound granules used in algorithms which could successfully construct a mosaic from the images coming from an endoscope capsule. In order to apply the algorithm, combined images must have a common area where the correspondence of points is determined. That allows to determine the transformation parameters to compensate movement of the capsule that occurs between moments when the mosaic images were acquired. The developed algorithm for images from...

  7. Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern

    Science.gov (United States)

    Doerry, Armin W.

    2013-04-30

    Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.

  8. Parallel-Processing Software for Creating Mosaic Images

    Science.gov (United States)

    Klimeck, Gerhard; Deen, Robert; McCauley, Michael; DeJong, Eric

    2008-01-01

    A computer program implements parallel processing for nearly real-time creation of panoramic mosaics of images of terrain acquired by video cameras on an exploratory robotic vehicle (e.g., a Mars rover). Because the original images are typically acquired at various camera positions and orientations, it is necessary to warp the images into the reference frame of the mosaic before stitching them together to create the mosaic. [Also see "Parallel-Processing Software for Correlating Stereo Images," Software Supplement to NASA Tech Briefs, Vol. 31, No. 9 (September 2007) page 26.] The warping algorithm in this computer program reflects the considerations that (1) for every pixel in the desired final mosaic, a good corresponding point must be found in one or more of the original images and (2) for this purpose, one needs a good mathematical model of the cameras and a good correlation of individual pixels with respect to their positions in three dimensions. The desired mosaic is divided into slices, each of which is assigned to one of a number of central processing units (CPUs) operating simultaneously. The results from the CPUs are gathered and placed into the final mosaic. The time taken to create the mosaic depends upon the number of CPUs, the speed of each CPU, and whether a local or a remote data-staging mechanism is used.

  9. An Optical Flow Method Applied to Co-Registration of Remote Sensing Images: Example for SAR/SAR, SAR/LIDAR, SAR/Optical Images of BIOSAR 2010 Campaign

    Science.gov (United States)

    Colin-Koeniguer, Elise

    2016-08-01

    This article proposes an optical flow type method for coregistration of forest remote sensing images. The principle of the algorithm called GeFolki is first explained. Results are shown on the images of the BioSAR 3 campaign, for the production of SAR interferograms, the coregistration a SAR and LIDAR image, and the coregistration an optical image and SAR image.The advantages of such an algorithm over conventional algorithms are explained. Finally, we propose various applications within the operating data for future BIOMASS mission: massive interferometry, ground truth production, upscaling by fusion of LIDAR and SAR data, and image mining.

  10. Speckle Suppression Method for SAR Image

    Directory of Open Access Journals (Sweden)

    Jiming Guo

    2013-04-01

    Full Text Available In this study, a new speckle reduction method was proposed in terms of by Bidimensional Empirical Mode Decomposition (BEMD. In this method, the SAR image containing speckle noise was decomposed into a number of elementary components by using BEMD and then the extremal points are done the boundary equivalent extension after screening and the residual continue to be done the boundary equivalent extension until screening is completed, finally, the image was reconstructed, which reduced the speckle noise. Experimental results show that this method has good effect on suppressing speckle noise, compared to the average filter, median filter and gaussian filter and has advantages of sufficiently retaining edge and detail information while suppressing speckle noise.

  11. SAR Image Desp eckling by Sparse Reconstruction Based on Shearlets

    Institute of Scientific and Technical Information of China (English)

    JI Jian; LI Xiao; XU Shuang-Xing; LIU Huan; HUANG Jing-Jing

    2015-01-01

    Synthetic aperture radar (SAR) image is usually polluted by multiplicative speckle noise, which can affect further processing of SAR image. This paper presents a new approach for multiplicative noise removal in SAR images based on sparse coding by shearlets filtering. First, a SAR despeckling model is built by the theory of compressed sensing (CS). Secondly, obtain shearlets coefficient through shearlet transform, each scale coefficient is represented as a unit. For each unit, sparse coefficient is iteratively estimated by using Bayesian estimation based on shearlets domain. The represented units are finally collaboratively aggregated to construct the despeckling image. Our results in SAR image despeckling show the good performance of this algorithm, and prove that the algorithm proposed is robustness to noise, which is not only good for reducing speckle, but also has an advantage in holding information of the edge.

  12. Optical flow with structure information for epithelial image mosaicing.

    Science.gov (United States)

    Ali, Sharib; Faraz, Khuram; Daul, Christian; Blondel, Walter

    2015-01-01

    Mosaicing of biological tissue surfaces is challenging due to the weak image textures. This contribution presents a mosaicing algorithm based on a robust and accurate variational optical flow scheme. A Riesz pyramid based multiscale approach aims at overcoming the "flattening-out" problem at coarser levels. Moreover, the structure information present in images of epithelial surfaces is incorporated into the data-term to improve the algorithm robustness. The algorithm accuracy is first assessed with simulated sequences and then used for mosaicing standard clinical endoscopic data.

  13. A beamforming algorithm for bistatic SAR image formation.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David Alan; Wahl, Daniel Eugene; Jakowatz, Charles V., Jr.

    2010-03-01

    Beamforming is a methodology for collection-mode-independent SAR image formation. It is essentially equivalent to backprojection. The authors have in previous papers developed this idea and discussed the advantages and disadvantages of the approach to monostatic SAR image formation vis--vis the more standard and time-tested polar formatting algorithm (PFA). In this paper we show that beamforming for bistatic SAR imaging leads again to a very simple image formation algorithm that requires a minimal number of lines of code and that allows the image to be directly formed onto a three-dimensional surface model, thus automatically creating an orthorectified image. The same disadvantage of beamforming applied to monostatic SAR imaging applies to the bistatic case, however, in that the execution time for the beamforming algorithm is quite long compared to that of PFA. Fast versions of beamforming do exist to help alleviate this issue. Results of image reconstructions from phase history data are presented.

  14. A beamforming algorithm for bistatic SAR image formation

    Science.gov (United States)

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

    2010-04-01

    Beamforming is a methodology for collection-mode-independent SAR image formation. It is essentially equivalent to backprojection. The authors have in previous papers developed this idea and discussed the advantages and disadvantages of the approach to monostatic SAR image formation vis-à-vis the more standard and time-tested polar formatting algorithm (PFA). In this paper we show that beamforming for bistatic SAR imaging leads again to a very simple image formation algorithm that requires a minimal number of lines of code and that allows the image to be directly formed onto a three-dimensional surface model, thus automatically creating an orthorectified image. The same disadvantage of beamforming applied to monostatic SAR imaging applies to the bistatic case, however, in that the execution time for the beamforming algorithm is quite long compared to that of PFA. Fast versions of beamforming do exist to help alleviate this issue. Results of image reconstructions from phase history data are presented.

  15. The Accuratre Signal Model and Imaging Processing in Geosynchronous SAR

    Science.gov (United States)

    Hu, Cheng

    With the development of synthetic aperture radar (SAR) application, the disadvantage of low earth orbit (LEO) SAR becomes more and more apparent. The increase of orbit altitude can shorten the revisit time and enlarge the coverage area in single look, and then satisfy the application requirement. The concept of geosynchronous earth orbit (GEO) SAR system is firstly presented and deeply discussed by K.Tomiyasi and other researchers. A GEO SAR, with its fine temporal resolution, would overcome the limitations of current imaging systems, allowing dense interpretation of transient phenomena as GPS time-series analysis with a spatial density several orders of magnitude finer. Until now, the related literatures about GEO SAR are mainly focused in the system parameter design and application requirement. As for the signal characteristic, resolution calculation and imaging algorithms, it is nearly blank in the related literatures of GEO SAR. In the LEO SAR, the signal model analysis adopts the `Stop-and-Go' assumption in general, and this assumption can satisfy the imaging requirement in present advanced SAR system, such as TerraSAR, Radarsat2 and so on. However because of long propagation distance and non-negligible earth rotation, the `Stop-and-Go' assumption does not exist and will cause large propagation distance error, and then affect the image formation. Furthermore the long propagation distance will result in the long synthetic aperture time such as hundreds of seconds, therefore the linear trajectory model in LEO SAR imaging will fail in GEO imaging, and the new imaging model needs to be proposed for the GEO SAR imaging processing. In this paper, considering the relative motion between satellite and earth during signal propagation time, the accurate analysis method for propagation slant range is firstly presented. Furthermore, the difference between accurate analysis method and `Stop-and-Go' assumption is analytically obtained. Meanwhile based on the derived

  16. SAR Image Segmentation using Vector Quantization Technique on Entropy Images

    CERN Document Server

    Kekre, H B; Sarode, Tanuja K

    2010-01-01

    The development and application of various remote sensing platforms result in the production of huge amounts of satellite image data. Therefore, there is an increasing need for effective querying and browsing in these image databases. In order to take advantage and make good use of satellite images data, we must be able to extract meaningful information from the imagery. Hence we proposed a new algorithm for SAR image segmentation. In this paper we propose segmentation using vector quantization technique on entropy image. Initially, we obtain entropy image and in second step we use Kekre's Fast Codebook Generation (KFCG) algorithm for segmentation of the entropy image. Thereafter, a codebook of size 128 was generated for the Entropy image. These code vectors were further clustered in 8 clusters using same KFCG algorithm and converted into 8 images. These 8 images were displayed as a result. This approach does not lead to over segmentation or under segmentation. We compared these results with well known Gray L...

  17. Investigation on Fine Registration for SAR and Optical Image

    Directory of Open Access Journals (Sweden)

    You Hong-jian

    2014-02-01

    Full Text Available The registration of SAR and optical remote sensing image is the basise for fusing of multi-source image and comprehensive analysis. In this paper a new fine registration method for SAR and optical image is proposed. Firstly, three to four corresponding points are selected manually to realize a coarse registration that eliminates the differences in scale and rotation. Many characteristic points in the optical image are detected and the corresponding points in SAR image are extracted using normalized gradient correlations based on the different gradients by operators. An irregular triangle network is constructed using these corresponding points and each triangle region is finely registered. Finally SAR image and optical image are finely registered. Experiment and processed results demonstrate the feasibility of this method.

  18. The ONERA Airborne Multi Frequency SAR Imaging Systems (PREPRINT)

    Science.gov (United States)

    2014-10-09

    The ONERA Airborne Multi-Frequency SAR Imaging Systems Olivier Ruault du Plessis Electromagnetism and Radar Department ONERA Salon de...Provence FRANCE Olivier.Ruault_du_Plessis@onera.fr Philippe Dreuillet Electromagnetism and Radar Department ONERA Palaiseau FRANCE...Philippe.Dreuillet@onera.fr Abstract—RAMSES-NG and SETHI, the airborne SAR systems developed by ONERA , integrate new generation of radar and optronics

  19. Classification of Targets in SAR Images Using ISAR Data

    NARCIS (Netherlands)

    Wit, J.J.M. de; Dekker, R.J.; Broek, A.C. van den

    2005-01-01

    Feature-based classification of targets in SAR images by using ISAR measurements was studied, based on polarimetric SAR and ISAR data acquired with the MEMPHIS radar system of FGAN-FHR. The data contained one T-72 battle tank, one BMP combat vehicle, and several confusers. The resolution was 75 cm.

  20. 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.

  1. 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...... matrices, and by applying a set of small orientation-dependent filters in an iterative scheme, the input image becomes highly filtered while maintaining most of the structures in the scene. Results using multi-look polarimetric C-band data from the Danish airborne polarimetric SAR, EMISAR, are presented....

  2. 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.

  3. Image Mosaic Method Based on SIFT Features of Line Segment

    Directory of Open Access Journals (Sweden)

    Jun Zhu

    2014-01-01

    Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

  4. Road network extraction in classified SAR images using genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    肖志强; 鲍光淑; 蒋晓确

    2004-01-01

    Due to the complicated background of objectives and speckle noise, it is almost impossible to extract roads directly from original synthetic aperture radar(SAR) images. A method is proposed for extraction of road network from high-resolution SAR image. Firstly, fuzzy C means is used to classify the filtered SAR image unsupervisedly, and the road pixels are isolated from the image to simplify the extraction of road network. Secondly, according to the features of roads and the membership of pixels to roads, a road model is constructed, which can reduce the extraction of road network to searching globally optimization continuous curves which pass some seed points. Finally, regarding the curves as individuals and coding a chromosome using integer code of variance relative to coordinates, the genetic operations are used to search global optimization roads. The experimental results show that the algorithm can effectively extract road network from high-resolution SAR images.

  5. Image automatic mosaics based on contour phase correlation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jing; HU Zhiping; LIU Zhitai; OU Zongying

    2007-01-01

    The image planar mosaics is studied,and an image automatic mosaics algorithm on the basis of contour phase correlation is proposed in this paper.To begin with,by taking into account mere translations and rotations between images,a contour phase correlation algorithm is used to realize the preliminary alignments of images,and the initial projective transformation matrices are obtained.Then,an optimization algorithm is used to optimize the initial projective transformation matrices,and complete the precise image mosaics.The contour phase correlation is an improvement on the conventional phase correlation in two aspects:First,the contours of images are extracted,and the phase correlation is applied to the contours of images instead of the whole original images;Second,when there are multiple peak values approximate to the maximum peak value in the δ function array,their corresponding translations can be regarded as candidate translations and calculated separately,and the best translation can be determined by the optimization of conformability of two images in the overlapping area.The running results show that the proposed algorithm can consistently yield high-quality mosaics,even in the cases of poor or differential lighting conditions,existences of minor rotations,and other complicated displacements between images.

  6. A Review of Spaceborne SAR Algorithm for Image Formation

    Directory of Open Access Journals (Sweden)

    Li Chun-sheng

    2013-03-01

    Full Text Available This paper firstly reviews the history and trends in development of spaceborne Synthetic Aperture Radar (SAR satellite technology in American and European countries. Besides, the basic information of the launched satellites and the future satellite plans are introduced. Then this paper summaries and assorts the imaging algorithm of spaceborn SAR satellite and analyzes the advantages and disadvantages of each algorithm. Moreover, the scope and the application status of each algorithm are presented. And then the paper elaborates trends of SAR imaging algorithm, which mainly introduces the algorithms based on compressive sensing theory and new image modes, and the results of simulation are also illustrated. At last, the paper summaries the development direction of spaceborne SAR imaging algorithm.

  7. SAR Imaging of Moving Targets via Compressive Sensing

    CERN Document Server

    Wang, Jun; Zhang, Hao; Wang, Xiqin

    2011-01-01

    An algorithm based on compressive sensing (CS) is proposed for synthetic aperture radar (SAR) imaging of moving targets. The received SAR echo is decomposed into the sum of basis sub-signals, which are generated by discretizing the target spatial domain and velocity domain and synthesizing the SAR received data for every discretized spatial position and velocity candidate. In this way, the SAR imaging problem is converted into sub-signal selection problem. In the case that moving targets are sparsely distributed in the observed scene, their reflectivities, positions and velocities can be obtained by using the CS technique. It is shown that, compared with traditional algorithms, the target image obtained by the proposed algorithm has higher resolution and lower side-lobe while the required number of measurements can be an order of magnitude less than that by sampling at Nyquist sampling rate. Moreover, multiple targets with different speeds can be imaged simultaneously, so the proposed algorithm has higher eff...

  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. A Study on Space-Borne SAR Mosaic Mode for an Agile Satellite%基于敏捷卫星平台的星载SAR Mosaic模式研究

    Institute of Scientific and Technical Information of China (English)

    韩晓磊; 李世强; 王宇; 韩晓东; 禹卫东

    2013-01-01

    Mosaic模式是聚束和ScanSAR的混合模式,能同时实现高分辨率、大场景成像.提出了一种易实现的Mosaic模式,它的距离向波束切换通过电扫描完成,方位向波束扫描通过机械扫描实现.敏捷卫星能通过控制俯仰机动,方便地实现方位向机械扫描,适于实施这种Mosaic模式.针对这种Mosaic模式的特点,提出了一种新的系统设计方法.该方法从零斜视角位置开始,递推求解一系列关于Burst斜视角和驻留时间的非线性方程组,得到系统参数和时间分配方案.此外,还提出了一种基于等效展宽天线方向图的Mosaic模式性能参数近似计算方法,它能直观、便利地得到Mosaic模式各种性能参数.%The Mosaic mode is a hybrid mode of spotlight and ScanSAR,and it can image a large coverage at a high resolution.In the paper,an easily realized Mosaic mode is proposed.In the mode,the beam switching in range is realized by electrical beam steering,whereas the beam steering in azimuth is realized by mechanical beam steering.The agile satellite can realize the mechanical beam steering by pitching maneuver expediently.Thus,it is fit for the implementation of the Mosaic mode.In this paper,a new system design method is presented for the Mosaic mode.Beginning with the broadside position,the nonlinear system in the unknown squint angle and dwell time of the burst is iteratively solved.In this way,the system parameters and timeline of the Mosaic mode are obtained.Moreover,a new approximate computation method for the performance parameters is obtained based on the equivalent stretch of the azimuth antenna pattern.It can achieve the performance parameters of the Mosaic mode visually and expediently.

  10. Noise Removal in SAR Images using Orthonormal Ridgelet Transform

    Directory of Open Access Journals (Sweden)

    A. Ravi,

    2015-05-01

    Full Text Available Development in the field of image processing for reducing speckle noise from digital images/satellite images is a challenging task for image processing applications. Previously many algorithms were proposed to de-speckle the noise in digital images. Here in this article we are presenting experimental results on de-speckling of Synthetic Aperture RADAR (SAR images. SAR images have wide applications in remote sensing and mapping the surfaces of all planets. SAR can also be implemented as "inverse SAR" by observing a moving target over a substantial time with a stationary antenna. Hence denoising of SAR images is an essential task for viewing the information. Here we introduce a transformation technique called ―Ridgelet‖, which is an extension level of wavelet. Ridgelet analysis can be done in the similar way how wavelet analysis was done in the Radon domain as it translates singularities along lines into point singularities under different frequencies. Simulation results were show cased for proving that proposed work is more reliable than compared to other despeckling processes, and the quality of de-speckled image is measured in terms of Peak Signal to Noise Ratio and Mean Square Error.

  11. Sparse SAR imaging based on L1/2 regularization

    Institute of Scientific and Technical Information of China (English)

    ZENG JinShan; FANG Jian; XU ZongBen

    2012-01-01

    In this paper,a novel method for synthetic aperture radar (SAR) imaging is proposed.The approach is based on L1/2 regularization to reconstruct the scattering field,which optimizes a quadratic error term of the SAR observation process subject to the interested scene sparsity. Compared to the conventional SAR imaging technique,the new method implements SAR imaging effectively at much lower sampling rate than the Nyquist rate,and produces high-quality images with reduced sidelobes and increased resolution. Also,over the prevalent greedy pursuit and L1 regularization based SAR imaging methods,there are remarkable performance improvements of the new method.On one hand,the new method significantly reduces the number of measurements needed for reconstruction,as supported by a phase transition diagram study.On the other hand,the new method is more robust to the observation noise.These fundamental properties of the new method are supported and demonstrated both by simulations and real SAR data experiments.

  12. The Montage Image Mosaic Service: Custom Image Mosaics On-Demand

    Science.gov (United States)

    Berriman, G. B.; Good, J. C.; Laity, A. C.; Kong, M.

    2008-08-01

    The Montage software suite has proven extremely useful as a general engine for reprojecting, background matching, and mosaicking astronomical image data from a wide variety of sources. The processing algorithms support all common World Coordinate System (WCS) projections and have been shown to be both astrometrically accurate and flux conserving. The background `matching' algorithm does not remove background flux but rather finds the best compromise background based on all the input and matches the individual images to that. The Infrared Science Archive (IRSA), part of the Infrared Processing and Analysis Center (IPAC) at Caltech, has now wrapped the Montage software as a CGI service and provided a compute and request management infrastructure capable of producing approximately 2 TBytes / day of image mosaic output (e.g. from 2MASS and SDSS data). Besides the basic Montage engine, this service makes use of a 16-node LINUX cluster (dual processor, dual core) and the ROME request management software developed by the National Virtual Observatory (NVO). ROME uses EJB/database technology to manage user requests, queue processing and load balance between users, and managing job monitoring and user notification. The Montage service will be extended to process user-defined data collections, including private data uploads.

  13. 3-D Target Location from Stereoscopic SAR Images

    Energy Technology Data Exchange (ETDEWEB)

    DOERRY,ARMIN W.

    1999-10-01

    SAR range-Doppler images are inherently 2-dimensional. Targets with a height offset lay over onto offset range and azimuth locations. Just which image locations are laid upon depends on the imaging geometry, including depression angle, squint angle, and target bearing. This is the well known layover phenomenon. Images formed with different aperture geometries will exhibit different layover characteristics. These differences can be exploited to ascertain target height information, in a stereoscopic manner. Depending on the imaging geometries, height accuracy can be on the order of horizontal position accuracies, thereby rivaling the best IFSAR capabilities in fine resolution SAR images. All that is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.

  14. Regional landslide forecasting model using interferometric SAR images

    Institute of Scientific and Technical Information of China (English)

    董育烦; 张发明; 高正夏; 蒯志要

    2008-01-01

    Method of obtaining landslide evaluating information by using Interferometric Synthetic Aperture Radar (InSAR) technique was discussed. More precision landslide surface deformation data extracted from InSAR image need take suitable SAR interferometric data selecting, path tracking, phase unwrapping processes. Then, the DEM model of scope and surface shape of the landslide was built. Combining with geological property of landslide and sliding displacements obtained from InSAR/D-InSAR images, a new landslide forecasting model called equal central angle slice method for those not obviously deformed landslides was put forward. This model breaks the limits of traditional research methods of geology. In this model, the landslide safety factor was calculated by equal central angle slice method, then considering the persistence ratio of the sliding surface based on plastic theory, the minimum safety factor was the phase when plastic area were complete persistence. This new model makes the application of InSAR/D-InSAR technology become more practical in geology hazard research.

  15. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2014-01-01

    other documentation. 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC...and Image Processing IX, 2001. [29] J.-F. Aujol, G. Aubert, L. Blanc- Fraud , and A. Chambolle, “Image decomposition application to SAR images,” in

  16. SAR image target segmentation based on entropy maximization and morphology

    Institute of Scientific and Technical Information of China (English)

    柏正尧; 刘洲峰; 何佩琨

    2004-01-01

    Entropy maximization thresholding is a simple, effective image segmentation method. The relation between the histogram entropy and the gray level of an image is analyzed. An approach, which speeds the computation of optimal threshold based on entropy maximization, is proposed. The suggested method has been applied to the synthetic aperture radar (SAR) image targets segmentation. Mathematical morphology works well in reducing the residual noise.

  17. SAR image formation with azimuth interpolation after azimuth transform

    Science.gov (United States)

    Doerry; Armin W. , Martin; Grant D. , Holzrichter; Michael W.

    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.

  18. [A microscopic image mosaicing algorithm based on normalized moment of inertia].

    Science.gov (United States)

    Lu, Fang-jie; Xia, Shun-ren

    2007-11-01

    A fast microscopic image mosaicing method is proposed in this paper by making a study of the mosaic methods and the characteristics of microscopic images. In the paper, invariant local features based on normalized moment of inertia (NMI) are used to select the matching points and calculate the spatial translation. The experimental results demonstrate that this algorithm can achieve fast, effective microscopic image mosaicing.

  19. Cauchy pdf modelling and its application to SAR image despeckling

    Institute of Scientific and Technical Information of China (English)

    Chen Guozhong; Liu Xingzhao

    2008-01-01

    Synthetic aperture radar(SAR)imagery is a kind of coherent system that produces a random pattern,named speckle,which degrades the merit of SAR images and affects their further application seriously.Therefore,how to restore SAR image from the speckle has become a necessary step in post-processing of image.A new despeckling method is putforth on the basis of wavelet.First.a new approach on the basis of"second kind statistics"is used to estimate the dispersion parameter of the Cauchy distribution.Then,this Cauchy prior is applied to model the distribution of the wavelet coefficients for the log-transformed reflectance of SAR image.Based on the above ideas,a new homomorphic wavelet-based maximum a posterior(MAP)despeckling method is proposed.Finally,the simulated speckled image and the real SAR image are used to verify our proposed method and the results show that it outperforms the other methods in terms of the speckle reduction and the feature retention.

  20. 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.

  1. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2013-01-01

    This new process is also valuable for many SAR image understanding tasks such as road detection, railway detection, ship wake detection, texture...Starck, and L. Boubchir, “Morphological diversity and sparse image denoising,” in Proc. IEEE Int. Conf. Acoust . Speech Signal Process., vol. 1. Apr

  2. 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...

  3. Classification of Polarimetric SAR Image Based on the Subspace Method

    Science.gov (United States)

    Xu, J.; Li, Z.; Tian, B.; Chen, Q.; Zhang, P.

    2013-07-01

    Land cover classification is one of the most significant applications in remote sensing. Compared to optical sensing technologies, synthetic aperture radar (SAR) can penetrate through clouds and have all-weather capabilities. Therefore, land cover classification for SAR image is important in remote sensing. The subspace method is a novel method for the SAR data, which reduces data dimensionality by incorporating feature extraction into the classification process. This paper uses the averaged learning subspace method (ALSM) method that can be applied to the fully polarimetric SAR image for classification. The ALSM algorithm integrates three-component decomposition, eigenvalue/eigenvector decomposition and textural features derived from the gray-level cooccurrence matrix (GLCM). The study site, locates in the Dingxing county, in Hebei Province, China. We compare the subspace method with the traditional supervised Wishart classification. By conducting experiments on the fully polarimetric Radarsat-2 image, we conclude the proposed method yield higher classification accuracy. Therefore, the ALSM classification method is a feasible and alternative method for SAR image.

  4. G0-WISHART DISTRIBUTION BASED CLASSIFICATION FROM POLARIMETRIC SAR IMAGES

    Directory of Open Access Journals (Sweden)

    G. C. Hu

    2017-09-01

    Full Text Available 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. 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.

  6. Ensemble polarimetric SAR image classification based on contextual sparse representation

    Science.gov (United States)

    Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun

    2016-05-01

    Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.

  7. Modelling Iteration Convergence Condition for Single SAR Image Geocoding

    Science.gov (United States)

    Dong, Yuting; Liao, Minghsheng; Zhang, Lu; Shi, Xuguo

    2014-11-01

    Single SAR image geocoding is to determine the ground coordinate for each pixel in the SAR image assisted with an external DEM. Due to the uncertainty of the elevation of each pixel in SAR image, an iterative procedure is needed, which suffers from the problem of divergence in some difficult areas such as shaded and serious layover areas. This paper aims at theoretically analysing the convergence conditions that has not been intensively studied till now. To make the discussion easier, the Range-Doppler (RD) model is simplified and then the general surface is simplified into a planar surface. Mathematical deduction is carried out to derive the convergence conditions and the impact factors for the convergence speed are analysed. The theoretical findings are validated by experiments for both simulated and real surfaces.

  8. Image Mosaic Techniques OptimizationUsing Wavelet

    Institute of Scientific and Technical Information of China (English)

    ZHOUAn-qi; CUILi

    2014-01-01

    This essay concentrates on two key procedures of image mosaic——image registration and imagefusion.Becauseof the character of geometric transformation invariance of edge points, wecalculate the angle difference of the direction vector ofedge points in different images anddraw an angle difference histogramto adjust the rotationproblem. Through this way, algorithm based on gray information is expandedandcan be used in images withdisplacementand rotation. Inthe term of image fusion, wavelet multi-scale analysis is used to fuse spliced images. In order to choose the best method of imagefusion,weevaluate the results of different methods of image fusion by cross entropy.

  9. Compressive SAR imaging with joint sparsity and local similarity exploitation.

    Science.gov (United States)

    Shen, Fangfang; Zhao, Guanghui; Shi, Guangming; Dong, Weisheng; Wang, Chenglong; Niu, Yi

    2015-02-12

    Compressive sensing-based synthetic aperture radar (SAR) imaging has shown its superior capability in high-resolution image formation. However, most of those works focus on the scenes that can be sparsely represented in fixed spaces. When dealing with complicated scenes, these fixed spaces lack adaptivity in characterizing varied image contents. To solve this problem, a new compressive sensing-based radar imaging approach with adaptive sparse representation is proposed. Specifically, an autoregressive model is introduced to adaptively exploit the structural sparsity of an image. In addition, similarity among pixels is integrated into the autoregressive model to further promote the capability and thus an adaptive sparse representation facilitated by a weighted autoregressive model is derived. Since the weighted autoregressive model is inherently determined by the unknown image, we propose a joint optimization scheme by iterative SAR imaging and updating of the weighted autoregressive model to solve this problem. Eventually, experimental results demonstrated the validity and generality of the proposed approach.

  10. Cross Correlation versus Mutual Information for Image Mosaicing

    Directory of Open Access Journals (Sweden)

    Sherin Ghannam

    2013-12-01

    Full Text Available This paper reviews the concept of image mosaicing and presents a comparison between two of the most common image mosaicing techniques. The first technique is based on normalized cross correlation (NCC for registering overlapping 2D images of a 3D scene. The second is based on mutual information (MI. The experimental results demonstrate that the two techniques have a similar performance in most cases but there are some interesting differences. The choice of a distinctive template is critical when working with NCC. On the other hand, when using MI, the registration procedure was able to provide acceptable performance even without distinctive templates. But generally the performance when using MI with large rotation angles was not accurate as with NCC.

  11. Effect of beam-pointing errors on bistatic SAR imaging

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The purpose is to conduct a research in the energy variation of echo wave and the imaging effect caused by the aero bistatic SAR pointing errors.Based on the moving geometry configuration of aero bistatic SAR,a model of beam pointing errors is built.Based on this,the azimuth Doppler frequency center estimation caused by these errors and the limitation to the beam pointing synchronization error are studied,and then the imaging result of different errors are analyzed.The computer's simulations are provided to prove the validity of the above analysis.

  12. Imaging Algorithm for Bistatic SAR Based on GNSS Signal

    Directory of Open Access Journals (Sweden)

    Tian Wei-ming

    2013-03-01

    Full Text Available In this paper imaging processing method for Bistatic Synthetic Aperture Radar (BiSAR utilizing navigation satellite is investigated. Considering the special problems of using Global Navigation Satellite System (GNSS signal to form SAR image, direct signal is used to estimate range migration parameters and range migration is corrected in azimuth time domain. Doppler sensitivity of phase-coded signal was solved by Doppler compensation. Through fitting the Doppler phase history with high-order polynomial, Doppler phase history is accurately approximated and azimuth compression is implemented by de-chirp processing. Through simulation and experimental data processing, the proposed method is verified.

  13. An automatic coastline detector for use with SAR images

    Energy Technology Data Exchange (ETDEWEB)

    Erteza, Ireena A.

    1998-09-01

    SAR imagery for coastline detection has many potential advantages over conventional optical stereoscopic techniques. For example, SAR does not have restrictions on being collected during daylight or when there is no cloud cover. In addition, the techniques for coastline detection witth SAR images can be automated. In this paper, we present the algorithmic development of an automatic coastline detector for use with SAR imagery. Three main algorithms comprise the automatic coastline detection algorithm, The first algorithm considers the image pre-processing steps that must occur on the original image in order to accentuate the land/water boundary. The second algorithm automatically follows along the accentuated land/water boundary and produces a single-pixel-wide coastline. The third algorithm identifies islands and marks them. This report describes in detail the development of these three algorithms. Examples of imagery are used throughout the paper to illustrate the various steps in algorithms. Actual code is included in appendices. The algorithms presented are preliminary versions that can be applied to automatic coastline detection in SAR imagery. There are many variations and additions to the algorithms that can be made to improve robustness and automation, as required by a particular application.

  14. 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...

  15. Imaging retinal mosaics in the living eye.

    Science.gov (United States)

    Rossi, E A; Chung, M; Dubra, A; Hunter, J J; Merigan, W H; Williams, D R

    2011-03-01

    Adaptive optics imaging of cone photoreceptors has provided unique insight into the structure and function of the human visual system and has become an important tool for both basic scientists and clinicians. Recent advances in adaptive optics retinal imaging instrumentation and methodology have allowed us to expand beyond cone imaging. Multi-wavelength and fluorescence imaging methods with adaptive optics have allowed multiple retinal cell types to be imaged simultaneously. These new methods have recently revealed rod photoreceptors, retinal pigment epithelium (RPE) cells, and the smallest retinal blood vessels. Fluorescence imaging coupled with adaptive optics has been used to examine ganglion cells in living primates. Two-photon imaging combined with adaptive optics can evaluate photoreceptor function non-invasively in the living primate retina.

  16. Polar format algorithm for SAR imaging with Matlab

    Science.gov (United States)

    Deming, Ross; Best, Matthew; Farrell, Sean

    2014-06-01

    Due to its computational efficiency, the polar format algorithm (PFA) is considered by many to be the workhorse for airborne synthetic aperture radar (SAR) imaging. PFA is implemented in spatial Fourier space, also known as "K-space", which is a convenient domain for understanding SAR performance metrics, sampling requirements, etc. In this paper the mathematics behind PFA are explained and computed examples are presented, both using simulated data, and experimental airborne radar data from the Air Force Research Laboratory (AFRL) Gotcha Challenge collect. In addition, a simple graphical method is described that can be used to model and predict wavefront curvature artifacts in PFA imagery, which are due to the limited validity of the underlying far-field approximation. The appendix includes Matlab code for computing SAR images using PFA.

  17. 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.

  18. THE SIMULATION OF THE SAR IMAGE OF INTERNAL SOLITARY WAVES IN ALBORAN SEA

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    SAR imaging mechanism of internal wave is studied. The numerical modelling of internal waves is obtained by the two-level scheme. The simulaed SAR images that have better expressed the features of internal waves are given by the internal waves SAR imaging theory and numerical modelling result.

  19. Aerial image mosaics built using images with vegetation index pre-calculated

    Science.gov (United States)

    Rosendo Candido, Leandro; de Castro Jorge, Lúcio André; Luppe, Maximiliam

    2016-10-01

    Precision agriculture (PA) has offered a multitude of benefits to farmers, such as cost reduction, accuracy and speed in decision making. Among the tools that work with PA, the aerial image mosaics have key role in accurate mapping of diseases and pests in crops. A mosaic is the combination of multiple images, creating a new image that covers the property or plots accurately. One of the important analysis for farmers is based on the properties of the reflectance in each range of the electromagnetic spectrum of vegetation. Performing mathematical combinations of the different spectral bands has a better understanding of the spectral response of the vegetation. These combinations are called vegetation index (VI) and are useful for the control of the biomass, water content in leaf, chlorophyll content and others. It is usually calculated VI after the construction of the mosaic, as well the farmer has an accurate analysis of its vegetation. However, building a mosaic of images, it has a high computational cost, taking hours to complete and then apply the VI and to have the first test results. In order to reduce the computational cost of this process, this work aims to present a mosaic of images constructed from images with the VI already pre-calculated providing faster analysis to the farmer, given the fact that applying VI on the image came a this reduction in density image and thus have the gain in computational cost to build the mosaic.

  20. Texture analysis and classification of SAR images of urban areas

    NARCIS (Netherlands)

    Dekker, R.J.

    2003-01-01

    In SAR image classification texture holds useful information. In a study after the ability of texture to discriminate urban land-cover, a set of measures was investigated. Among them were histogram measures, wavelet energy, fractal dimension, lacunarity and semivariograms. The latter were chosen as

  1. Unsupervised Classification of SAR Images using Hierarchical Agglomeration and EM

    NARCIS (Netherlands)

    Kayabol, K.; Krylov, V.; Zerubia, J.; Salerno, E.; Cetin, A.E.; Salvetti, O.

    2012-01-01

    We implement an unsupervised classification algorithm for high resolution Synthetic Aperture Radar (SAR) images. The foundation of algorithm is based on Classification Expectation-Maximization (CEM). To get rid of two drawbacks of EM type algorithms, namely the initialization and the model order sel

  2. 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.

  3. SAR image autofocus by sharpness optimization: a theoretical study.

    Science.gov (United States)

    Morrison, Robert L; Do, Minh N; Munson, David C

    2007-09-01

    Synthetic aperture radar (SAR) autofocus techniques that optimize sharpness metrics can produce excellent restorations in comparison with conventional autofocus approaches. To help formalize the understanding of metric-based SAR autofocus methods, and to gain more insight into their performance, we present a theoretical analysis of these techniques using simple image models. Specifically, we consider the intensity-squared metric, and a dominant point-targets image model, and derive expressions for the resulting objective function. We examine the conditions under which the perfectly focused image models correspond to stationary points of the objective function. A key contribution is that we demonstrate formally, for the specific case of intensity-squared minimization autofocus, the mechanism by which metric-based methods utilize the multichannel defocusing model of SAR autofocus to enforce the stationary point property for multiple image columns. Furthermore, our analysis shows that the objective function has a special separble property through which it can be well approximated locally by a sum of 1-D functions of each phase error component. This allows fast performance through solving a sequence of 1-D optimization problems for each phase component simultaneously. Simulation results using the proposed models and actual SAR imagery confirm that the analysis extends well to realistic situations.

  4. UWB front-end for SAR-based imaging system

    NARCIS (Netherlands)

    Monni, S.; Grooters, R.; Neto, A.; Nennie, F.A.

    2010-01-01

    A planarly fed UWB leaky lens antenna is presented integrated with wide band transmit and receive front-end electronics, to be used in a SAR-based imaging system. The unique non-dispersive characteristics of this antenna over a very wide bandwidth, together with the dual band front-end electronics b

  5. 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.

  6. An Improved Shape Contexts Based Ship Classification in SAR Images

    Directory of Open Access Journals (Sweden)

    Ji-Wei Zhu

    2017-02-01

    Full Text Available In synthetic aperture radar (SAR imagery, relating to maritime surveillance studies, the ship has always been the main focus of study. In this letter, a method of ship classification in SAR images is proposed to enhance classification accuracy. In the proposed method, to fully exploit the distinguishing characters of the ship targets, both topology and intensity of the scattering points of the ship are considered. The results of testing the proposed method on a data set of three types of ships, collected via a space-borne SAR sensor designed by the Institute of Electronics, Chinese Academy of Sciences (IECAS, establish that the proposed method is superior to several existing methods, including the original shape contexts method, traditional invariant moments and the recent approach.

  7. Chest X-ray imaging of patients with SARS

    Institute of Scientific and Technical Information of China (English)

    陆普选; 周伯平; 陈心春; 袁明远; 龚小龙; 杨根东; 刘锦清; 袁本通; 郑广平; 杨桂林; 王火生

    2003-01-01

    Objective To investigate the chest X-ray manifestations of SARS cases.Methods A retrospective study was conducted among 52 clinically confirmed SARS patients from February 9 to May 10, 2003. Chest X-ray scanning was performed at a interval of 1-3 days according to the requirements. The manifestations and special features of SARS in X-ray were analyzed. Results Small or large patchy shadows with intensive density in both lungs were observed in 31 cases, ground-glass like opacification in 16, small patchy shadows in one lung lobe or one lung segment in 18, nodular shadows in one lung segment in 1, and increased lung marking in lung interstitial tissues in 2. Rapidly changing consolidations revealed in chest X-ray images were found to be associated with SARS infections, and they were not affected by treatment with antibiotics.Conclusion Chest X-ray provides a sensitive and specific method for the diagnosis and treatment of SARS, and those present with symptoms and signs should undergo chest X-ray scanning every 1-3 days.

  8. Feature preserving compression of high resolution SAR images

    Science.gov (United States)

    Yang, Zhigao; Hu, Fuxiang; Sun, Tao; Qin, Qianqing

    2006-10-01

    Compression techniques are required to transmit the large amounts of high-resolution synthetic aperture radar (SAR) image data over the available channels. Common Image compression methods may lose detail and weak information in original images, especially at smoothness areas and edges with low contrast. This is known as "smoothing effect". It becomes difficult to extract and recognize some useful image features such as points and lines. We propose a new SAR image compression algorithm that can reduce the "smoothing effect" based on adaptive wavelet packet transform and feature-preserving rate allocation. For the reason that images should be modeled as non-stationary information resources, a SAR image is partitioned to overlapped blocks. Each overlapped block is then transformed by adaptive wavelet packet according to statistical features of different blocks. In quantifying and entropy coding of wavelet coefficients, we integrate feature-preserving technique. Experiments show that quality of our algorithm up to 16:1 compression ratio is improved significantly, and more weak information is reserved.

  9. A General Epipolar-Line Model between Optical and SAR Images and Used in Image Matching

    Directory of Open Access Journals (Sweden)

    Shuai Xing

    2014-02-01

    Full Text Available The search space and strategy are important for optical and SAR image matching. In this paper a general epipolar-line model has been proposed between linear array push-broom optical and SAR images. Then a dynamic approximate epipolar-line constraint model (DAELCM has been constructed and used to construct a new image matching algorithm with Harris operator and CRA. Experimental results have shown that the general epipolar-line model is valid and successfully used in optical and SAR image matching, and effectively limits the search space and decreased computation.

  10. 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...... are obtained while at the same time preserving most of the structures in the image. The algorithm is evaluated using multilook polarimetric L-band data from the Danish airborne EMISAR system, and the impact of the algorithm on the unsupervised H-α classification is demonstrated......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...

  11. SAR IMAGE ENHANCEMENT BASED ON BEAM SHARPENING TECHNIQUE

    Institute of Scientific and Technical Information of China (English)

    LIYong; ZI-IANGKun-hui; ZHUDai-yin; ZHUZhao-da

    2004-01-01

    A major problem encountered in enhancing SAR image is the total loss of phase information and the unknown parameters of imaging system. The beam sharpening technique, combined with synthetic aperture radiation pattern estimation provides an approach to process this kind of data to achieve higher apparent resolution. Based on the criterion of minimizing the expected quadratic estimation error, an optimum FIR filter with a symmetrical structure is designed whose coefficients depend on the azimuth response of local isolated prominent points because this response can be approximately regarded as the synthetic aperture radiation pattern of the imaging system. The point target simulation shows that the angular resolution is improved by a ratio of almost two to one. The processing results of a live SAR image demonstrate the validity of the method.

  12. Image Combination Analysis in SPECAN Algorithm of Spaceborne SAR

    Institute of Scientific and Technical Information of China (English)

    臧铁飞; 李方慧; 龙腾

    2003-01-01

    An analysis of image combination in SPECAN algorithm is delivered in time-frequency domain in detail and a new image combination method is proposed. For four multi-looks processing one sub-aperture data in every three sub-apertures is processed in this combination method. The continual sub-aperture processing in SPECAN algorithm is realized and the processing efficiency can be dramatically increased. A new parameter is also put forward to measure the processing efficient of SAR image processing. Finally, the raw data of RADARSAT are used to test the method and the result proves that this method is feasible to be used in SPECAN algorithm of spaceborne SAR and can improve processing efficiently. SPECAN algorithm with this method can be used in quick-look imaging.

  13. Multiscale Segmentation of Polarimetric SAR Image Based on Srm Superpixels

    Science.gov (United States)

    Lang, F.; Yang, J.; Wu, L.; Li, D.

    2016-06-01

    Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.

  14. 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.

  15. a SAR Image Registration Method Based on Sift Algorithm

    Science.gov (United States)

    Lu, W.; Yue, X.; Zhao, Y.; Han, C.

    2017-09-01

    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.

  16. A Level Set Filter for Speckle Reduction in SAR Images

    OpenAIRE

    Huang Bo; Li Hongga; Huang Xiaoxia

    2010-01-01

    Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can b...

  17. A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions

    Science.gov (United States)

    Huang, Shiqi; Huang, Wenzhun; Zhang, Ting

    2016-12-01

    The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application.

  18. A Compressive Sensing SAR Imaging Approach Based on Wavelet Package Algorithm

    Directory of Open Access Journals (Sweden)

    Shi Yan

    2013-06-01

    Full Text Available Compressive sensing SAR imaging can significantly reduce the sampling rate and the amount of data,but it is essential only in the case where the reflection coefficients of SAR scene are sparse. This paper proposed a compressive sensing SAR imaging method based on wavelet packet sparse representation. The wavelet packet algorithm is used to choose the most sparse representation of the SAR scene by training the same type of SAR images. By solving for the minimum 1 l norm optimization, the SAR scene reflection coefficients can be reconstructed. Unambiguous SAR image can be produced with the proposed method even with fewer samples. SAR data simulation experiments demonstrate the efficiency of the proposed method.

  19. SAR Image Segmentation Based On Hybrid PSOGSA Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Amandeep Kaur

    2014-09-01

    Full Text Available Image segmentation is useful in many applications. It can identify the regions of interest in a scene or annotate the data. It categorizes the existing segmentation algorithm into region-based segmentation, data clustering, and edge-base segmentation. Region-based segmentation includes the seeded and unseeded region growing algorithms, the JSEG, and the fast scanning algorithm. Due to the presence of speckle noise, segmentation of Synthetic Aperture Radar (SAR images is still a challenging problem. We proposed a fast SAR image segmentation method based on Particle Swarm Optimization-Gravitational Search Algorithm (PSO-GSA. In this method, threshold estimation is regarded as a search procedure that examinations for an appropriate value in a continuous grayscale interval. Hence, PSO-GSA algorithm is familiarized to search for the optimal threshold. Experimental results indicate that our method is superior to GA based, AFS based and ABC based methods in terms of segmentation accuracy, segmentation time, and Thresholding.

  20. Dynamic and data-driven classification for polarimetric SAR images

    Science.gov (United States)

    Uhlmann, S.; Kiranyaz, S.; Ince, T.; Gabbouj, M.

    2011-11-01

    In this paper, we introduce dynamic and scalable Synthetic Aperture Radar (SAR) terrain classification based on the Collective Network of Binary Classifiers (CNBC). The CNBC framework is primarily adapted to maximize the SAR classification accuracy on dynamically varying databases where variations do occur in any time in terms of (new) images, classes, features and users' relevance feedback. Whenever a "change" occurs, the CNBC dynamically and "optimally" adapts itself to the change by means of its topology and the underlying evolutionary method MD PSO. Thanks to its "Divide and Conquer" type approach, the CNBC can also support varying and large set of (PolSAR) features among which it optimally selects, weighs and fuses the most discriminative ones for a particular class. Each SAR terrain class is discriminated by a dedicated Network of Binary Classifiers (NBC), which encapsulates a set of evolutionary Binary Classifiers (BCs) discriminating the class with a distinctive feature set. Moreover, with each incremental evolution session, new classes/features can be introduced which signals the CNBC to create new corresponding NBCs and BCs within to adapt and scale dynamically to the change. This can in turn be a significant advantage when the current CNBC is used to classify multiple SAR images with similar terrain classes since no or only minimal (incremental) evolution sessions are needed to adapt it to a new classification problem while using the previously acquired knowledge. We demonstrate our proposed classification approach over several medium and highresolution NASA/JPL AIRSAR images applying various polarimetric decompositions. We evaluate and compare the computational complexity and classification accuracy against static Neural Network classifiers. As CNBC classification accuracy can compete and even surpass them, the computational complexity of CNBC is significantly lower as the CNBC body supports high parallelization making it applicable to grid

  1. A novel SAR fusion image segmentation method based on triplet Markov field

    Science.gov (United States)

    Wang, Jiajing; Jiao, Shuhong; Sun, Zhenyu

    2015-03-01

    Markov random field (MRF) has been widely used in SAR image segmentation because of the advantage of directly modeling the posterior distribution and suppresses the speckle on the influence of the segmentation result. However, when the real SAR images are nonstationary images, the unsupervised segmentation results by MRF can be poor. The recent proposed triplet Markov field (TMF) model is well appropriate for nonstationary SAR image processing due to the introduction of an auxiliary field which reflects the nonstationarity. In addition, on account of the texture features of SAR image, a fusion image segmentation method is proposed by fusing the gray level image and texture feature image. The effectiveness of the proposed method in this paper is demonstrated by a synthesis SAR image and the real SAR images segmentation experiments, and it is better than the state-of-art methods.

  2. Image mosaicing for automated pipe scanning

    Science.gov (United States)

    Summan, Rahul; Dobie, Gordon; Guarato, Francesco; MacLeod, Charles; Marshall, Stephen; Forrester, Cailean; Pierce, Gareth; Bolton, Gary

    2015-03-01

    Remote visual inspection (RVI) is critical for the inspection of the interior condition of pipelines particularly in the nuclear and oil and gas industries. Conventional RVI equipment produces a video which is analysed online by a trained inspector employing expert knowledge. Due to the potentially disorientating nature of the footage, this is a time intensive and difficult activity. In this paper a new probe for such visual inspections is presented. The device employs a catadioptric lens coupled with feature based structure from motion to create a 3D model of the interior surface of a pipeline. Reliance upon the availability of image features is mitigated through orientation and distance estimates from an inertial measurement unit and encoder respectively. Such a model affords a global view of the data thus permitting a greater appreciation of the nature and extent of defects. Furthermore, the technique estimates the 3D position and orientation of the probe thus providing information to direct remedial action. Results are presented for both synthetic and real pipe sections. The former enables the accuracy of the generated model to be assessed while the latter demonstrates the efficacy of the technique in a practice.

  3. Landsat ETM+ False-Color Image Mosaics of Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2007-01-01

    In 2005, the U.S. Agency for International Development and the U.S. Trade and Development Agency contracted with the U.S. Geological Survey to perform assessments of the natural resources within Afghanistan. The assessments concentrate on the resources that are related to the economic development of that country. Therefore, assessments were initiated in oil and gas, coal, mineral resources, water resources, and earthquake hazards. All of these assessments require geologic, structural, and topographic information throughout the country at a finer scale and better accuracy than that provided by the existing maps, which were published in the 1970's by the Russians and Germans. The very rugged terrain in Afghanistan, the large scale of these assessments, and the terrorist threat in Afghanistan indicated that the best approach to provide the preliminary assessments was to use remotely sensed, satellite image data, although this may also apply to subsequent phases of the assessments. Therefore, the first step in the assessment process was to produce satellite image mosaics of Afghanistan that would be useful for these assessments. This report discusses the production of the Landsat false-color image database produced for these assessments, which was produced from the calibrated Landsat ETM+ image mosaics described by Davis (2006).

  4. Calibrated Landsat ETM+ nonthermal-band image mosaics of Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2006-01-01

    In 2005, the U.S. Agency for International Development and the U.S. Trade and Development Agency contracted with the U.S. Geological Survey to perform assessments of the natural resources within Afghanistan. The assessments concentrate on the resources that are related to the economic development of that country. Therefore, assessments were initiated in oil and gas, coal, mineral resources, water resources, and earthquake hazards. All of these assessments require geologic, structural, and topographic information throughout the country at a finer scale and better accuracy than that provided by the existing maps, which were published in the 1970s by the Russians and Germans. The very rugged terrain in Afghanistan, the large scale of these assessments, and the terrorist threat in Afghanistan indicated that the best approach to provide the preliminary assessments was to use remotely sensed, satellite image data, although this may also apply to subsequent phases of the assessments. Therefore, the first step in the assessment process was to produce satellite image mosaics of Afghanistan that would be useful for these assessments. This report discusses the production and characteristics of the fundamental satellite image databases produced for these assessments, which are calibrated image mosaics of all six Landsat nonthermal (reflected) bands.

  5. Interferometric SAR imaging by transmitting stepped frequency chaotic noise signals

    Science.gov (United States)

    Zhang, Yunhua; Gu, Xiang; Zhai, Wenshuai; Dong, Xiao; Shi, Xiaojin; Kang, Xueyan

    2015-10-01

    Noise radar has been applied in many fields since it was proposed more than 50 years ago. However, it has not been applied to interferometric SAR imaging yet as far as we know. This paper introduces our recent work on interferometric noise radar. An interferometric SAR system was developed which can transmit both chirp signal and chaotic noise signal (CNS) at multiple carrier frequencies. An airborne experiment with this system by transmitting both signals was carried out, and the data were processed to show the capability of interferometric SAR imaging with CNS. The results shows that although the interferometric phase quality of CNS is degraded due to the signal to noise ratio (SNR) is lower compared with that of chirp signal, we still can get satisfied DEM after multi-looking processing. Another work of this paper is to apply compressed sensing (CS) theory to the interferometric SAR imaging with CNS. The CS theory states that if a signal is sparse, then it can be accurately reconstructed with much less sampled data than that regularly required according to Nyquist Sampling Theory. To form a structured random matrix, if the transmitted signal is of fixed waveform, then random subsampling is needed. However, if the transmitted signal is of random waveform, then only uniform subsampling is needed. This is another advantage of noise signal. Both the interferometric phase images and the DEMs by regular method and by CS method are processed with results compared. It is shown that the degradation of interferometric phases due to subsampling is larger than that of amplitude image.

  6. Error Estimation Techniques to Refine Overlapping Aerial Image Mosaic Processes via Detected Parameters

    Science.gov (United States)

    Bond, William Glenn

    2012-01-01

    In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid. The method presented first locates…

  7. 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.

  8. Multiscale MRF-based Texture Segmentation of SAR Image

    Institute of Scientific and Technical Information of China (English)

    XUXin; LIDeren; SUNHong

    2004-01-01

    We propose a multiscale Bayesian segmentation algorithm for SAR image in this paper. A hierarchical two-level Markov random field (MRF) is applied to represent both texture and region label over the wavelet lattice. The high level uses an isotropic Multi-level logistic (MLL) random field to characterize the blob-like region formation process at each scale and the interscale dependencies over the corresponding multiresolution region. At lower level a novel Causal Gaussian autoregressive (CGAR) process is proposed to describe the fill-in of multiresolution region. Once the multiscale double MRFs model is established, in term of Sequential maximum a posteriori (SMAP), model parameter estimate and region segmentation are performed alternately from coarse to fine scale. Our segmentation method is tested on both synthetic and ERS-1 SAR images.

  9. Sparse representation-based spectral clustering for SAR image segmentation

    Science.gov (United States)

    Zhang, Xiangrong; Wei, Zhengli; Feng, Jie; Jiao, Licheng

    2011-12-01

    A new method, sparse representation based spectral clustering (SC) with Nyström method, is proposed for synthetic aperture radar (SAR) image segmentation. Different from the conventional SC, this proposed technique is developed by using the sparse coefficients which obtained by solving l1 minimization problem to construct the affinity matrix and the Nyström method is applied to alleviate the segmentation process. The advantage of our proposed method is that we do not need to select the scaling parameter in the Gaussian kernel function artificially. We apply the proposed method, k-means and the classic spectral clustering algorithm with Nyström method to SAR image segmentation. The results show that compared with the other two methods, the proposed method can obtain much better segmentation results.

  10. Underwater topography detection of Shuangzi Reefs with SAR images acquired in different time

    Institute of Scientific and Technical Information of China (English)

    YANG Jungang; ZHANG Jie; MENG Junmin

    2007-01-01

    Imaging mechanism of underwater topography by SAR and a underwater topography SAR detection model built on the theory of underwater topography detection with SAR image presented by Yuan Yeli are used to detect the underwater topography of Shuangzi Reefs in the Nansha Islands with three scenes of SAR images acquired in different time. Detection results of three SAR images are compared with the chart topography and the detection errors are analyzed. Underwater topography detection experiments of Shuangzi Reefs show that the detection model is practicable. The detection results indicate that SAR images acquired in different time also can be used to detect the underwater topography, and the detection results are affected by the ocean conditions in the SAR acquiring time.

  11. Strip mosaicing confocal microscopy for rapid imaging over large areas of excised tissue

    Science.gov (United States)

    Abeytunge, Sanjee; Li, Yongbiao; Larson, Bjorg; Peterson, Gary; Toledo-Crow, Ricardo; Rajadhyaksha, Milind

    2012-03-01

    Confocal mosaicing microscopy is a developing technology platform for imaging tumor margins directly in fresh tissue, without the processing that is required for conventional pathology. Previously, basal cell carcinoma margins were detected by mosaicing of confocal images of 12 x 12 mm2 of excised tissue from Mohs surgery. This mosaicing took 9 minutes. Recently we reported the initial feasibility of a faster approach called "strip mosaicing" on 10 x 10 mm2 of tissue that was demonstrated in 3 minutes. In this paper we report further advances in instrumentation and software. Rapid mosaicing of confocal images on large areas of fresh tissue potentially offers a means to perform pathology at the bedside. Thus, strip mosaicing confocal microscopy may serve as an adjunct to pathology for imaging tumor margins to guide surgery.

  12. Image mosaic and topographic map of the moon

    Science.gov (United States)

    Hare, Trent M.; Hayward, Rosalyn K.; Blue, Jennifer S.; Archinal, Brent A.

    2015-01-01

    Sheet 1: This image mosaic is based on data from the Lunar Reconnaissance Orbiter Wide Angle Camera (WAC; Robinson and others, 2010), an instrument on the National Aeronautics and Space Administration (NASA) Lunar Reconnaissance Orbiter (LRO) spacecraft (Tooley and others, 2010). The equatorial WAC images were orthorectified onto the Global Lunar Digital Terrain Mosaic (GLD100, WAC-derived 100 m/pixel digital elevation model; Scholten and others, 2012) while the polar images were orthorectified onto the lunar LOLA polar digital elevation models (Neumann and others, 2010). The Mercator projection is used between latitudes ±57°, with a central meridian at 0° longitude and latitude equal to the nominal scale at 0°. The Polar Stereographic projection is used for the regions north of the +55° parallel and south of the –55° parallel, with a central meridian set for both at 0° and a latitude of true scale at +90° and -90°, respectively. All named features greater than 85 km in diameter or length were included unless they were not visible on the map. Some selected well-known features less than 85 km in size were also included. For listed references, please open the full PDF.

  13. 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.

  14. Research and Development of Image Mosaics%图像拼接技术

    Institute of Scientific and Technical Information of China (English)

    王俊杰; 刘家茂; 胡运发; 于玉

    2003-01-01

    Image mosaics have been an active area of research in the fields of computer vision,image processing and computer graphics in recent years. The automatic fast construcuon of unlinuted field of view,high-resolution image mosaics is a main research task of this area. According to the procedure of image mosaics,the paper introduces and discusses image acquisition,geometric corrections,image register and image blending in detail. In the last part of the paper,we make a discussion on some problems of research and point out the future research directions.

  15. Compressive SAR Imaging with Joint Sparsity and Local Similarity Exploitation

    Directory of Open Access Journals (Sweden)

    Fangfang Shen

    2015-02-01

    Full Text Available Compressive sensing-based synthetic aperture radar (SAR imaging has shown its superior capability in high-resolution image formation. However, most of those works focus on the scenes that can be sparsely represented in fixed spaces. When dealing with complicated scenes, these fixed spaces lack adaptivity in characterizing varied image contents. To solve this problem, a new compressive sensing-based radar imaging approach with adaptive sparse representation is proposed. Specifically, an autoregressive model is introduced to adaptively exploit the structural sparsity of an image. In addition, similarity among pixels is integrated into the autoregressive model to further promote the capability and thus an adaptive sparse representation facilitated by a weighted autoregressive model is derived. Since the weighted autoregressive model is inherently determined by the unknown image, we propose a joint optimization scheme by iterative SAR imaging and updating of the weighted autoregressive model to solve this problem. Eventually, experimental results demonstrated the validity and generality of the proposed approach.

  16. Design, synthesis, anti-tobacco mosaic virus (TMV) activity, and SARs of 7-methoxycryptopleurine derivatives.

    Science.gov (United States)

    Wang, Ziwen; Feng, Anzheng; Cui, Mingbo; Liu, Yuxiu; Wang, Lizhong; Wang, Qingmin

    2014-11-01

    A series of 7-methoxycryptopleurine derivatives 2-23 were prepared and evaluated for their antiviral activity against tobacco mosaic virus (TMV) for the first time. The bioassay results showed that most of these compounds exhibited excellent in vivo anti-TMV activity, of which 7-methoxycryptopleurine salt derivatives 16, 19, and 23 displayed significantly higher activity than 7-methoxycryptopleurine (1) and commercial ribavirin and ningnanmycin. Salification, the most commonly employed method for modifying physical-chemical properties, did significantly increase antiviral activity, and different salt forms displayed different antiviral effect. This study provides fundamental support for development and optimization of phenanthroquinolizidine alkaloids as potential inhibitors of plant virus. © 2014 John Wiley & Sons A/S.

  17. Decreasing range resolution of a SAR image to permit correction of motion measurement errors beyond the SAR range resolution

    Science.gov (United States)

    Doerry, Armin W.; Heard, Freddie E.; Cordaro, J. Thomas

    2010-07-20

    Motion measurement errors that extend beyond the range resolution of a synthetic aperture radar (SAR) can be corrected by effectively decreasing the range resolution of the SAR in order to permit measurement of the error. Range profiles can be compared across the slow-time dimension of the input data in order to estimate the error. Once the error has been determined, appropriate frequency and phase correction can be applied to the uncompressed input data, after which range and azimuth compression can be performed to produce a desired SAR image.

  18. Radar image preprocessing. [of SEASAT-A SAR data

    Science.gov (United States)

    Frost, V. S.; Stiles, J. A.; Holtzman, J. C.; Held, D. N.

    1980-01-01

    Standard image processing techniques are not applicable to radar images because of the coherent nature of the sensor. Therefore there is a need to develop preprocessing techniques for radar images which will then allow these standard methods to be applied. A random field model for radar image data is developed. This model describes the image data as the result of a multiplicative-convolved process. Standard techniques, those based on additive noise and homomorphic processing are not directly applicable to this class of sensor data. Therefore, a minimum mean square error (MMSE) filter was designed to treat this class of sensor data. The resulting filter was implemented in an adaptive format to account for changes in local statistics and edges. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure was the result of this study. Digitally correlated Seasat-A synthetic aperture radar (SAR) imagery was used to test the technique.

  19. Feature Based Image Mosaic Using Steerable Filters and Harris Corner Detector

    Directory of Open Access Journals (Sweden)

    Mahesh

    2013-05-01

    Full Text Available Image mosaic is to be combine several views of a scene in to single wide angle view. This paper proposes the feature based image mosaic approach. The mosaic image system includes feature point detection, feature point descriptor extraction and matching. A RANSAC algorithm is applied to eliminate number of mismatches and obtain transformation matrix between the images. The input image is transformed with the correct mapping model for image stitching and same is estimated. In this paper, feature points are detected using steerable filters and Harris, and compared with traditional Harris, KLT, and FAST corner detectors.

  20. A detection model of underwater topography with a series of SAR images acquired at different time

    Institute of Scientific and Technical Information of China (English)

    YANG Jungang; ZHANG Jie; MENG Junmin

    2010-01-01

    underwater topography is one of oceanic features detected by Synthetic Aperture Radar. Under-water topography SAR imaging mechanism shows that tidal current is the important factor for underwater topography SAR imaging. Thus under the same wind field condition, SAR images for the same area acquired at different time include different information of the underwater topogra-phy. To utilize synchronously SAR images acquired at different time for the underwater topography SAR detection and improve the precision of detection, based on the detection model of underwater topography with single SAR image and the periodicity of tidal current, a detection model of under- water topography with a series of SAR images acquired at different time is developed by combing with tide and tidal current numerical simulation. To testify the feasibility of the presented model, Taiwan Shoal located at the south outlet of Taiwan Strait is selected as study area and three SAR images are used in the underwater topography detection. The detection results are compared with the field observation data of water depth carried out by R/V Dongfanghong 2, and the errors of the detection are compared with those of the single SAR image. All comparisons show that the detec- tion model presented in the paper improves the precision of underwater topography SAR detection, and the presented model is feasible.

  1. SAR image segmentation using MSER and improved spectral clustering

    Science.gov (United States)

    Gui, Yang; Zhang, Xiaohu; Shang, Yang

    2012-12-01

    A novel approach is presented for synthetic aperture radar (SAR) image segmentation. By incorporating the advantages of maximally stable extremal regions (MSER) algorithm and spectral clustering (SC) method, the proposed approach provides effective and robust segmentation. First, the input image is transformed from a pixel-based to a region-based model by using the MSER algorithm. The input image after MSER procedure is composed of some disjoint regions. Then the regions are treated as nodes in the image plane, and a graph structure is applied to represent them. Finally, the improved SC is used to perform globally optimal clustering, by which the result of image segmentation can be generated. To avoid some incorrect partitioning when considering each region as one graph node, we assign different numbers of nodes to represent the regions according to area ratios among the regions. In addition, K-harmonic means instead of K-means is applied in the improved SC procedure in order to raise its stability and performance. Experimental results show that the proposed approach is effective on SAR image segmentation and has the advantage of calculating quickly.

  2. A Level Set Filter for Speckle Reduction in SAR Images

    Directory of Open Access Journals (Sweden)

    Xiaoxia Huang

    2010-01-01

    Full Text Available Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

  3. A Level Set Filter for Speckle Reduction in SAR Images

    Science.gov (United States)

    Li, Hongga; Huang, Bo; Huang, Xiaoxia

    2010-12-01

    Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

  4. Automatic Registration of SAR Images with the Integrated Complementary Invariant Feature

    Directory of Open Access Journals (Sweden)

    Xiao-hua Wang

    2014-01-01

    Full Text Available The accurate Synthetic Aperture Radar (SAR image registration is important for exact analyses of mine deformation and ecological environment change. Currently, many image registration algorithms have been proposed, but these registration algorithms cannot be directly applied to SAR image, so an integrated registration approach is presented in this paper. Firstly, it is the coarse matching with Canny edge dividing regions; secondly, it is the fine matching by SIFT algorithm with improved Canny edge features; finally, obtain accurate registration SAR image. This approach has fewer computations than that simply using SIFT feature matching. Experimental analyses with SAR images of Yanzhou Mine demonstrate the efficiency and the accuracy of this approach for mine SAR image registration, which provides a simple and effective tool in SAR monitoring of mining deformation and ecological changes

  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. Method of airborne SAR image match integrating multi-information for block adjustment

    Science.gov (United States)

    Yang, S. C.; Huang, G. M.; Zhao, Z.; Lu, L. J.

    2015-06-01

    For the automation of SAR image Block Adjustment, this paper proposed a method of SAR image matching integrating multiinformation. It takes full advantage of SAR image geometric information, feature information, gray-related information and external auxiliary terrain information for SAR image matching. And then Image Tie Points (ITPs) of Block Adjustment can be achieved automatically. The main parts of extracting ITPs automatically include: First, SAR images were rectified geometrically based on the geometric information and external auxiliary terrain information (existed DEM) before match. Second, ground grid points with a certain interval can be get in the block area and approximate ITPs were acquired based on external auxiliary terrain information. Then match reference point was extracted for homologous image blocks with Harris feature detection operator and ITPs were obtained with pyramid matching based on gray-related information. At last, ITPs were transferred from rectified images to original SAR images and used in block adjustment. In the experiment, X band airborne SAR images acquired by Chinese airborne SAR system - CASMSAR system were used to make up the block. The result had showed that the method is effective for block adjustment of SAR data.

  7. A novel method for multi-angle SAR image matching

    Institute of Scientific and Technical Information of China (English)

    Li Dapeng

    2015-01-01

    Multi-angle synthetic aperture radar (SAR) image matching is very challenging, because the same object may cause different backscattering patterns, heavily depending on the radar incident angle. A technique based on the relations between the invariant positions of ground targets among the reference and sensed images is proposed to accommodate the nonmatching patterns. It involves a target extraction using wavelet coefficient fusion, as well as a geometric voting matching routine for searching the matched control points (CPs) in the reference and sensed images, respec-tively. To accelerate the speed of the search, a robust, rapidly corresponding CPs determination strategy is exploited by utilizing the global spatial transformation model, as well as a procedure of outlier removal to ensure the desired accuracy. Meanwhile, the positions of the matched point pairs are relocated using mutual information. The final warping of the images according to the CPs is performed by using a polynomial function. The results show the possibility of matching multi-angle SAR images in general cases.

  8. A high-resolution, four-band SAR testbed with real-time image formation

    Energy Technology Data Exchange (ETDEWEB)

    Walker, B.; Sander, G.; Thompson, M.; Burns, B.; Fellerhoff, R.; Dubbert, D.

    1996-03-01

    This paper describes the Twin-Otter SAR Testbed developed at Sandia National Laboratories. This SAR is a flexible, adaptable testbed capable of operation on four frequency bands: Ka, Ku, X, and VHF/UHF bands. The SAR features real-time image formation at fine resolution in spotlight and stripmap modes. High-quality images are formed in real time using the overlapped subaperture (OSA) image-formation and phase gradient autofocus (PGA) algorithms.

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

    Science.gov (United States)

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

    2015-12-01

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

  10. Color fusion of SAR and FLIR images using a natural color transfer technique

    Institute of Scientific and Technical Information of China (English)

    Shaoyuan Sun; Zhongliang Jing; Zhenhua Li; Gang Liu

    2005-01-01

    Fusion of synthetic aperture radar (SAR) and forward looking infrared (FLIR) images is an important subject for aerospace and sensor surveillance. This paper presents a scheme to achieve a natural color image based on the contours feature of SAR and the target region feature of FLIR so that the overall scene recognition and situational awareness can be improved. The SAR and FLIR images are first decomposed into steerable pyramids, and the contour maps in the SAR image and the region maps in the FLIR image are calculated. The contour and region features are fused at each level of the steerable pyramids. A color image is then formed by transferring daytime color to the monochromic image by using the natural color transfer technique. Experimental results show that the proposed method is effective in providing a color fusion of SAR and FLIR images.

  11. Azimuth resolution improvement for spaceborne SAR images with quasi-non-overlapped Doppler bandwidth

    Institute of Scientific and Technical Information of China (English)

    Zheng Bao

    2014-01-01

    The azimuth resolution improvement problem is solved via a coherent combination of synthetic aperture radar (SAR) ima-ges with the quasi-non-overlapped Doppler bandwidth. Prior to the spectra combination, SAR images should be co-registered, while phase biases induced by topography, atmospheric propagation de-lays and baseline measurement errors should be calibrated. How-ever, the coregistration accuracy suffers from large Doppler decorrelation caused by the quasi-non-overlapped Doppler band-width. Furthermore, the method used to estimate phase biases from interferogram of azimuth pre-filtered SAR image pairs wil fail when there is no overlapped spectrum. The fringe simulation and maximum sharpness optimization are adopted to deal with the problems. Accordingly, a novel algorithm to coherently synthesize SAR images is presented. The experiment with the Terra SAR X-band (TerraSAR-X) satel ite data validates the performance of the presented method.

  12. Extending Driving Vision Based on Image Mosaic Technique

    Directory of Open Access Journals (Sweden)

    Chen Deng

    2017-01-01

    Full Text Available Car cameras have been used extensively to assist driving by make driving visible. However, due to the limitation of the Angle of View (AoV, the dead zone still exists, which is a primary origin of car accidents. In this paper, we introduce a system to extend the vision of drivers to 360 degrees. Our system consists of four wide-angle cameras, which are mounted at different sides of a car. Although the AoV of each camera is within 180 degrees, relying on the image mosaic technique, our system can seamlessly integrate 4-channel videos into a panorama video. The panorama video enable drivers to observe everywhere around a car as far as three meters from a top view. We performed experiments in a laboratory environment. Preliminary results show that our system can eliminate vision dead zone completely. Additionally, the real-time performance of our system can satisfy requirements for practical use.

  13. AN IBR METHOD:PANORAMIC MOSAICS OF SLIT IMAGES WITH DEPTH

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Providing a wider movement range of virtual camera is an unsolvedproblem for state-of-the-art image-based rendering system.In this paper,we present a new image based rendering technology called panoramic mosaics of slit images with depth that can provide large virtual camera motion region for some scenes.By limiting camera motion to a horizontal plane only,a slit image with united depth value is used as the rendering element.The panoramic mosaics of slit images with depth are easy to capture,and the data size is as small as that of panorama.We present here the capturing,construction as well as rendering process of panoramic slit images mosaic with depth.In addition,we present the join up process of multiple panoramic slit images mosaic with depth.

  14. SAR and Oblique Aerial Optical Image Fusion for Urban Area Image Segmentation

    Science.gov (United States)

    Fagir, J.; Schubert, A.; Frioud, M.; Henke, D.

    2017-05-01

    The fusion of synthetic aperture radar (SAR) and optical data is a dynamic research area, but image segmentation is rarely treated. While a few studies use low-resolution nadir-view optical images, we approached the segmentation of SAR and optical images acquired from the same airborne platform - leading to an oblique view with high resolution and thus increased complexity. To overcome the geometric differences, we generated a digital surface model (DSM) from adjacent optical images and used it to project both the DSM and SAR data into the optical camera frame, followed by segmentation with each channel. The fused segmentation algorithm was found to out-perform the single-channel version.

  15. Bionic Mosaic Method of Panoramic Image Based on Compound Eye of Fly

    Institute of Scientific and Technical Information of China (English)

    Haipeng Chen; Xuanjing Shen; Xiaofei Li; Yushan Jin

    2011-01-01

    To satisfy the requirements of real-time and high quality mosaics,a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye.Several CCD cameras were used in this system to imitate the small eyes of a compound eye.Based on the optical analysis of this system,a direct panoramic image mosaic algorithm was proposed.Several sub-images were collected by the bionic compound eye visual system,and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images.Thus,a panoramic image with a large field of view was directly mosaicked,which expanded the field and guaranteed the high resolution.The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality.Furthermore,the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors.This method has better real-time properties compared to other methods.

  16. The Application of the Montage Image Mosaic Engine To The Visualization Of Astronomical Images

    Science.gov (United States)

    Berriman, G. Bruce; Good, J. C.

    2017-05-01

    The Montage Image Mosaic Engine was designed as a scalable toolkit, written in C for performance and portability across *nix platforms, that assembles FITS images into mosaics. This code is freely available and has been widely used in the astronomy and IT communities for research, product generation, and for developing next-generation cyber-infrastructure. Recently, it has begun finding applicability in the field of visualization. This development has come about because the toolkit design allows easy integration into scalable systems that process data for subsequent visualization in a browser or client. The toolkit it includes a visualization tool suitable for automation and for integration into Python: mViewer creates, with a single command, complex multi-color images overlaid with coordinate displays, labels, and observation footprints, and includes an adaptive image histogram equalization method that preserves the structure of a stretched image over its dynamic range. The Montage toolkit contains functionality originally developed to support the creation and management of mosaics, but which also offers value to visualization: a background rectification algorithm that reveals the faint structure in an image; and tools for creating cutout and downsampled versions of large images. Version 5 of Montage offers support for visualizing data written in HEALPix sky-tessellation scheme, and functionality for processing and organizing images to comply with the TOAST sky-tessellation scheme required for consumption by the World Wide Telescope (WWT). Four online tutorials allow readers to reproduce and extend all the visualizations presented in this paper.

  17. GRAY TONE FILTERING ON ERS-SAR IMAGES APPLIED TO CHANGE DETECTION AND MAPPING

    Directory of Open Access Journals (Sweden)

    Gilles André

    2011-05-01

    Full Text Available In SAR images, the pixel values are tightly related to physical parameters of the soil such as topography, roughness and humidity, regardless to atmospheric conditions. Therefore, SAR images may be used to detect, and quantify changes in land cover, by comparison of time series SAR data. Classical change detection techniques from SAR images are based on additive synthesis of RGB colors and arithmetic operations between images. The noisy aspect of ERS image due to the original speckle is an obstacle for available mapping and quantification of the changes. Here, statistical and morphological filters are used to reduce the speckle noise. Combined techniques of change detection and noise filtering are applied here to assess and map from ERS-SAR images the impact of regular or catastrophic flood and deforestation in the East Coast of Madagascar.

  18. Illicit vessel identification in inland waters using SAR image

    Science.gov (United States)

    Zhang, Fengli; Wu, Bingfang; Zhang, Lei; Huang, Huiping; Tian, Yichen

    2006-10-01

    Synthetic Aperture Radar remote sensing has been effectively used in water compliance and enforcement, especially in ship detection, but it is still very difficult to classify or identify vessels in inland water only using existing SAR image. Nevertheless some experience knowledge can help, for example waterway channel is of great significance for water traffic management and illegal activity monitoring. It can be used for judging a vessel complying with traffic rules or not, and also can be used to indicate illicit fishing vessels which are usually far away from navigable waterway channel. For illicit vessel identification speed and efficiency are very important, so it will be significant if we can extract waterway channel directly from SAR images and use it to identify illicit vessels. The paper first introduces the modified two-parameter CFAR algorithm used to detect ship targets in inland waters, and then uses principal curves and neural networks to extract waterway channel. Through comparing the detection results and the extracted waterway channel those vessels not complying with water traffic rules or potential illicit fishing vessels can be easily identified.

  19. Recognizing articulated objects and object articulation in SAR images

    Science.gov (United States)

    Bhanu, Bir; Jones, Grinnell, III; Ahn, Joon S.

    1998-09-01

    The focus of this paper is recognizing articulated objects and the pose of the articulated parts in SAR images. Using SAR scattering center locations as features, the invariance with articulation (i.e. turret rotation for the T72, T80 and M1a tanks, missile erect vs. down for the SCUD launcher) is shown as a function of object azimuth. Similar data is shown for configuration differences in the MSTAR (Public) Targets. The UCR model-based recognition engine (which uses non- articulated models to recognize articulated, occluded and non-standard configuration objects) is described and target identification performance results are given as confusion matrices and ROC curves for six inch and one foot resolution XPATCH images and the one foot resolution MSTAR data. Separate body and turret models are developed that are independent of the relative positions between the body and the turret. These models are used with a subsequent matching technique to refine the pose of the body and determine the pose of the turret. An expression of the probability that a random match will occur is derived and this function is used to set thresholds to minimize the probability of a random match for the recognition system. Results for identification, body pose and turret pose are presented as a function of percent occlusion for articulated XPATCH data and results are given for identification and body pose for articulated MSTAR data.

  20. Flight path-driven mitigation of wavefront curvature effects in SAR images

    Science.gov (United States)

    Doerry, Armin W.

    2009-06-23

    A wavefront curvature effect associated with a complex image produced by a synthetic aperture radar (SAR) can be mitigated based on which of a plurality of possible flight paths is taken by the SAR when capturing the image. The mitigation can be performed differently for different ones of the flight paths.

  1. Efficient DPCA SAR imaging with fast iterative spectrum reconstruction method

    Institute of Scientific and Technical Information of China (English)

    FANG Jian; ZENG JinShan; XU ZongBen; ZHAO Yao

    2012-01-01

    The displaced phase center antenna (DPCA) technique is an effective strategy to achieve wide-swath synthetic aperture radar (SAR) imaging with high azimuth resolution.However,traditionally,it requires strict limitation of the pulse repetition frequency (PRF) to avoid non-uniform sampling.Otherwise,any deviation could bring serious ambiguity if the data are directly processed using a matched filter.To break this limitation,a recently proposed spectrum reconstruction method is capable of recovering the true spectrum from the nonuniform samples. However,the performance is sensitive to the selection of the PRF.Sparse regularization based imaging may provide a way to overcome this sensitivity. The existing time-domain method,however,requires a large-scale observation matrix to be built,which brings a high computational cost.In this paper,we propose a frequency domain method,called the iterative spectrum reconstruction method,through integration of the sparse regularization technique with spectrum analysis of the DPCA signal.By approximately expressing the observation in the frequency domain,which is realized via a series of decoupled linear operations,the method performs SAR imaging which is then not directly based on the observation matrix,which reduces the computational cost from O(N2) to O(NlogN) (where N is the number of range cells),and is therefore more efficient than the time domain method. The sparse regularization scheme,realized via a fast thresholding iteration,has been adopted in this method,which brings the robustness of the imaging process to the PRF selection.We provide a series of simulations and ground based experiments to demonstrate the high efficiency and robustness of the method.The simulations show that the new method is almost as fast as the traditional mono-channel algorithm,and works well almost independently of the PRF selection.Consequently,the suggested method can be accepted as a practical and efficient wide-swath SAR imaging technique.

  2. a Novel Image Registration Algorithm for SAR and Optical Images Based on Virtual Points

    Science.gov (United States)

    Ai, C.; Feng, T.; Wang, J.; Zhang, S.

    2013-07-01

    Optical image is rich in spectral information, while SAR instrument can work in both day and night and obtain images through fog and clouds. Combination of these two types of complementary images shows the great advantages of better image interpretation. Image registration is an inevitable and critical problem for the applications of multi-source remote sensing images, such as image fusion, pattern recognition and change detection. However, the different characteristics between SAR and optical images, which are due to the difference in imaging mechanism and the speckle noises in SAR image, bring great challenges to the multi-source image registration. Therefore, a novel image registration algorithm based on the virtual points, derived from the corresponding region features, is proposed in this paper. Firstly, image classification methods are adopted to extract closed regions from SAR and optical images respectively. Secondly, corresponding region features are matched by constructing cost function with rotate invariant region descriptors such as area, perimeter, and the length of major and minor axes. Thirdly, virtual points derived from corresponding region features, such as the centroids, endpoints and cross points of major and minor axes, are used to calculate initial registration parameters. Finally, the parameters are corrected by an iterative calculation, which will be terminated when the overlap of corresponding region features reaches its maximum. In the experiment, WordView-2 and Radasat-2 with 0.5 m and 4.7 m spatial resolution respectively, obtained in August 2010 in Suzhou, are used to test the registration method. It is shown that the multi-source image registration algorithm presented above is effective, and the accuracy of registration is up to pixel level.

  3. A Likelihood-Based SLIC Superpixel Algorithm for SAR Images Using Generalized Gamma Distribution

    Directory of Open Access Journals (Sweden)

    Huanxin Zou

    2016-07-01

    Full Text Available The simple linear iterative clustering (SLIC method is a recently proposed popular superpixel algorithm. However, this method may generate bad superpixels for synthetic aperture radar (SAR images due to effects of speckle and the large dynamic range of pixel intensity. In this paper, an improved SLIC algorithm for SAR images is proposed. This algorithm exploits the likelihood information of SAR image pixel clusters. Specifically, a local clustering scheme combining intensity similarity with spatial proximity is proposed. Additionally, for post-processing, a local edge-evolving scheme that combines spatial context and likelihood information is introduced as an alternative to the connected components algorithm. To estimate the likelihood information of SAR image clusters, we incorporated a generalized gamma distribution (GГD. Finally, the superiority of the proposed algorithm was validated using both simulated and real-world SAR images.

  4. 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.

  5. 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.

  6. Image quality specification and maintenance for airborne SAR

    Science.gov (United States)

    Clinard, Mark S.

    2004-08-01

    Specification, verification, and maintenance of image quality over the lifecycle of an operational airborne SAR begin with the specification for the system itself. Verification of image quality-oriented specification compliance can be enhanced by including a specification requirement that a vendor provide appropriate imagery at the various phases of the system life cycle. The nature and content of the imagery appropriate for each stage of the process depends on the nature of the test, the economics of collection, and the availability of techniques to extract the desired information from the data. At the earliest lifecycle stages, Concept and Technology Development (CTD) and System Development and Demonstration (SDD), the test set could include simulated imagery to demonstrate the mathematical and engineering concepts being implemented thus allowing demonstration of compliance, in part, through simulation. For Initial Operational Test and Evaluation (IOT&E), imagery collected from precisely instrumented test ranges and targets of opportunity consisting of a priori or a posteriori ground-truthed cultural and natural features are of value to the analysis of product quality compliance. Regular monitoring of image quality is possible using operational imagery and automated metrics; more precise measurements can be performed with imagery of instrumented scenes, when available. A survey of image quality measurement techniques is presented along with a discussion of the challenges of managing an airborne SAR program with the scarce resources of time, money, and ground-truthed data. Recommendations are provided that should allow an improvement in the product quality specification and maintenance process with a minimal increase in resource demands on the customer, the vendor, the operational personnel, and the asset itself.

  7. Polarimetric SAR Image Supervised Classification Method Integrating Eigenvalues

    Directory of Open Access Journals (Sweden)

    Xing Yanxiao

    2016-04-01

    Full Text Available Since classification methods based on H/α space have the drawback of yielding poor classification results for terrains with similar scattering features, in this study, we propose a polarimetric Synthetic Aperture Radar (SAR image classification method based on eigenvalues. First, we extract eigenvalues and fit their distribution with an adaptive Gaussian mixture model. Then, using the naive Bayesian classifier, we obtain preliminary classification results. The distribution of eigenvalues in two kinds of terrains may be similar, leading to incorrect classification in the preliminary step. So, we calculate the similarity of every terrain pair, and add them to the similarity table if their similarity is greater than a given threshold. We then apply the Wishart distance-based KNN classifier to these similar pairs to obtain further classification results. We used the proposed method on both airborne and spaceborne SAR datasets, and the results show that our method can overcome the shortcoming of the H/α-based unsupervised classification method for eigenvalues usage, and produces comparable results with the Support Vector Machine (SVM-based classification method.

  8. MIMO-OFDM signal optimization for SAR imaging radar

    Science.gov (United States)

    Baudais, J.-Y.; Méric, S.; Riché, V.; Pottier, É.

    2016-12-01

    This paper investigates the optimization of the coded orthogonal frequency division multiplexing (OFDM) transmitted signal in a synthetic aperture radar (SAR) context. We propose to design OFDM signals to achieve range ambiguity mitigation. Indeed, range ambiguities are well known to be a limitation for SAR systems which operates with pulsed transmitted signal. The ambiguous reflected signal corresponding to one pulse is then detected when the radar has already transmitted the next pulse. In this paper, we demonstrate that the range ambiguity mitigation is possible by using orthogonal transmitted wave as OFDM pulses. The coded OFDM signal is optimized through genetic optimization procedures based on radar image quality parameters. Moreover, we propose to design a multiple-input multiple-output (MIMO) configuration to enhance the noise robustness of a radar system and this configuration is mainly efficient in the case of using orthogonal waves as OFDM pulses. The results we obtain show that OFDM signals outperform conventional radar chirps for range ambiguity suppression and for robustness enhancement in 2 ×2 MIMO configuration.

  9. Information compression and speckle reduction for multifrequency polarimetric SAR images based on kernel PCA

    Institute of Scientific and Technical Information of China (English)

    Li Ying; Lei Xiaogang; Bai Bendu; Zhang Yanning

    2008-01-01

    Multifrequency polarimetric SAR imagery provides a very convenient approach for signal processing and acquisition of radar image. However, the amount of information is scattered in several images, and redundancies exist between different bands and polarizations. Similar to signal-polarimetric SAR image, multifrequency polarimetric SAR image is corrupted with speckle noise at the same time. A method of information compression and speckle reduction for multifrequency polarimetric SAR imagery is presented based on kernel principal component analysis (KPCA). KPCA is a nonlinear generalization of the linear principal component analysis using the kernel trick. The NASA/JPL polarimetric SAR imagery of P, L, and C bands quadpolarizations is used for illustration. The experimental results show that KPCA has better capability in information compression and speckle reduction as compared with linear PCA.

  10. THE FAST FIXED-POINT ALGORITHM FOR SPECKLE REDUCTION OF POLARIMETRIC SAR IMAGE

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Chen Xiaoning; Pi Yiming; Hou Yinming

    2005-01-01

    In this letter, a simple and efficient method of image speckle reduction for polarimetric SAR is put forward. It is based on the fast fixed-point ICA (Independent Component Analysis) algorithm of orthogonal and symmetric matrix. Simulation experiment is carried out to separate speckle noise from the polarimetric SAR images, and it indicates that this algorithm has high convergency speed and stability, the image speckle noise is reduced effectively and the speckle index is low, and the image quality is improved obviously.

  11. Feature-point-extracting-based automatically mosaic for composite microscopic images

    Institute of Scientific and Technical Information of China (English)

    YIN YanSheng; ZHAO XiuYang; TIAN XiaoFeng; LI Jia

    2007-01-01

    Image mosaic is a crucial step in the three-dimensional reconstruction of composite materials to align the serial images. A novel method is adopted to mosaic two SiC/Al microscopic images with an amplification coefficient of 1000. The two images are denoised by Gaussian model, and feature points are then extracted by using Harris corner detector. The feature points are filtered through Canny edge detector. A 40x40 feature template is chosen by sowing a seed in an overlapped area of the reference image, and the homologous region in floating image is acquired automatically by the way of correlation analysis. The feature points in matched templates are used as feature point-sets. Using the transformational parameters acquired by SVD-ICP method, the two images are transformed into the universal coordinates and merged to the final mosaic image.

  12. COMPARISON OF FILTERS DEDICATED TO SPECKLE SUPPRESSION IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    Full Text Available This paper presents the results of research on the effectiveness of different filtering methods dedicated to speckle suppression in SAR images. The tests were performed on RadarSat-2 images and on an artificial image treated with simulated speckle noise. The research analysed the performance of particular filters related to the effectiveness of speckle suppression and to the ability to preserve image details and edges. Speckle is a phenomenon inherent to radar images – a deterministic noise connected with land cover type, but also causing significant changes in digital numbers of pixels. As a result, it may affect interpretation, classification and other processes concerning radar images. Speckle, resembling “salt and pepper” noise, has the form of a set of relatively small groups of pixels of values markedly different from values of other pixels representing the same type of land cover. Suppression of this noise may also cause suppression of small image details, therefore the ability to preserve the important parts of an image, was analysed as well. In the present study, selected filters were tested, and methods dedicated particularly to speckle noise suppression: Frost, Gamma-MAP, Lee, Lee-Sigma, Local Region, general filtering methods which might be effective in this respect: Mean, Median, in addition to morphological filters (alternate sequential filters with multiple structuring element and by reconstruction. The analysis presented in this paper compared the effectiveness of different filtering methods. It proved that some of the dedicated radar filters are efficient tools for speckle suppression, but also demonstrated a significant efficiency of the morphological approach, especially its ability to preserve image details.

  13. Tropical forest mapping at regional scale using the GRFM SAR mosaics over the Amazon in South America

    NARCIS (Netherlands)

    Sgrenzaroli, M.

    2004-01-01

    The work described in this thesis concerns the estimation of tropical forest vegetation cover in the Amazon region using as data source a continental scale high resolution (100 m) radar mosaic as data source. The radar mosaic was compiled by the Jet Propulsion Laboratory (NASA JPL) using approximate

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

    OpenAIRE

    Lu Ping-ping; Du Kang-ning; Yu Wei-dong; Wang Yu; Deng Yun-kai

    2014-01-01

    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 extracti...

  15. PERFORMANCE EVALUATION OF SEVERAL FUSION APPROACHES FOR CCD/SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Several image fusion approaches for CCD/SAR images are studied and the performance evaluation of these fusion approaches is completed in this paper. Firstly, the preprocessing of CCD/SAR images before fusion is fulfilled. Then, the image fusion methods including linear superposition, nonlinear operator method and multiresolution methods, of which the multiresolution methods include Laplacian pyramid, ratio pyramid, contrast pyramid, gradient pyramid, morphological pyramid and discrete wavelet transform, are adopted to fuse two types of images. Lastly, the four performance measures, standard deviation, entropy, cross entropy and spatial frequency, are calculated to compare the fusion results by different fusion approaches in this paper. Experimental results show that contrast pyramid, morphology pyramid and discrete wavelet transformation in multiresolution approaches are more suitable for CCD/SAR image fusion than other ones proposed in this paper and the objective performance evaluation of CCD/SAR image fusion approaches are effective.

  16. Polarization mosaicing: high dynamic range and polarization imaging in a wide field of view

    Science.gov (United States)

    Schechner, Yoav Y.; Nayar, Shree K.

    2003-12-01

    We present an approach for imaging the polarization state of scene points in a wide field of view, while enhancing the radiometric dynamic range of imaging systems. This is achieved by a simple modification of image mosaicking, which is a common technique in remote sensing. In traditional image mosaics, images taken in varying directions or positions are stitched to obtain a larger image. Yet, as the camera moves, it senses each scene point multiple times in overlapping regions of the raw frames. We rigidly attach to the camera a fixed, spatially varying polarization and attenuation filter. This way, the camera motion-induced multiple measurements per scene point are taken under different optical settings. This is in contrast to the redundant measurements of traditional mosaics. Computational algorithms then analyze the data to extract polarization imaging with high dynamic range across the mosaic field of view. We developed a Maximum Likelihood method to automatically register the images, in spite of the challenging spatially varying effects. Then, we use Maximum Likelihood to handle, in a single framework, variable exposures (due to transmittance variations), saturation, and partial polarization filtering. As a by product, these results enable polarization settings of cameras to change while the camera moves, alleviating the need for camera stability. This work demonstrates the modularity of the Generalized Mosaicing approach, which we recently introduced for multispectral image mosaics. The results are useful for the wealth of polarization imaging applications, in addition to mosaicking applications, particularly remote sensing. We demonstrate experimental results obtained using a system we built.

  17. Decorrelating Clutter Statistics for Long Integration Time SAR Imaging

    Science.gov (United States)

    Leanza, Antonio; Monti Guarnieri, Andrea; Recchia, Andrea; Broquetas Ibars, Antoni; Ruiz Rodon, Josep

    2015-05-01

    It is presented an experiment aimed to assess and eventually complement the Billingsley Internal Clutter Motion (ICM) model for long integration time SAR imaging. Exploiting a real-aperture rotating antenna Ground-Based RADAR, observations of rural areas in different periods of the year have been performed. The collected data, obtained from two different acquisition modes, have been processed to obtain short-term and long-term clutter de-correlation analysis. The results obtained revealed interesting aspects of the phenomenon. In particular, it can be observed that the process is non-stationary with time, say minutes to hours, and that DC/AC ratio follows a day/night characteristic. Moreover, the results showed values of the AC component decay rate β higher than the foreseen ones in the considered spectral interval, which is quite below the one analyzed in the Billingsley experiment.

  18. Fast Detection of Oil Spills and Ships Using SAR Images

    Directory of Open Access Journals (Sweden)

    Alberto Lupidi

    2017-03-01

    Full Text Available In this paper, we show the capabilities of a new maritime control system based on the processing of COSMO-SkyMed Synthetic Aperture Radar (SAR images. This system aims at fast detection of ships that may be responsible for illegal oil dumping. In particular, a novel detection algorithm based on the joint use of the significance parameter, wavelet correlator and a two-dimensional Constant False Alarm Rate (2D-CFAR is designed. Results show the effectiveness of such algorithms, which can be used by the maritime authorities to have a faster although still reliable response. The proposed algorithm, together with the short revisit time of the COSMO-SkyMed constellation, can help with tracking the scenario evolution from one acquisition to the next.

  19. NEPR World View 2 Satellite Mosaic - NOAA TIFF Image

    Data.gov (United States)

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

  20. SAR Imaging Technology Makes Major Advances in China over the Past 25 Years

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    @@ On September 17, 1979, scientists from the CAS Institute of Electronics succeeded in obtaining their first microwave remote sensing images from a prototype airborne synthetic aperture radar (SAR) system. Over the past 25 years, Chinese scientists have won many R&D results and made remarkable progress in developing SAR and its ground receiving systems.

  1. An imaging algorithm based on keystone transform for one-stationary bistatic SAR of spotlight mode

    Science.gov (United States)

    Qiu, Xiaolan; Behner, Florian; Reuter, Simon; Nies, Holger; Loffeld, Otmar; Huang, Lijia; Hu, Donghui; Ding, Chibiao

    2012-12-01

    This article proposes an imaging algorithm based on Keystone Transform for bistatic SAR with a stationary receiver. It can efficiently be applied to high-resolution spotlight mode, and can directly be process the bistatic SAR data which have been ranged compressed by the synchronization reference pulses. Both simulation and experimental results validate the good performance of this algorithm.

  2. 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.

  3. Geometric registration and rectification of spaceborne SAR imagery

    Science.gov (United States)

    Curlander, J. C.; Pang, S. N.

    1982-01-01

    This paper describes the development of automated location and geometric rectification techniques for digitally processed synthetic aperture radar (SAR) imagery. A software package has been developed that is capable of determining the absolute location of an image pixel to within 60 m using only the spacecraft ephemeris data and the characteristics of the SAR data collection and processing system. Based on this location capability algorithms have been developed that geometrically rectify the imagery, register it to a common coordinate system and mosaic multiple frames to form extended digital SAR maps. These algorithms have been optimized using parallel processing techniques to minimize the operating time. Test results are given using Seasat SAR data.

  4. Confocal microscopy with strip mosaicing for rapid imaging over large areas of excised tissue

    Science.gov (United States)

    Abeytunge, Sanjee; Li, Yongbiao; Larson, Bjorg; Peterson, Gary; Seltzer, Emily; Toledo-Crow, Ricardo; Rajadhyaksha, Milind

    2013-06-01

    Confocal mosaicing microscopy is a developing technology platform for imaging tumor margins directly in freshly excised tissue, without the processing required for conventional pathology. Previously, mosaicing on 12-×-12 mm2 of excised skin tissue from Mohs surgery and detection of basal cell carcinoma margins was demonstrated in 9 min. Last year, we reported the feasibility of a faster approach called "strip mosaicing," which was demonstrated on a 10-×-10 mm2 of tissue in 3 min. Here we describe further advances in instrumentation, software, and speed. A mechanism was also developed to flatten tissue in order to enable consistent and repeatable acquisition of images over large areas. We demonstrate mosaicing on 10-×-10 mm2 of skin tissue with 1-μm lateral resolution in 90 s. A 2.5-×-3.5 cm2 piece of breast tissue was scanned with 0.8-μm lateral resolution in 13 min. Rapid mosaicing of confocal images on large areas of fresh tissue potentially offers a means to perform pathology at the bedside. Imaging of tumor margins with strip mosaicing confocal microscopy may serve as an adjunct to conventional (frozen or fixed) pathology for guiding surgery.

  5. SAR Images Unsupervised Change Detection Based on Combination of Texture Feature Vector with Maximum Entropy Principle

    Directory of Open Access Journals (Sweden)

    ZHUANG Huifu

    2016-03-01

    Full Text Available Generally, spatial-contextual information would be used in change detection because there is significant speckle noise in synthetic aperture radar(SAR images. In this paper, using the rich texture information of SAR images, an unsupervised change detection approach to high-resolution SAR images based on texture feature vector and maximum entropy principle is proposed. The difference image is generated by using the 32-dimensional texture feature vector of gray-level co-occurrence matrix(GLCM. And the automatic threshold is obtained by maximum entropy principle. In this method, the appropriate window size to change detection is 11×11 according to the regression analysis of window size and precision index. The experimental results show that the proposed approach is better could both reduce the influence of speckle noise and improve the detection accuracy of high-resolution SAR image effectively; and it is better than Markov random field.

  6. SAR imaging simulation for an inhomogeneous undulated lunar surface based on triangulated irregular network

    Institute of Scientific and Technical Information of China (English)

    FA WenZhe; XU Feng; JIN YaQiu

    2009-01-01

    Based on the statistics of the lunar cratered terrain, e.g., population, dimension and shape of craters, the terrain feature of cratered lunar surface is numerically generated. According to the Inhomogeneous distribution of the lunar surface slope, the triangulated irregular network (TIN) is employed to make the digital elevation of lunar surface model. The Kirchhoff approximation of surface scattering is then applied to simulation of lunar surface scattering. The synthetic aperture radar (SAR) image for compre-hensive cratered lunar surface is numerically generated using back projection (BP) algorithm of SAR Imaging. Making use of the digital elevation and Clementlne UVVIS data at Apollo 15 landing site as the ground truth, an SAR Image at Apollo 15 landing site Is simulated. The image simulation is verified using real SAR image and echoes statistics.

  7. 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.

  8. 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.

  9. 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

  10. Fast SAR Image Change Detection Using Bayesian Approach Based Difference Image and Modified Statistical Region Merging

    Directory of Open Access Journals (Sweden)

    Han Zhang

    2014-01-01

    Full Text Available A novel fast SAR image change detection method is presented in this paper. Based on a Bayesian approach, the prior information that speckles follow the Nakagami distribution is incorporated into the difference image (DI generation process. The new DI performs much better than the familiar log ratio (LR DI as well as the cumulant based Kullback-Leibler divergence (CKLD DI. The statistical region merging (SRM approach is first introduced to change detection context. A new clustering procedure with the region variance as the statistical inference variable is exhibited to tailor SAR image change detection purposes, with only two classes in the final map, the unchanged and changed classes. The most prominent advantages of the proposed modified SRM (MSRM method are the ability to cope with noise corruption and the quick implementation. Experimental results show that the proposed method is superior in both the change detection accuracy and the operation efficiency.

  11. Airborne SAR Real-time Imaging Algorithm Design and Implementation with CUDA on NVIDIA GPU

    Directory of Open Access Journals (Sweden)

    Meng Da-di

    2013-12-01

    Full Text Available Synthetic Aperture Radar (SAR image processing requires huge computation amount. Traditionally, this task runs on the workstation or server based on Central Processing Unit (CPU and is rather time-consuming, hence real-time processing of SAR data is impossible. Based on Compute Unified Device Architecture (CUDA technology, a new plan of SAR imaging algorithm operated on NVIDIA Graphic Processing Unit (GPU is proposed. The new proposal makes it possible that the data processing procedure and CPU/GPU data exchanging execute concurrently, especially when SAR data size exceeds total GPU global memory size. Multi-GPU is suitably supported by the new proposal and all of computational resources are fully exploited. It is shown by experiment on NVIDIA K20C and INTEL E5645 that the proposed solution accelerates SAR data processing by tens of times. Consequently, the GPU based SAR processing system with the proposed solution embedded is much more power saving and portable, which makes it qualified to be a real-time SAR data processing system. Experiment shows that SAR data of 36 Mega points can be processed in real-time per second by K20C with the new solution equipped.

  12. Segmentation-Based PolSAR Image Classification Using Visual Features: RHLBP and Color Features

    Directory of Open Access Journals (Sweden)

    Jian Cheng

    2015-05-01

    Full Text Available A segmentation-based fully-polarimetric synthetic aperture radar (PolSAR image classification method that incorporates texture features and color features is designed and implemented. This method is based on the framework that conjunctively uses statistical region merging (SRM for segmentation and support vector machine (SVM for classification. In the segmentation step, we propose an improved local binary pattern (LBP operator named the regional homogeneity local binary pattern (RHLBP to guarantee the regional homogeneity in PolSAR images. In the classification step, the color features extracted from false color images are applied to improve the classification accuracy. The RHLBP operator and color features can provide discriminative information to separate those pixels and regions with similar polarimetric features, which are from different classes. Extensive experimental comparison results with conventional methods on L-band PolSAR data demonstrate the effectiveness of our proposed method for PolSAR image classification.

  13. Ship Detection in SAR Image Based on the Alpha-stable Distribution

    Directory of Open Access Journals (Sweden)

    Xiaofeng Li

    2008-08-01

    Full Text Available This paper describes an improved Constant False Alarm Rate (CFAR ship detection algorithm in spaceborne synthetic aperture radar (SAR image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution.

  14. A Novel Ship Wake Detection Method of SAR Images Based on Frequency Domain

    Institute of Scientific and Technical Information of China (English)

    Liu Hao; Zhu Minhui

    2003-01-01

    Moving ships produce a set of waves of "V' pattern on the ocean. These waves can often be seen by Synthetic Aperture Radar (SAR). The detection of these wakes can provide important information for surveillance of shipping, such as ship traveling direction and speed. A novel approach to the detection of ship wakes in SAR images based on frequency domain is provided in this letter. Compared with traditional Radon-based approaches, computation is reduced by 20%-40% without losing nearly any of detection performance. The testing results using real data and simulation of synthetic SAR images test the algorithm's feasibility and robustness.

  15. REALIZATION OF QUICK-LOOK IMAGING FOR SPACEBORNE SAR BASED ON PARALLEL PROCESSING

    Institute of Scientific and Technical Information of China (English)

    Tang Zhi; Zhou Yinqing; Li Jingwen

    2004-01-01

    Large range cell migration is a severe challenge to imaging algorithm for spaceborne SAR. Based on design of Finite Impulse Response (FIR) filter and Range Doppler (RD) algorithm,a realization of quick-look imaging for large range cell migration is proposed. It realized quicklook imaging of 8 times reduced resolution with parallel processing on memory shared 8 CPU SGI server. According to simulation experiment, this quick-look imaging algorithm with parallel processing can image 16384× 16384 SAR raw data within 6 seconds. It reaches the requirement of real-time imaging.

  16. Automatic compensation of antenna beam roll-off in SAR images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2006-04-01

    The effects of a non-uniform antenna beam are sometimes visible in Synthetic Aperture Radar (SAR) images. This might be due to near-range operation, wide scenes, or inadequate antenna pointing accuracy. The effects can be mitigated in the SAR image by fitting very a simple model to the illumination profile and compensating the pixel brightness accordingly, in an automated fashion. This is accomplished without a detailed antenna pattern calibration, and allows for drift in the antenna beam alignments.

  17. STUDY ON THE TECHNIQUE TO DETECT TEXTURE FEATURES IN SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Ding Dongtao; Hou Yinming

    2004-01-01

    This letter studies on the detection of texture features in Synthetic Aperture Radar (SAR) images. Through analyzing the feature detection method proposed by Lopes, an improved texture detection method is proposed, which can not only detect the edge and lines but also avoid stretching edge and suppressing lines of the former algorithm. Experimental results with both simulated and real SAR images verify the advantage and practicability of the improved method.

  18. Directional Filter for SAR Images Based on Nonsubsampled Contourlet Transform and Immune Clonal Selection

    Institute of Scientific and Technical Information of China (English)

    Xiao-Hui Yang; Li-Cheng Jiao; Deng-Feng Li

    2009-01-01

    A directional filter algorithm for intensity synthetic aperture radar (SAR) image based on nonsubsampled contourlet transform (NSCT) and immune clonal selection (ICS) is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.

  19. yourSky: Custom Sky-Image Mosaics via the Internet

    Science.gov (United States)

    Jacob, Joseph

    2003-01-01

    yourSky (http://yourSky.jpl.nasa.gov) is a computer program that supplies custom astronomical image mosaics of sky regions specified by requesters using client computers connected to the Internet. [yourSky is an upgraded version of the software reported in Software for Generating Mosaics of Astronomical Images (NPO-21121), NASA Tech Briefs, Vol. 25, No. 4 (April 2001), page 16a.] A requester no longer has to engage in the tedious process of determining what subset of images is needed, nor even to know how the images are indexed in image archives. Instead, in response to a requester s specification of the size and location of the sky area, (and optionally of the desired set and type of data, resolution, coordinate system, projection, and image format), yourSky automatically retrieves the component image data from archives totaling tens of terabytes stored on computer tape and disk drives at multiple sites and assembles the component images into a mosaic image by use of a high-performance parallel code. yourSky runs on the server computer where the mosaics are assembled. Because yourSky includes a Web-interface component, no special client software is needed: ordinary Web browser software is sufficient.

  20. Enhancement of SAR images using fuzzy shrinkage technique in curvelet domain

    Indian Academy of Sciences (India)

    SHIVAKUMARA SWAMY PURANIK MATH; VANI KALIYAPERUMAL

    2017-09-01

    The synthetic aperture radar (SAR) images are mainly affected by speckle noise. Speckle degrades the features in the image and reduces the ability of a human observer to resolve fine detail, hence despeckling is very much required for SAR images. 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 frequency scales using curvelet transform, and then applies the fuzzy shrinking technique to high-frequency coefficients to restore noise-contaminated coefficients. The proposed method does not use threshold approach only by proper selection of shrinking parameter the speckle in SAR image is suppressed. The experiment is carried out on different resolutions of RISAT-1 SAR images, and results are compared with the existing filtering algorithms in terms of noise mean variance (NMV), mean square difference (MSD), equal number of looks (ENL), noise standard deviation (NSD) and speckle suppression index (SSI). A comparison of the results shows that the proposed technique suppresses noise significantly, preserves the details of the image and improves the visual quality of the image

  1. A Method for Sea Surface Wind Field Retrieval from SAR Image Mode Data

    Institute of Scientific and Technical Information of China (English)

    SHAO Weizeng; SUN Jian; GUAN Changlong; SUN Zhanfeng

    2014-01-01

    To retrieve wind field from SAR images, the development for surface wind field retrieval from SAR images based on the improvement of new inversion model is present. Geophysical Model Functions (GMFs) have been widely applied for wind field retrieval from SAR images. Among them CMOD4 has a good performance under low and moderate wind conditions. Although CMOD5 is developed recently with a more fundamental basis, it has ambiguity of wind speed and a shape gradient of normalized radar cross section under low wind speed condition. This study proposes a method of wind field retrieval from SAR image by com-bining CMOD5 and CMOD4 Five VV-polarisation RADARSAT2 SAR images are implemented for validation and the retrieval re-sults by a combination method (CMOD5 and CMOD4) together with CMOD4 GMF are compared with QuikSCAT wind data. The root-mean-square error (RMSE) of wind speed is 0.75 m s-1 with correlation coefficient 0.84 using the combination method and the RMSE of wind speed is 1.01 m s-1 with correlation coefficient 0.72 using CMOD4 GMF alone for those cases. The proposed method can be applied to SAR image for avoiding the internal defect in CMOD5 under low wind speed condition.

  2. 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.

  3. Correction of projective distortion in long-image-sequence mosaics without prior information

    Science.gov (United States)

    Yang, Chenhui; Mao, Hongwei; Abousleman, Glen; Si, Jennie

    2010-04-01

    Image mosaicking is the process of piecing together multiple video frames or still images from a moving camera to form a wide-area or panoramic view of the scene being imaged. Mosaics have widespread applications in many areas such as security surveillance, remote sensing, geographical exploration, agricultural field surveillance, virtual reality, digital video, and medical image analysis, among others. When mosaicking a large number of still images or video frames, the quality of the resulting mosaic is compromised by projective distortion. That is, during the mosaicking process, the image frames that are transformed and pasted to the mosaic become significantly scaled down and appear out of proportion with respect to the mosaic. As more frames continue to be transformed, important target information in the frames can be lost since the transformed frames become too small, which eventually leads to the inability to continue further. Some projective distortion correction techniques make use of prior information such as GPS information embedded within the image, or camera internal and external parameters. Alternatively, this paper proposes a new algorithm to reduce the projective distortion without using any prior information whatsoever. Based on the analysis of the projective distortion, we approximate the projective matrix that describes the transformation between image frames using an affine model. Using singular value decomposition, we can deduce the affine model scaling factor that is usually very close to 1. By resetting the image scale of the affine model to 1, the transformed image size remains unchanged. Even though the proposed correction introduces some error in the image matching, this error is typically acceptable and more importantly, the final mosaic preserves the original image size after transformation. We demonstrate the effectiveness of this new correction algorithm on two real-world unmanned air vehicle (UAV) sequences. The proposed method is

  4. 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...

  5. 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 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...

  6. An integrative synchronization and imaging approach for bistatic spaceborne/stratospheric SAR with a fixed receiver

    Science.gov (United States)

    Zhang, Qilei; Chang, Wenge; Li, Xiangyang

    2013-12-01

    Bistatic spaceborne/stratospheric synthetic aperture radar (SAR) with a fixed receiver is a novel hybrid bistatic SAR system, in which a spaceborne SAR serves as the transmitter of opportunity, while a fixed receiver is mounted on a stratospheric platform. This paper presents an integrative synchronization and imaging approach for this particular system. Firstly, a novel synchronization method using the direct-path signal, which can be collected by a dedicated antenna, is proposed and applied. The synchronization error can be completely removed using the proposed method. However, as the cost of synchronization, the characteristic of synchronized echo's range history becomes quite different from that of general bistatic SAR data. To focus this particular synchronized data, its 2-D spectrum is derived under linear approximations and then a frequency-domain imaging algorithm using two-dimensional inverse scaled Fourier transform (2-DISFT) is proposed. At last, the proposed integrative synchronization and imaging algorithm is verified by simulations.

  7. Change detection in high resolution SAR images based on multiscale texture features

    Science.gov (United States)

    Wen, Caihuan; Gao, Ziqiang

    2011-12-01

    This paper studied on change detection algorithm of high resolution (HR) Synthetic Aperture Radar (SAR) images based on multi-scale texture features. Firstly, preprocessed multi-temporal Terra-SAR images were decomposed by 2-D dual tree complex wavelet transform (DT-CWT), and multi-scale texture features were extracted from those images. Then, log-ratio operation was utilized to get difference images, and the Bayes minimum error theory was used to extract change information from difference images. Lastly, precision assessment was done. Meanwhile, we compared with the result of method based on texture features extracted from gray-level cooccurrence matrix (GLCM). We had a conclusion that, change detection algorithm based on multi-scale texture features has a great more improvement, which proves an effective method to change detect of high spatial resolution SAR images.

  8. The chest X-ray image features of patients with severe SARS: a preliminary study

    Institute of Scientific and Technical Information of China (English)

    刘晋新; 唐小平; 江松峰; 陈碧华; 张烈光; 黄德扬; 黄务枝; 史红玲; 尹炽标; 陈金城

    2003-01-01

    Objective To study the chest X-ray image features of patients with severe SARS.Methods Chest X-ray image features in 36 patients with severe SARS were retrospectively analyzed. The image characteristics were compared with those of 224 patients with common SARS. Results The important chest X-ray imaging features of 36 patients with severe SARS included small patch of infiltration (n=27, 75.0%), large patch of infiltration (n=22, 61.1%), large area of lung consolidation (n=10, 27.3%), interstitial lung lesion (n=26, 72.2%), ground-glass shadow (n=28, 77.8%), irregular linear opacity (n=15, 41.7%), diffuse lung lesion (n=12, 33.3%), with single lung involved (n=9, 25.0%), and both lungs involved (n=32, 88.9%). The rates of large patch of infiltration, large area of lung consolidation, ground-glass shadow, diffuse lung lesion and involvement of both lungs in patients with severe SARS were significantly higher than those in patients with common type of SARS (all P<0.01). Out of the 11 severe SARS patients who died, nine had large area of ground-glass shadow with air bronchogram in both lungs before death.Conclusions Large patch of infiltration, large area of consolidation, ground-glass shadow, diffuse lung lesion and involvement of both lungs were the main X-ray image characteristics of patients with severe SARS. Large area of ground-glass shadow with air bronchogram in both lungs indicated a bad prognosis.

  9. A three-component method for timely detection of land cover changes using polarimetric SAR images

    Science.gov (United States)

    Qi, Zhixin; Yeh, Anthony Gar-On; Li, Xia; Zhang, Xiaohu

    2015-09-01

    This study proposes a new three-component method for timely detection of land cover changes using polarimetric synthetic aperture radar (PolSAR) images. The three components are object-oriented image analysis (OOIA), change vector analysis (CVA), and post-classification comparison (PCC). First, two PolSAR images acquired over the same area at different dates are segmented hierarchically to delineate land parcels (image objects). Then, parcel-based CVA is performed with the coherency matrices of the PolSAR data to detect changed parcels. Finally, PCC based on a parcel-based classification algorithm integrating polarimetric decomposition, decision tree algorithms, and support vector machines is used to determine the type of change for the changed parcels. Compared with conventional PCC based on the widely used Wishart supervised classification, the three-component method achieves much higher accuracy for land cover change detection with PolSAR images. The contribution of each component is evaluated by excluding it from the method. The integration of OOIA in the method greatly reduces the false alarms caused by speckle noise in PolSAR images as well as improves the accuracy of PolSAR image classification. CVA contributes to the method by significantly reducing the effect of the classification errors on the change detection. The use of PCC in the method not only identifies different types of land cover change but also reduces the false alarms introduced by the change in the environment. The three-component method is validated in land development detection, which is important to many developing countries that are confronting a growing problem of unauthorized construction land expansion. The results show that the three-component method is effective in detecting land developments with PolSAR images.

  10. SAR imaging method based on coprime sampling and nested sparse sampling

    Institute of Scientific and Technical Information of China (English)

    Hongyin Shi; Baojing Jia

    2015-01-01

    As the signal bandwidth and the number of channels increase, the synthetic aperture radar (SAR) imaging system pro-duces huge amount of data according to the Shannon-Nyquist theorem, causing a huge burden for data transmission. This pa-per concerns the coprime sampling and nested sparse sampling, which are proposed recently but have never been applied to real world for target detection, and proposes a novel way which uti-lizes these new sub-Nyquist sampling structures for SAR sam-pling in azimuth and reconstructs the data of SAR sampling by compressive sensing (CS). Both the simulated and real data are processed to test the algorithm, and the results indicate the way which combines these new undersampling structures and CS is able to achieve the SAR imaging effectively with much less data than regularly ways required. Final y, the influence of a little sam-pling jitter to SAR imaging is analyzed by theoretical analysis and experimental analysis, and then it concludes a little sampling jitter have no effect on image quality of SAR.

  11. Error Estimation and Unambiguous Reconstruction for Chinese First Dual-Channel Spaceborne SAR Imaging

    Science.gov (United States)

    Jin, T.; Qiu, X.; Hu, D.; Ding, C.

    2017-09-01

    Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF) process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems.

  12. Creating updated, scientifically-calibrated mosaic images for the RC3 catalogue

    CERN Document Server

    Lee, Jung Lin

    2015-01-01

    The Third Reference Catalogue of Bright Galaxies (RC3) is a reasonably complete listing of 23,011 nearby, large, bright galaxies. By using the final imaging data release from the Sloan Digital Sky Survey, we generate scientifically-calibrated FITS mosaics by using the montage program for all SDSS imaging bands for all RC3 galaxies that lie within the survey footprint. We further combine the SDSS g, r, and i band FITS mosaics for these galaxies to create color-composite images by using the STIFF program. We generalized this software framework to make FITS mosaics and color-composite images for an arbitrary catalog and imaging data set. Due to positional inaccuracies inherent in the RC3 catalog, we employ a recursive algorithm in our mosaicking pipeline that first determines the correct location for each galaxy, and subsequently applies the mosaicking procedure. As an additional test of this new software pipeline and to obtain mosaic images of a larger sample of RC3 galaxies, we also applied this pipeline to ph...

  13. Digital shaded-relief image mosaic of the nearshore coastal waters southwest Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southwest Moloka'i. This image mosaic was generated...

  14. Digital shaded-relief image mosaic of the nearshore coastal waters of southcentral Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southcentral Moloka'i. This image mosaic was generated...

  15. Digital shaded-relief image mosaic of the nearshore coastal waters of southcentral Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southcentral Moloka'i. This image mosaic was generated...

  16. A SIFT Algorithm for Bistatic SAR Imaging in Spaceborne Constant-offset Configuration (in English

    Directory of Open Access Journals (Sweden)

    Chen Shi-chao

    2013-03-01

    Full Text Available Focusing on the problem of the space-variance of the range cell migration term for bistatic Synthetic Aperture Radar (SAR, a Scaled Inverse Fourier Transform (SIFT based imaging algorithm for constant-offset configuration bistatic SAR data processing is proposed in this article. Range cell migration correction is realized through two times phase multiplies and one time convolution operation. Since the imaging algorithm is based on an exact precise spectrum which is deduced from the Geometry-Based Formula (GBF algorithm, the proposed algorithm can handle the bistatic SAR data which are obtained with a large baseline to ratio. The advantages and effectiveness of the proposed imaging method have been verified by simulated and comparable experiments. Moreover, unlike the other scaling imaging algorithms which are dependent on the frequency modulated characteristics of the signal, the SIFT imaging algorithm is also suitable for phase-coded signal, which has a wider application areas.

  17. AN EVIDENT SIDELOBE CONTROL METHOD BASED ON NSCT FOR SHIP TARGET IN SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    Li Xueying; Yin Dong; Zhang Rong; Wang Kui

    2011-01-01

    Evident sidelobe on faint ship target seriously affects the accuracy of the target segmentation in Synthetic Aperture Radar (SAR) images.To avoid this problem,a novel sidelobe control method based on NonSubsampled Contourlet Transform (NSCT) for ship targets in SAR images is presented in this paper.This method enhances the SAR images in NSCT domain based on target azimuth estimation and then inhibits the sidelobe directionally in NSCT high-pass frequency subbands.Experimental results on RADARSAT-2 images demonstrate that the proposed method can not only reduce the strong sidelobes effectively,but also enhance the intensity of the objects successfully.Therefore,it gives a good segmentation result on the dark ship images with strong sidelobe,and enhances the detection rate on these targets.

  18. Detection and Imaging of Moving Targets with LiMIT SAR Data

    Science.gov (United States)

    2017-03-03

    1 Detection and Imaging of Moving Targets with LiMIT SAR Data Michael Newey, Gerald Benitz, David Barrett MIT Lincoln Laboratory Lexington...sandeep.mishra@baesystems.com Abstract Detecting moving targets in SAR imagery has recently gained a lot of interest as a way to replace optical...moving target detection and classification in adverse (e.g. cloudy) weather conditions. This can be particularly important for small radar antennas

  19. On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

    Science.gov (United States)

    Medina Revera, Edwin J.; Espinosa, Ramon Vasquez

    1997-01-01

    The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

  20. MULTI-REGION SEGMENTATION OF SAR IMAGE BY A MULTIPHASE LEVEL SET APPROACH

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Cao Zongjie; Pi Yiming

    2008-01-01

    In this letter, a multiphase level set approach unifying region and boundary-based infor- mation for multi-region segmentation of Synthetic Aperture Radar (SAR) image is presented. An energy functional that is applicable for SAR image segmentation is defined. It consists of two terms describing the local statistic characteristics and the gradient characteristics of SAR image respectively. A multiphase level set model that explicitly describes the different regions in one image is proposed. The purpose of such a multiphase model is not only to simplify the way of denoting multi-region by level set but also to guarantee the accuracy of segmentation. According to the presented multiphase model, the curve evolution equations with respect to edge curves are deduced. The multi-region segmentation is implemented by the numeric solution of the partial differential equations. The performance of the approach is verified by both simulation and real SAR images. The experiments show that the proposed algorithm reduces the speckle effect on segmentation and increases the boundary alignment accuracy, thus correctly divides the multi-region SAR image into different homogenous regions.

  1. SAR image change detection algorithm based on stationary wavelet and bi-dimensional intrinsic mode function

    Science.gov (United States)

    Huang, S. Q.; Wang, Z. L.; Xie, T. G.; Li, Z. C.

    2017-09-01

    Speckle noise in synthetic aperture radar (SAR) image is produced by the coherent imaging mechanism, which brings a great impact on the change information acquisition of multi-temporal SAR images. Two-dimensional stationary wavelet transform (SWT) and bi-dimensional empirical mode decomposition (BEMD) are the non-stationary signal processing theory of multi-scale transform. According to their implementation process and SAR image characteristic, this paper proposed a new multi-temporal SAR image change detection method based on the combination of the stationary wavelet transform and the bi-dimensional intrinsic mode function (BIMF) features, called SWT-BIMF algorithm. The contribution of the new algorithm includes two aspects. One is the design of the two selections of decomposition features, that is, the speckle noise filtering; another is the selected features to perform the enhance processing, so more effective change information will obtain. The feasibility of the SWT-BIMF algorithm is verified by the measured SAR image data, and good experimental results are obtained.

  2. 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.

  3. 利用高分辨率聚束模式TerraSAR-X影像的PSInSAR监测地表变形%Monitoring Land Deformation Using PSInSAR with TerraSAR-X High Resolution Spotlight SAR Images

    Institute of Scientific and Technical Information of China (English)

    李永生; 张景发; 罗毅; 姜文亮

    2012-01-01

    利用20景于2010-03~2010-11期间采集的高分辨率聚束(1m分辨率)模式的TerraSAR-X SAR数据,采用永久散射体干涉测量技术(PSInSAR)获取了西藏羊八井地区由地热电站开采地下水引起的地面沉降。结果显示,羊八井地热电站周边及地热开采井地区在2010年期间的地面沉降速率最大达到25mm·a-1,而盆地其他地区的地面平均沉降速率为1mm·a-1。将其与ASAR获取的平均沉降速率结果对比,两者的相关性达到了0.76,这说明TerraSAR-X高分辨率SAR数据不仅可以提供高密度PS点,而且更好地体现了散射体的细节变化和微量位移情况。%Persistent scatterer InSAR was used to detect surface subsidence in the the Yangbajing geothermal power plant due to extraction of ground water with area aroun twent resolution TerraSAR-X spotlight SAR images collected between March and November y hig 2010 d h The results suggest that land subsidence in the areas of geothermal wells is up to 25 mm · a^-1 whilst the subsidence in the basin is less than 1 mm · a^- 1. And the correlation between TerraSAR-X and ASAR derived mean velocities is 0.76. TerraSAR-X high resolution spot- light SAR images can provide higher density of PS points than ASAR data, and also can re- veal the detail change and micro-displacement in a single ground object.

  4. An Aerial Image Mosaic Method Based on UAV Position and Attitude Information

    OpenAIRE

    CHENG Zhenggang; Zhang, Li

    2016-01-01

    As the existing methods for aerial image mosaic take high computational, a fast and effective algorithm based on the position and attitude information of unmanned aerial vehicles (UAV) is proposed. Firstly, the coordinates and attitude angles of UAV can be obtained by airborne GPS and inertial measurement unit (IMU), and each aerial image has a corresponding position and attitude information. The homography matrix between two aerial images with the positions and attitude information can be ca...

  5. 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.

  6. Geodetic imaging of tectonic deformation with InSAR

    Science.gov (United States)

    Fattahi, Heresh

    Precise measurements of ground deformation across the plate boundaries are crucial observations to evaluate the location of strain localization and to understand the pattern of strain accumulation at depth. Such information can be used to evaluate the possible location and magnitude of future earthquakes. Interferometric Synthetic Aperture Radar (InSAR) potentially can deliver small-scale (few mm/yr) ground displacement over long distances (hundreds of kilometers) across the plate boundaries and over continents. However, Given the ground displacement as our signal of interest, the InSAR observations of ground deformation are usually affected by several sources of systematic and random noises. In this dissertation I identify several sources of systematic and random noise, develop new methods to model and mitigate the systematic noise and to evaluate the uncertainty of the ground displacement measured with InSAR. I use the developed approach to characterize the tectonic deformation and evaluate the rate of strain accumulation along the Chaman fault system, the western boundary of the India with Eurasia tectonic plates. I evaluate the bias due to the topographic residuals in the InSAR range-change time-series and develope a new method to estimate the topographic residuals and mitigate the effect from the InSAR range-change time-series (Chapter 2). I develop a new method to evaluate the uncertainty of the InSAR velocity field due to the uncertainty of the satellite orbits (Chapter 3) and a new algorithm to automatically detect and correct the phase unwrapping errors in a dense network of interferograms (Chapter 4). I develop a new approach to evaluate the impact of systematic and stochastic components of the tropospheric delay on the InSAR displacement time-series and its uncertainty (Chapter 5). Using the new InSAR time-series approach developed in the previous chapters, I study the tectonic deformation across the western boundary of the India plate with Eurasia and

  7. Extraction of Coastlines with Fuzzy Approach Using SENTINEL-1 SAR Image

    Science.gov (United States)

    Demir, N.; Kaynarca, M.; Oy, S.

    2016-06-01

    Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS) Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the LIDAR points of

  8. THE REALIZATION OF THE PPP AUTOFOCUS METHOD IN PFA FOR SPOTLIGHT MODE SAR IMAGING

    Institute of Scientific and Technical Information of China (English)

    Fu Wenxian; Hong Wen; Li Shaohong

    2002-01-01

    This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation. Mathematical analysis and computer simulations show the above mentioned motion kinds and their corresponding damages on spotlight mode SAR imaging. Based on this analysis, a single PPP is introduced for spotlight mode SAR imaging with the PFA on the assumption that relative rotation between APC and imaged scene is uniform. The selected single point is used first to correct the quadratic and higher order phase errors and then to adjust the linear errors. After this compensation, the space-invariant phase errors caused by translation are almost corrected. Finally results are presented with the simulated data.

  9. THE REALIZATION OF THE PPP AUTOFOCUS METHOD IN PFA FOR SPOTLIGHT MODE SAR IMAGING

    Institute of Scientific and Technical Information of China (English)

    FuWenxian; HongWen; 等

    2002-01-01

    This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation.Mathematical analysis and computer simulations show the sbove mentioned motion kinds and their corresponding damages on spotlight mode SAR imaging.Based on this analysis, a single PPP is introduced for spotlight mode SAR imaging with the PFA on the assumption that relative rotation between APC and imaged sceme is uniform.The selected single point is used first to correct the quadratic and higher order phase errors and then to adjust the linear errors.After this compensation, the space-invariant phase errors caused by translation are almost corrected.Finally results are presented with the simulated data.

  10. Compressed Sensing Imaging Algorithm for High-squint SAR Based on NCS Operator

    Directory of Open Access Journals (Sweden)

    Gu Fufei

    2016-02-01

    Full Text Available A novel compressed sensing imaging algorithm for high-squint Synthetic Aperture Radar (SAR based on a Nonlinear Chirp-Scaling (NCS operator is proposed. First, the echo signal of high-squint SAR is analyzed, and a novel imaging method based on the Nyquist-sampled echo signal is proposed. With the proposed method, the range migration is corrected and the coupling problem in the range and azimuth directions is solved. Then, to solve the problem of high-squint SAR imaging using undersampled echo signals, the NCS operator and compressed sensing algorithm based on this operator are constructed. Imaging results are obtained by solving an optimization problem. The proposed method can recover a sparse scene using undersampled echo data. Furthermore, it can recover a nonsparse scene using fully sampled data. Finally, simulations show the effectiveness of the proposed method.

  11. An Optimal Method For Wake Detection In SAR Images Using Radon Transformation Combined With Wavelet Filters

    CERN Document Server

    Krishnaveni, M; Subashini, P

    2009-01-01

    A new fangled method for ship wake detection in synthetic aperture radar (SAR) images is explored here. Most of the detection procedure applies the Radon transform as its properties outfit more than any other transformation for the detection purpose. But still it holds problems when the transform is applied to an image with a high level of noise. Here this paper articulates the combination between the radon transformation and the shrinkage methods which increase the mode of wake detection process. The latter shrinkage method with RT maximize the signal to noise ratio hence it leads to most optimal detection of lines in the SAR images. The originality mainly works on the denoising segment of the proposed algorithm. Experimental work outs are carried over both in simulated and real SAR images. The detection process is more adequate with the proposed method and improves better than the conventional methods.

  12. Refocusing of Moving Targets in SAR Images via Parametric Sparse Representation

    Directory of Open Access Journals (Sweden)

    Yichang Chen

    2017-08-01

    Full Text Available In this paper, a parametric sparse representation (PSR method is proposed for refocusing of moving targets in synthetic aperture radar (SAR images. In regular SAR images, moving targets are defocused due to unknown motion parameters. Refocusing of moving targets requires accurate phase compensation of echo data. In the proposed method, the region of interest (ROI data containing the moving targets are extracted from the complex SAR image and represented in a sparse fashion through a parametric transform, which is related to the phase compensation parameter. By updating the reflectivities of moving target scatterers and the parametric transform in an iterative fashion, the phase compensation parameter can be accurately estimated and the SAR images of moving targets can be refocused well. The proposed method directly operates on small-size defocused ROI data, which helps to reduce the computational burden and suppress the clutter. Compared to other existing ROI-based methods, the proposed method can suppress asymmetric side-lobes and improve the image quality. Both simulated data and real SAR data collected by GF-3 satellite are used to validate the effectiveness of the proposed method.

  13. 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.

  14. Fast correlation technique for glacier flow monitoring by digital camera and space-borne SAR images

    Directory of Open Access Journals (Sweden)

    Moreau Luc

    2011-01-01

    Full Text Available Abstract Most of the image processing techniques have been first proposed and developed on small size images and progressively applied to larger and larger data sets resulting from new sensors and application requirements. In geosciences, digital cameras and remote sensing images can be used to monitor glaciers and to measure their surface velocity by different techniques. However, the image size and the number of acquisitions to be processed to analyze time series become a critical issue to derive displacement fields by the conventional correlation technique. In this paper, a mathematical optimization of the classical normalized cross-correlation and its implementation are described to overcome the computation time and window size limitations. The proposed implementation is performed with a specific memory management to avoid most of the temporary result re-computations. The performances of the software resulting from this optimization are assessed by computing the correlation between optical images of a serac fall, and between Synthetic Aperture Radar (SAR images of Alpine glaciers. The optical images are acquired by a digital camera installed near the Argentière glacier (Chamonix, France and the SAR images are acquired by the high resolution TerraSAR-X satellite over the Mont-Blanc area. The results illustrate the potential of this implementation to derive dense displacement fields with a computational time compatible with the camera images acquired every 2 h and with the size of the TerraSAR-X scenes covering 30 × 50 km2.

  15. Target Detection in SAR Images Based on a Level Set Approach

    Energy Technology Data Exchange (ETDEWEB)

    Marques, Regis C.P.; Medeiros, Fatima N.S.; Ushizima, Daniela M.

    2008-09-01

    This paper introduces a new framework for point target detection in synthetic aperture radar (SAR) images. We focus on the task of locating reflective small regions using alevel set based algorithm. Unlike most of the approaches in image segmentation, we address an algorithm which incorporates speckle statistics instead of empirical parameters and also discards speckle filtering. The curve evolves according to speckle statistics, initially propagating with a maximum upward velocity in homogeneous areas. Our approach is validated by a series of tests on synthetic and real SAR images and compared with three other segmentation algorithms, demonstrating that it configures a novel and efficient method for target detection purpose.

  16. An Aerial Image Mosaic Method Based on UAV Position and Attitude Information

    Directory of Open Access Journals (Sweden)

    CHENG Zhenggang

    2016-06-01

    Full Text Available As the existing methods for aerial image mosaic take high computational, a fast and effective algorithm based on the position and attitude information of unmanned aerial vehicles (UAV is proposed. Firstly, the coordinates and attitude angles of UAV can be obtained by airborne GPS and inertial measurement unit (IMU, and each aerial image has a corresponding position and attitude information. The homography matrix between two aerial images with the positions and attitude information can be calculated. Then the registration of the mosaic images is obtained by the operation of homography matrix. Finally, the multiple images can be stitched and the whole panorama got. A large number of experiments demonstrate this algorithm is efficient.

  17. Antenatal diagnosis of mirror-image dextrocardia in association with situs inversus and Turner's mosaicism.

    Science.gov (United States)

    Ortiga, D J; Chiba, Y; Kanai, H; Hosono, T

    2001-10-01

    We describe the antenatal diagnosis of a fetus with mirror-image dextrocardia, complete situs inversus and Turner's mosaicism (45,XO/46,XY) that was artificially terminated at 19 weeks. Autopsy confirmed our initial findings. This case represents an unusual combination of anomalies rarely encountered in clinical practice.

  18. SAR Computation inside Fetus by RF Coil during MR Imaging Employing Realistic Numerical Pregnant Woman Model

    Science.gov (United States)

    Kikuchi, Satoru; Saito, Kazuyuki; Takahashi, Masaharu; Ito, Koichi; Ikehira, Hiroo

    This paper presents the computational electromagnetic dosimetry inside an anatomically based pregnant woman models exposed to electromagnetic wave during magnetic resonance imaging. The two types of pregnant woman models corresponding to early gestation and 26 weeks gestation were used for this study. The specific absorption rate (SAR) in and around a fetus were calculated by radiated electromagnetic wave from highpass and lowpass birdcage coil. Numerical calculation results showed that high SAR region is observed at the body in the vicinity of gaps of the coil, and is related to concentrated electric field in the gaps of human body such as armpit and thigh. Moreover, it has confirmed that the SAR in the fetus is less than International Electrotechnical Commission limit of 10W/kg, when whole-body average SARs are 2W/kg and 4W/kg, which are the normal operating mode and first level controlled operating mode, respectively.

  19. An Algorithm for Ship Wake Detection from the SAR Images Using the Radon Transform and Morphological Image Processing

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Using the Rador transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linesr texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.

  20. A sparsity-driven approach for joint SAR imaging and phase error correction.

    Science.gov (United States)

    Önhon, N Özben; Cetin, Müjdat

    2012-04-01

    Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed images. The application of interest in this paper is synthetic aperture radar (SAR) imaging, which particularly suffers from motion-induced model errors. These types of errors result in phase errors in SAR data, which cause defocusing of the reconstructed images. Particularly focusing on imaging of fields that admit a sparse representation, we propose a sparsity-driven method for joint SAR imaging and phase error correction. Phase error correction is performed during the image formation process. The problem is set up as an optimization problem in a nonquadratic regularization-based framework. The method involves an iterative algorithm, where each iteration of which consists of consecutive steps of image formation and model error correction. Experimental results show the effectiveness of the approach for various types of phase errors, as well as the improvements that it provides over existing techniques for model error compensation in SAR.

  1. Building detection and building parameter retrieval in InSAR phase images

    Science.gov (United States)

    Dubois, Clémence; Thiele, Antje; Hinz, Stefan

    2016-04-01

    The high resolution provided by the current satellite SAR missions makes them an attractive solution for the detailed analysis of urban areas. Especially due to their weather and daylight independency, they can be employed when optical sensors come to their limits. Due to the specific oblique side-looking configuration of such SAR sensors, phenomena such as layover, double bounce and shadow appear at building location, which can be better understood with very high resolution (VHR) SAR data. The detection of those areas, as well as the retrieval of building parameters through a detailed analysis of the extracted structures, is a challenging task. Indeed, depending on the acquisition configuration, on building material and surroundings, those patterns are not always consistent in amplitude SAR images. They can be difficult to recognize and distinguish automatically. Considering InSAR phase images instead of amplitude images is very helpful for this task, as InSAR is more depending on the geometry. Therefore, in this paper, we focus on the detection and extraction of building layover in InSAR phase images. Two complementing detectors are proposed, and their results are combined, in order to provide reliable building hypotheses. Based on the extracted segments, further analysis is conducted. Especially, the number of connected facades is analyzed. Characteristically geometrical shapes are finally fitted for each facade to permit the determination of the final building parameters as length, width, and height. Results of this approach are shown for three different datasets, first in terms of correctness and completeness of the extraction, and second in terms of accuracy of the extracted building parameters. For the considered datasets, the completeness and correctness are of about 70% and 90%, respectively. Eliminating clear outliers, the determined parameters present an accuracy up to 4 m (length), 2 m (height) and 3 ° (orientation). In this article isolated, middle to

  2. Polarimetric Contextual Classification of PolSAR Images Using Sparse Representation and Superpixels

    Directory of Open Access Journals (Sweden)

    Jilan Feng

    2014-07-01

    Full Text Available In recent years, sparse representation-based techniques have shown great potential for pattern recognition problems. In this paper, the problem of polarimetric synthetic aperture radar (PolSAR image classification is investigated using sparse representation-based classifiers (SRCs. We propose to take advantage of both polarimetric information and contextual information by combining sparsity-based classification methods with the concept of superpixels. Based on polarimetric feature vectors constructed by stacking a variety of polarimetric signatures and a superpixel map, two strategies are considered to perform polarimetric-contextual classification of PolSAR images. The first strategy starts by classifying the PolSAR image with pixel-wise SRC. Then, spatial regularization is imposed on the pixel-wise classification map by using majority voting within superpixels. In the second strategy, the PolSAR image is classified by taking superpixels as processing elements. The joint sparse representation-based classifier (JSRC is employed to combine the polarimetric information contained in feature vectors and the contextual information provided by superpixels. Experimental results on real PolSAR datasets demonstrate the feasibility of the proposed approaches. It is proven that the classification performance is improved by using contextual information. A comparison with several other approaches also verifies the effectiveness of the proposed approach.

  3. Multi-Core DSP Based Parallel Architecture for FMCW SAR Real-Time Imaging

    Directory of Open Access Journals (Sweden)

    C. F. Gu

    2015-12-01

    Full Text Available This paper presents an efficient parallel processing architecture using multi-core Digital Signal Processor (DSP to improve the capability of real-time imaging for Frequency Modulated Continuous Wave Synthetic Aperture Radar (FMCW SAR. With the application of the proposed processing architecture, the imaging algorithm is modularized, and each module is efficiently realized by the proposed processing architecture. In each module, the data processing of different cores is executed in parallel, also the data transmission and data processing of each core are synchronously carried out, so that the processing time for SAR imaging is reduced significantly. Specifically, the time of corner turning operation, which is very time-consuming, is ignored under computationally intensive case. The proposed parallel architecture is applied to a compact Ku-band FMCW SAR prototype to achieve real-time imageries with 34 cm x 51 cm (range x azimuth resolution.

  4. SAR images classification method based on Dempster-Shafer theory and kernel estimate

    Institute of Scientific and Technical Information of China (English)

    He Chu; Xia Guisong; Sun Hong

    2007-01-01

    To study the scene classification in the Synthetic Aperture Radar (SAR) image, a novel method based on kernel estimate, with the Markov context and Dempster-Shafer evidence theory is proposed.Initially, a nonparametric Probability Density Function (PDF) estimate method is introduced, to describe the scene of SAR images.And then under the Markov context, both the determinate PDF and the kernel estimate method are adopted respectively, to form a primary classification.Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification.Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification.Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results.Experimental results on real SAR images illustrate a rather impressive performance.

  5. Edge Detection of PolSAR Image Based on Stochastic Distance

    Directory of Open Access Journals (Sweden)

    WANG Qing

    2015-07-01

    Full Text Available A new edge detection methodology in PolSAR images is proposed, which is based on stochastic distance in the statistical theory and combined with complex Wishart distribution. Its main principle is inspired from the phenomenon that stochastic distance of two classes separated by an edge is closely related to the edge direction and the contrast of two classes. Simulation experiments are carried out to analyze the performance of the proposed methods. Results prove that methods have better capabilities in edge orientation and edge positioning than common used methods. Then, the proposed detection procedure is tested on a simulated PolSAR image with the complex Wishart distribution, as well as an airborne fully polarimetric SAR image.

  6. Polarimetric SAR Image Object Segmentation via Level Set with Stationary Global Minimum

    Directory of Open Access Journals (Sweden)

    Wen Yang

    2010-01-01

    Full Text Available We present a level set-based method for object segmentation in polarimetric synthetic aperture radar (PolSAR images. In our method, a modified energy functional via active contour model is proposed based on complex Gaussian/Wishart distribution model for both single-look and multilook PolSAR images. The modified functional has two interesting properties: (1 the curve evolution does not enter into local minimum; (2 the level set function has a unique stationary convergence state. With these properties, the desired object can be segmented more accurately. Besides, the modified functional allows us to set an effective automatic termination criterion and makes the algorithm more practical. The experimental results on synthetic and real PolSAR images demonstrate the effectiveness of our method.

  7. 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.

  8. Comparing C- and L-band SAR images for sea ice motion estimation

    Science.gov (United States)

    Lehtiranta, J.; Siiriä, S.; Karvonen, J.

    2015-02-01

    Pairs of consecutive C-band synthetic-aperture radar (SAR) images are routinely used for sea ice motion estimation. The L-band radar has a fundamentally different character, as its longer wavelength penetrates deeper into sea ice. L-band SAR provides information on the seasonal sea ice inner structure in addition to the surface roughness that dominates C-band images. This is especially useful in the Baltic Sea, which lacks multiyear ice and icebergs, known to be confusing targets for L-band sea ice classification. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal cross-correlation (MCC) approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.

  9. a New 2d Otsu for Water Extraction from SAR Image

    Science.gov (United States)

    Guo, Y.; Zhang, J.

    2017-09-01

    SAR image segmentation is a crucial step that heavily influences the performance of image interpretation. The texture factor to replace the neighborhood mean dimension in the traditional Otsu method is proposed in this work, aiming at the problem that the SAR image has unique characteristics and the original 2D Otsu method only considers the pixel neighborhood mean information. In this paper, TerraSAR image with the single band and single polarization is used to water extraction. Firstly, the semantic function is used to analyze the structural characteristics of the sample image to determine the optimal parameters of the texture information extraction. Then, calculate the textural measures such as contrast, entropy, homogeneity, mean and second moment based on gray level co-occurrence matrix(GLCM) method. The results are compared with the artificially marked images and the results of the original 2D Otsu.The experimental results achieve higher objective values, which shows the proposed algorithm using texture factor has a high practical value for SAR Image water segmentation.

  10. The Landsat Image Mosaic of the Antarctica Web Portal

    Directory of Open Access Journals (Sweden)

    Christopher J Rusanowski

    2007-06-01

    Full Text Available People believe what they can see. The Poles exist as a frozen dream to most people. The International Polar Year wants to break the ice (so to speak, open up the Poles to the general public, support current polar research, and encourage new research projects.  The IPY officially begins in March, 2007. As part of this effort, the U.S. Geological Survey (USGS and the British Antarctic Survey (BAS, with funding from the National Science Foundation (NSF, are developing three Landsat mosaics of Antarctica and an Antarctic Web Portal with a Community site and an online map viewer. When scientists are able to view the entire scope of polar research, they will be better able to collaborate and locate the resources they need. When the general public more readily sees what is happening in the polar environments, they will understand how changes to the polar areas affect everyone.

  11. The landsat image mosaic of the Antarctica Web Portal

    Science.gov (United States)

    Rusanowski, C.J.

    2007-01-01

    People believe what they can see. The Poles exist as a frozen dream to most people. The International Polar Year wants to break the ice (so to speak), open up the Poles to the general public, support current polar research, and encourage new research projects. The IPY officially begins in March, 2007. As part of this effort, the U.S. Geological Survey (USGS) and the British Antarctic Survey (BAS), with funding from the National Science Foundation (NSF), are developing three Landsat mosaics of Antarctica and an Antarctic Web Portal with a Community site and an online map viewer. When scientists are able to view the entire scope of polar research, they will be better able to collaborate and locate the resources they need. When the general public more readily sees what is happening in the polar environments, they will understand how changes to the polar areas affect everyone.

  12. Speckle Filtering in PolSAR Images by Enhanced Wavelet Thresholding

    Science.gov (United States)

    Boutarfa, Souhila; Bouchemakh, Lynda; Smara, Youcef

    2016-08-01

    The PolSAR images are affected by a noise called speckle, which deteriorates image quality and complicates image interpretation. The polarimetric filtering is a necessary treatment prior to analysis that allows to reduce speckle and to obtain an improved image quality.In this paper, we present a polarimetric speckle filtering method based on enhancement of wavelet thresholding, hard and soft thresholding using directional coefficients improvement to reduce speckle without destroying the information. This algorithm is based on the classification of significant coefficients and applying the thresholding to obtain a better image quality.The methods are applied to the three polarimetric E-SAR images acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band and the fully polarimetric RADARSAT-2 images acquired on Algiers, Algeria, in C-band.To evaluate the performance of each filter, we based it on the following criteria: smoothing homogeneous areas, preserving structural characteristics of objects and maintaining the information.

  13. SAR image segmentation with entropy ranking based adaptive semi-supervised spectral clustering

    Science.gov (United States)

    Zhang, Xiangrong; Yang, Jie; Hou, Biao; Jiao, Licheng

    2010-10-01

    Spectral clustering has become one of the most popular modern clustering algorithms in recent years. In this paper, a new algorithm named entropy ranking based adaptive semi-supervised spectral clustering for SAR image segmentation is proposed. We focus not only on finding a suitable scaling parameter but also determining automatically the cluster number with the entropy ranking theory. Also, two kinds of constrains must-link and cannot-link based semi-supervised spectral clustering is applied to gain better segmentation results. Experimental results on SAR images show that the proposed method outperforms other spectral clustering algorithms.

  14. Change detection of polarimetric SAR images based on the KummerU Distribution

    Science.gov (United States)

    Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

    2014-11-01

    In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

  15. Fusion of Spaceborne Optical and SAR Images for Building Height Quick Extraction in Big Urban Areas

    Directory of Open Access Journals (Sweden)

    TIAN Feng

    2017-07-01

    Full Text Available The spaceborne high-resolution optical images and synthetic aperture radar (SAR images are applied to extract building height in urban areas widely. But the lack of optical satellite parameters along with the SAR images' incomplete scattering characteristics and inefficient extraction make the application flawed. To cure the above problems, we investigated the joint use of the spaceborne high-resolution optical images and SAR images to extract building height information quickly in big urban areas. The chain is decomposed into the main following steps: First, the building shadows are extracted by integrating support vector machines (SVM with morphological shadow index (MSI and their lengths are measured automatically. Then, the height extraction from SAR images based on a model matching technique for some appropriate samples. Finally, obtain the other heights based on the simple linear regression analysis. This approach which combines the data and feature from different satellite systems to make up the flaws for each other is not only efficient and low-cost, but also satisfy the basic accuracy requirement.

  16. Comparison of Oil Spill Classifications Using Fully and Compact Polarimetric SAR Images

    Directory of Open Access Journals (Sweden)

    Yuanzhi Zhang

    2017-02-01

    Full Text Available In this paper, we present a comparison between several algorithms for oil spill classifications using fully and compact polarimetric SAR images. Oil spill is considered as one of the most significant sources of marine pollution. As a major difficulty of SAR-based oil spill detection algorithms is the classification between mineral and biogenic oil, we focus on quantitatively analyzing and comparing fully and compact polarimetric satellite synthetic aperture radar (SAR modes to detect hydrocarbon slicks over the sea surface, discriminating them from weak-damping surfactants, such as biogenic slicks. The experiment was conducted on quad-pol SAR data acquired during the Norwegian oil-on-water experiment in 2011. A universal procedure was used to extract the features from quad-, dual- and compact polarimetric SAR modes to rank different polarimetric SAR modes and common supervised classifiers. Among all the dual- and compact polarimetric SAR modes, the π/2 mode has the best performance. The best supervised classifiers vary and depended on whether sufficient polarimetric information can be obtained in each polarimetric mode. We also analyzed the influence of the number of polarimetric parameters considered as inputs for the supervised classifiers, onto the detection/discrimination performance. We discovered that a feature set with four features is sufficient for most polarimetric feature-based oil spill classifications. Moreover, dimension reduction algorithms, including principle component analysis (PCA and the local linear embedding (LLE algorithm, were employed to learn low dimensional and distinctive information from quad-polarimetric SAR features. The performance of the new feature sets has comparable performance in oil spill classification.

  17. A despeckle filter for the Cassini SAR images of Titan's surface

    Science.gov (United States)

    Bratsolis, Emmanuel; Solomonidou, Anezina; Bampasidis, Georgios; Le Mouelic, Stephane; Sotin, Christophe; Coustenis, Athena; Moussas, Xenophon; Kyriakopoulos, Konstantinos

    2010-05-01

    Cassini carries a multimode Ku-band (13.78 GHz) radar instrument designed to probe the surface of Titan and that of other targets in the Saturn system in four operating modes: imaging, altimetry, scatterometry, and radiometry. The Synthetic Aperture Radar (SAR) mode is used at altitudes under ~4000 km, resulting in spatial resolution ranging from ~350 m to >1 km. Images are acquired either left or right of nadir using 2-7 looks. A swath 120-450 km wide is created from 5 antenna beams. SAR coverage is dependent on spacecraft range and orbital geometry. Radar backscatter variations in SAR images can be interpreted in terms of variations of surface slope, near-surface roughness, or near-surface dielectric properties. The images obtained using SAR revealed that Titan has very complex surface (Elachi et al. 2005). A filtering technique is applied to obtain the restored image. One of the major problems hampering the derivation of meaningful texture information from SAR imagery is the speckle noise. It overlays "real" structures and causes gray value variations even in homogeneous parts of the image. Our method is based on probabilistic methods and regards an image as a random element drawn from a prespecified set of possible images. The TSPR (Total Sum Preserving Regularization) filter used here is based on a membrane model Markov random field approximation with a Gaussian conditional probability density function optimized by a synchronous local iterative method. The final form of despeckling gives a sum-preserving regularization for the pixel values of the image. The TSPR method preserves the mean values of local homogeneous regions and decreases the standard deviation up to six times (Bratsolis and Sigelle, 2003). The despeckle filter can be used as intermediate stage for the extraction of meaningful regions that correspond to structural units in the scene or distinguish objects of interest (Bratsolis, 2009). References E. Bratsolis, and M. Sigelle, "Fast SAR Image

  18. Digital image mosaics of the nearshore coastal waters of selected areas on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including...

  19. Heat equation inversion framework for average SAR calculation from magnetic resonance thermal imaging.

    Science.gov (United States)

    Alon, Leeor; Sodickson, Daniel K; Deniz, Cem M

    2016-10-01

    Deposition of radiofrequency (RF) energy can be quantified via electric field or temperature change measurements. Magnetic resonance imaging has been used as a tool to measure three dimensional small temperature changes associated with RF radiation exposure. When duration of RF exposure is long, conversion from temperature change to specific absorption rate (SAR) is nontrivial due to prominent heat-diffusion and conduction effects. In this work, we demonstrated a method for calculation of SAR via an inversion of the heat equation including heat-diffusion and conduction effects. This method utilizes high-resolution three dimensional magnetic resonance temperature images and measured thermal properties of the phantom to achieve accurate calculation of SAR. Accuracy of the proposed method was analyzed with respect to operating frequency of a dipole antenna and parameters used in heat equation inversion. Bioelectromagnetics. 37:493-503, 2016. © 2016 Wiley Periodicals, Inc.

  20. 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.

  1. A Modified Frequency Domain Imaging Method for One-stationary Bistatic SAR

    Directory of Open Access Journals (Sweden)

    Jin Ri-chu

    2014-04-01

    Full Text Available Bistatic Synthetic Aperture Radar (BiSAR in one-stationary mode has many advantages over the traditional monostatic SAR. Its echo, however, shows serious space variance in both range and azimuth directions due to its complex imaging geometry, making it hard to be processed by the frequency methods used in the monostatic SAR. To solve that problem, a method based on blocks and interpolation has been proposed by Wang Yu et al.. With this method, points can be well focused except for those located on the edge of each block. In this paper, a modified method is put forward, which adopts new block-dividing strategy and new mapping relationship in the interpolation. With the proposed method, points on the edge can also be well focused, making the quality of the final image greatly improved.

  2. An estimation method for InSAR interferometric phase combined with image auto-coregistration

    Institute of Scientific and Technical Information of China (English)

    LI Hai; LI Zhenfang; LIAO Guisheng; BAO Zheng

    2006-01-01

    In this paper we propose a method to estimate the InSAR interferometric phase of the steep terrain based on the terrain model of local plane by using the joint subspace projection technique proposed in our previous paper. The method takes advantage of the coherence information of neighboring pixel pairs to auto-coregister the SAR images and employs the projection of the joint signal subspace onto the corresponding joint noise subspace to estimate the terrain interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the interferometric phase (interferogram) of very steep terrain even if the coregistration error reaches one pixel. The effectiveness of the method is verified via simulated data and real data.

  3. Coupling Regular Tessellation with Rjmcmc Algorithm to Segment SAR Image with Unknown Number of Classes

    Science.gov (United States)

    Wang, Y.; Li, Y.; Zhao, Q. H.

    2016-06-01

    This paper presents a Synthetic Aperture Radar (SAR) image segmentation approach with unknown number of classes, which is based on regular tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC') algorithm. First of all, an image domain is portioned into a set of blocks by regular tessellation. The image is modeled on the assumption that intensities of its pixels in each homogeneous region satisfy an identical and independent Gamma distribution. By Bayesian paradigm, the posterior distribution is obtained to build the region-based image segmentation model. Then, a RJMCMC algorithm is designed to simulate from the segmentation model to determine the number of homogeneous regions and segment the image. In order to further improve the segmentation accuracy, a refined operation is performed. To illustrate the feasibility and effectiveness of the proposed approach, two real SAR image is tested.

  4. High resolution mosaic image of capillaries in human retina by adaptive optics

    Institute of Scientific and Technical Information of China (English)

    Ning Ling; Yudong Zhang; Xuejun Rao; Cheng Wang; Yiyun Hu; Wenhan Jiang

    2005-01-01

    Adaptive optics (AO) has been proved as a powerful means for high resolution imaging of human retina.Because of the pixel number of charge-coupled device (CCD) camera, the field of view is limited to 1°.In order to have image of capillaries around vivo human fovea, we use mosaic method to obtain high resolution image in area of 6°× 6°. Detailed structures of capillaries around fovea with resolution of 2.3μm are clearly shown. Comparison shows that this method has a much higher resolution than current clinic retina imaging methods.

  5. 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.

  6. Matching suitable feature construction for SAR images based on evolutionary synthesis strategy

    Institute of Scientific and Technical Information of China (English)

    Bu Yanlong; Tang Geshi; Liu Hongfu; Pan Liang

    2013-01-01

    In the paper, a set of algorithms to construct synthetic aperture radar (SAR) matching suitable features are firstly proposed based on the evolutionary synthesis strategy. During the pro-cess, on the one hand, the indexes of primary matching suitable features (PMSFs) are designed based on the characteristics of image texture, SAR imaging and SAR matching algorithm, which is a process involving expertise;on the other hand, by designing a synthesized operation expression tree based on PMSFs, a much more flexible expression form of synthesized features is built, which greatly expands the construction space. Then, the genetic algorithm-based optimized searching process is employed to search the synthesized matching suitable feature (SMSF) with the highest efficiency, largely improving the optimized searching efficiency. In addition, the experimental results of the airborne synthetic aperture radar ortho-images of C-band and P-band show that the SMSFs gained via the algorithms can reflect the matching suitability of SAR images accurately and the matching probabilities of selected matching suitable areas of ortho-images could reach 99 ± 0.5%.

  7. 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.

  8. Terrain topographic inversion using single-pass polarimetric SAR image data

    Institute of Scientific and Technical Information of China (English)

    JIN Yaqiu; LUO Lin

    2004-01-01

    The shift of polarization orientation angle ψat the maximum of co-polarized or cross-polarized back-scattering signature can be used to estimate the surface slopes. It has been utilized to generate the digital elevation mapping (DEM) and terrain topography using two-pass fully polarimetric SAR or interferometric SAR (INSAR) image data. This paper presents an approach to DEM inversion by using a single pass of polarimetric SAR data. The ψ shift is derived, by using the Mueller matrix solution, as a function of three Stokes parameters, /vs, Ihs, Us, which are measured by the SAR polarimetry. Using the Euler angles transformation, the orientation angle ψ is related to both the range and azimuth angles of the tilted surface and radar viewing geometry, as has been discussed by many authors. When only a single-pass SAR data is available, the adaptive thresholding method and image morphological thinning algorithm for linear textures are proposed to first determine the azimuth angle. Then, making use of full multi-grid algorithm, both the range and azimuth angles are utilized to solve the Poisson equation of DEM to produce the terrain topography.

  9. A NEW APPROACH TO FAST MOSAIC UAV IMAGES

    Directory of Open Access Journals (Sweden)

    Q. Liu

    2012-09-01

    Full Text Available Unmanned Aerial Vehicles (UAVs have been widely used to acquire high quality terrain images of the areas of interest, particularly when such a task could potentially risk human life or even impossible as the areas cannot be accessed easily by surveyors. Once the images have been obtained, traditional photogrammetric processing process can be used to establish a relative orientation model and then, absolute orientation model with the procedures of space resection and intersection. In many such applications, the geo- referenced images which are stitched together to represent the geospatial relationships for the feature objects are sufficient. A fast or near real-time processing approach for UAV images using GPS/INS data has being investigated for years. One beneficial application of such approach is the capability of quick production of geo-referenced images for various engineering or business activities, such as urban and road planning, the site selection of factories and bridges, etc. In this paper, we have proposed a new fast processing approach for the UAV images collected with an integrated GPS/INS/Vision system. The approach features that the corresponding points between images have been determined, and then coordinate transformation is carried out to implement image stitching. The accuracy of corresponding points normally affects the quality of stitched images, but the results of our experiments revealed that the image stitching errors were obvious even the accuracy of corresponding points was high. The stitching errors could be caused by the changes of surface elevation.

  10. ICA Based Speckle Filtering for Target Extraction in SAR Images Using Adaptive Space Separation

    Institute of Scientific and Technical Information of China (English)

    LI Yu-tong; ZHOU Yue; YANG Lei

    2008-01-01

    A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information entropy (WIE) incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE (threshold versus weighted-information-entropy), independent components are adaptively separated and the bases are classified accordingly. Thus, the image space is separated into two subspaces: "clean" and "noise". Then, a proposed nonlinear operator ABO is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.

  11. A NEW UNSUPERVISED CLASSIFICATION ALGORITHM FOR POLARIMETRIC SAR IMAGES BASED ON FUZZY SET THEORY

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Xie Yan; Pi Yiming; Hou Yinming

    2006-01-01

    In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combination of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classification accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by experiments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data.

  12. SAR image despeckling based on edge detection and nonsubsampled second generation bandelets

    Institute of Scientific and Technical Information of China (English)

    Zhang Wenge; Liu Fang; Jiao Licheng; Gao Xinbo

    2009-01-01

    To preserve the sharp features and details of the synthetic aperture radar (SAR) image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform (NSBT) domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges are detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Ganssian scale mixture (BLS-GSM).

  13. SAR image classification with non-stationary multinomial logistic mixture of amplitude and texture densities

    NARCIS (Netherlands)

    Kayabol, K.; Voisin, A.; Zerubia, J.

    2011-01-01

    We combine both amplitude and texture statistics of the Synthetic Aperture Radar (SAR) images using Products of Experts (PoE) approach for classification purpose. We use Nakagami density to model the class amplitudes. To model the textures of the classes, we exploit a non-Gaussian Markov Random Fiel

  14. 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...... be easily assessed when using the Random Forests algorithm....

  15. A Novel Speckle Filter for SAR Images Based on Informationtheoretic Heterogeneity Measurements

    Institute of Scientific and Technical Information of China (English)

    Chen Jie; Zhu Jing; Li Chunsheng; Zhou Yinqing

    2009-01-01

    Most adaptive speckle filters are based on the local coefficient of variation, which serves to measure the heterogeneity of synthetic aperture radar (SAR) images. However, the sensitivity of the measurements to speckle and noise of SAR images would greatly deteriorate the speckle reduction. This article, based upon the information theory, presents a novel parameter for the heterogeneity measurement as a general index to quantitate the SAR image heterogeneity. Further, as a new speckle reduction algorithm based on the aforesaid quantitative heterogeneity measurements, it puts forward a heterogeneity-based speckle reduction filter (HBSRF), which uses the information-theoretic heterogeneity measurements as a criterion to classify the SAR images as belonging to homogeneous or heterogeneous regions. Then the finite iteration procedure and edge detection algorithms are adopted to strike the best balance between speckle reduction and edge preservation. The results from the computer simulation have demonstrated that the proposed effective method is superior to the conventional speckle filters based on the local coefficient of variation both in textural preservation and speckle reduction.

  16. 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.

  17. 14-bit pipeline-SAR ADC for image sensor readout circuits

    Science.gov (United States)

    Wang, Gengyun; Peng, Can; Liu, Tianzhao; Ma, Cheng; Ding, Ning; Chang, Yuchun

    2015-03-01

    A two stage 14bit pipeline-SAR analog-to-digital converter includes a 5.5bit zero-crossing MDAC and a 9bit asynchronous SAR ADC for image sensor readout circuits built in 0.18um CMOS process is described with low power dissipation as well as small chip area. In this design, we employ comparators instead of high gain and high bandwidth amplifier, which consumes as low as 20mW of power to achieve the sampling rate of 40MSps and 14bit resolution.

  18. A novel autofocus algorithm based on maximum total variation criteria for SAR images

    Institute of Scientific and Technical Information of China (English)

    MA Lun; LIAO Guisheng

    2007-01-01

    A novel autofocus algorithm for synthetic aperture radar (SAR)based on total variation is presented in this Paper.The method,which starts with a complex phase-degraded SAR image,after the phase errors model is introduced into the range-compressed phase-history domain,carries out phase errors correction by changing the focus till the total variation of the azimuth profile is maximized.Compared with the minimum entropy autofocus algorithm,the autofocus algorithm has less computational complexity and is easier to implement.The simulation and the processing results of the measured data show the validity of the proposed method.

  19. Oil spill detection from SAR image using SVM based classification

    Directory of Open Access Journals (Sweden)

    A. A. Matkan

    2013-09-01

    Full Text Available In this paper, the potential of fully polarimetric L-band SAR data for detecting sea oil spills is investigated using polarimetric decompositions and texture analysis based on SVM classifier. First, power and magnitude measurements of HH and VV polarization modes and, Pauli, Freeman and Krogager decompositions are computed and applied in SVM classifier. Texture analysis is used for identification using SVM method. The texture features i.e. Mean, Variance, Contrast and Dissimilarity from them are then extracted. Experiments are conducted on full polarimetric SAR data acquired from PALSAR sensor of ALOS satellite on August 25, 2006. An accuracy assessment indicated overall accuracy of 78.92% and 96.46% for the power measurement of the VV polarization and the Krogager decomposition respectively in first step. But by use of texture analysis the results are improved to 96.44% and 96.65% quality for mean of power and magnitude measurements of HH and VV polarizations and the Krogager decomposition. Results show that the Krogager polarimetric decomposition method has the satisfying result for detection of sea oil spill on the sea surface and the texture analysis presents the good results.

  20. Pantir - a Dual Camera Setup for Precise Georeferencing and Mosaicing of Thermal Aerial Images

    Science.gov (United States)

    Weber, I.; Jenal, A.; Kneer, C.; Bongartz, J.

    2015-03-01

    Research and monitoring in fields like hydrology and agriculture are applications of airborne thermal infrared (TIR) cameras, which suffer from low spatial resolution and low quality lenses. Common ground control points (GCPs), lacking thermal activity and being relatively small in size, cannot be used in TIR images. Precise georeferencing and mosaicing however is necessary for data analysis. Adding a high resolution visible light camera (VIS) with a high quality lens very close to the TIR camera, in the same stabilized rig, allows us to do accurate geoprocessing with standard GCPs after fusing both images (VIS+TIR) using standard image registration methods.

  1. Semi-supervised Learning for Classification of Polarimetric SAR Images Based on SVM-Wishart

    Directory of Open Access Journals (Sweden)

    Hua Wen-qiang

    2015-02-01

    Full Text Available In this study, we propose a new semi-supervised classification method for Polarimetric SAR (PolSAR images, aiming at handling the issue that the number of train set is small. First, considering the scattering characters of PolSAR data, this method extracts multiple scattering features using target decomposition approach. Then, a semi-supervised learning model is established based on a co-training framework and Support Vector Machine (SVM. Both labeled and unlabeled data are utilized in this model to obtain high classification accuracy. Third, a recovery scheme based on the Wishart classifier is proposed to improve the classification performance. From the experiments conducted in this study, it is evident that the proposed method performs more effectively compared with other traditional methods when the number of train set is small.

  2. PSI Deformation Map Retrieval by Means of Temporal Sublook Coherence on Reduced Sets of SAR Images

    Directory of Open Access Journals (Sweden)

    Rubén Iglesias

    2015-01-01

    Full Text Available Prior to the application of any persistent scatterer interferometry (PSI technique for the monitoring of terrain displacement phenomena, an adequate pixel selection must be carried out in order to prevent the inclusion of noisy pixels in the processing. The rationale is to detect the so-called persistent scatterers, which are characterized by preserving their phase quality along the multi-temporal set of synthetic aperture radar (SAR images available. Two criteria are mainly available for the estimation of pixels’ phase quality, i.e., the coherence stability and the amplitude dispersion or permanent scatterers (PS approach. The coherence stability method allows an accurate estimation of the phase statistics, even when a reduced number of SAR acquisitions is available. Unfortunately, it requires the multi-looking of data during the coherence estimation, leading to a spatial resolution loss in the final results. In contrast, the PS approach works at full-resolution, but it demands a larger number of SAR images to be reliable, typically more than 20. There is hence a clear limitation when a full-resolution PSI processing is to be carried out and the number of acquisitions available is small. In this context, a novel pixel selection method based on exploiting the spectral properties of point-like scatterers, referred to as temporal sublook coherence (TSC, has been recently proposed. This paper seeks to demonstrate the advantages of employing PSI techniques by means of TSC on both orbital and ground-based SAR (GB-SAR data when the number of images available is small (10 images in the work presented. The displacement maps retrieved through the proposed technique are compared, in terms of pixel density and phase quality, with traditional criteria. Two X-band datasets composed of 10 sliding spotlight TerraSAR-X images and 10 GB-SAR images, respectively, over the landslide of El Forn de Canillo (Andorran Pyrenees, are employed for this study. For both

  3. On semantics-based spatial data preprocessing: a case study in non-ortho RS images mosaic

    Science.gov (United States)

    Wang, Daojun; Gong, Jianhua; Ma, Ai-Nai

    2008-10-01

    A Three-Level Information Architecture containing Syntactic Information, Semantic Information and Pragmatic Information is put forward in Comprehensive Information Theory (CIT). From this point of view, spatial data analysis is in cooperation with semantic information and Spatial Data Preprocessing (SDP) is corresponding to syntactic information. However, in many practical applications, SDP based only on syntactic information can not get a good effect. Semantics-based preprocessing may be an effective scheme. RS images mosaic is a typical SDP where optimal mosaic line extraction is the crux. Lots of researches based on syntactic information are effective just for orthophoto maps. In this paper, an overall optimal mosaic line extraction scheme has been addressed for non-Ortho RS images. It is argued that there is no projection error in the projection datum fitted by Ground Control Points (GCPs), or regional main height surface which can be recognized in medium resolution RS images. Based on above reasons, the method suggests that GCPs collecting for precise geometrical correction should be on the main height surface, as well as the mosaic line extracting for RS images mosaic. Three sheets of CBERS CCD images of Taiyuan are taken as the experimental data. According to the afore-mentioned method, by collecting GCPs in wide riverbeds, all three sheets are rectified to an existing ETM+ mosaic image. And then, the central lines of wide riverbeds in the overlapping areas are extracted as the mosaic line. The experimental result indicates that this method can extract an overall optimal mosaic line and eliminate the visual texture seam-line effectively, even for non-Ortho RS images. It concludes that SDP based on semantic information can play a good role in spatial data applications.

  4. AUTOMATIC SHIP DETECTION IN SINGLE-POL SAR IMAGES USING TEXTURE FEATURES IN ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    E. Khesali

    2015-12-01

    Full Text Available This paper presents a novel method for detecting ships from high-resolution synthetic aperture radar (SAR images. This method categorizes ship targets from single-pol SAR images using texture features in artificial neural networks. As such, the method tries to overcome the lack of an operational solution that is able to reliably detect ships with one SAR channel. The method has the following three main stages: 1 feature extraction; 2 feature selection; and 3 ship detection. The first part extracts different texture features from SAR image. These textures include occurrence and co occurrence measures with different window sizes. Then, best features are selected. Finally, the artificial neural network is used to extract ship pixels from sea ones. In post processing stage some morphological filters are used to improve the result. The effectiveness of the proposed method is verified using Sentinel-1 data in VV polarization. Experimental results indicate that the proposed algorithm can be implemented with time-saving, high precision ship extraction, feature analysis, and detection. The results also show that using texture features the algorithm properly discriminates speckle noise from ships.

  5. IMAGING AND MTI PROCESSING BASED ON DUAL-FREQUENCIES DUAL-APERTURES SPACEBORNE SAR

    Institute of Scientific and Technical Information of China (English)

    Yin Jianfeng; Li Daojing; Wu Yirong

    2009-01-01

    Based on dual-frequencies dual-apertures spaceborne SAR (Synthetic Aperture Radar), a new SAR system with four receiving channels and two operation modes is presented in this paper. SAR imaging and Moving Target Indication (MTI) are studied in this system. High resolution imaging with wide swath is implemented by the Mode I, and MTI is completed by the Mode II. High azimuth resolution is achieved by the Displaced Phase Center (DPC) multibeam technique. And the Coherent Accumulation (CA) method, which combines dual channels data of different carrier frequency, is used to enhance the range resolution. For the data of different carrier frequency, the two aperture interferometric processing is executed to implement clutter cancellation, respectively. And the couple of clutter suppressed data are employed to implement Dual Carrier Frequency Conjugate Processing (DCFCP), then both slow and fast moving targets detection can be completed, followed by moving target imaging. The simulation results show the validity of the signal processing method of this new SAR system.

  6. An efficient two-objective automatic SAR image segmentation framework using artificial immune system

    Science.gov (United States)

    Yang, Dongdong; Niu, Ruican; Fei, Rong; Jiang, Qiaoyong; Li, Hongye; Cao, Zijian

    2015-12-01

    Here, an efficient multi-objective automatic segmentation framework (MASF) is formulated and applied to synthetic aperture radar (SAR) image unsupervised classification. In the framework, three important issues are presented: 1) two reasonable image preprocessing techniques, including spatial filtering and watershed operator, are discussed at the initial stage of the framework; 2)then, an efficient immune multi-objective optimization algorithm with uniform clone, adaptive selection by online nondominated solutions, and dynamic deletion in diversity maintenance is proposed; 3 two very simple, but very efficient conflicting clustering validity indices are incorporated into the framework and simultaneously optimized. Two simulated SAR data and two complicated real images are used to quantitatively validate its effectiveness. In addition, four other state-of-the-art image segmentation methods are employed for comparison.

  7. SAR IMAGING SIMULATION OF HORIZONTAL FULLY TWO-DIMENSIONAL INTERNAL WAVES

    Institute of Scientific and Technical Information of China (English)

    SHEN Hui; HE Yi-Jun

    2006-01-01

    Based on the research of Lynett and Liu, a new horizontal fully two-dimensional internal wave propagation model with rotation effect was deduced, which can be used to simulate the characteristics of internal waves in a horizontal fully two-dimensional plane. By combining the imaging mechanism of Synthetic Aperture Radar(SAR), a simulation procedure was fatherly acquired, which can simulate the propagation characteristics of oceanic internal waves into SAR images. In order to evaluate the validity of the proposed simulation procedure, case studies are performed in South China Sea and results from simulation procedure are analyzed in detail. A very good consistency was found between the simulation results and satellite images. The proposed simulation procedure will be a possible foundation for the quantitative interpretation of internal waves from fully two-dimensional satellite images.

  8. 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%.

  9. 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.

  10. Global Controlled Mosaic of Mercury from MESSENGER Orbital Images

    Science.gov (United States)

    Becker, K. J.; Weller, L. A.; Edmundson, K. L.; Becker, T. L.; Robinson, M. S.; Solomon, S. C.

    2011-12-01

    The MESSENGER spacecraft entered orbit around Mercury in March 2011. Since then, the Mercury Dual Imaging System (MDIS) has been steadily acquiring images from the monochrome, narrow-angle camera (NAC) and the multispectral, wide-angle camera (WAC). With these images, the U.S. Geological Survey (USGS) is constructing a global, controlled monochrome base map of the planet using the Integrated Software for Imagers and Spectrometers (ISIS3) [1]. Although the characterization of MESSENGER spacecraft's navigation and attitude data has proven to be reliable to date, an element of uncertainty in these parameters is unavoidable. This leads to registration offsets between images in the base map. To minimize these errors, images are controlled using a least-squares bundle adjustment that provides refined spacecraft attitude and position parameters plus triangulated ground coordinates of image tie points. As a first effort, 4542 images (2781 NAC, 1761 WAC G filter) have been controlled with a root mean squared error of 0.25 pixels in image space [2]. A preliminary digital elevation model (DEM) is also being produced from the large number of ground points (~ 47,000) triangulated in this adjustment. The region defined by these points ranges from 80°S to 86°N latitude and 158°E to 358°E longitude. A symmetric, unimodal distribution and a dynamic range of 10.5 km characterize the hypsometry of this area. Minimum, maximum, and mean elevations are -5.0, 5.5, and -0.2 km relative to the mean radius of Mercury (2440 km) as defined by the mission. The USGS will use the DEM and base map for the construction of a registered color (WAC) map of high spatial integrity essential for reliable scientific interpretation of the color data. Ongoing improvements to the base map will be made as new images from MDIS become available, providing continuity in resolution, illumination, and viewing conditions. Additional bundle adjustments will further improve spacecraft attitude. The results from

  11. 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.

  12. Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics

    Science.gov (United States)

    Davis, Philip A.

    2012-01-01

    Airborne digital-image data were collected for the Arizona part of the Colorado River ecosystem below Glen Canyon Dam in 2009. These four-band image data are similar in wavelength band (blue, green, red, and near infrared) and spatial resolution (20 centimeters) to image collections of the river corridor in 2002 and 2005. These periodic image collections are used by the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey to monitor the effects of Glen Canyon Dam operations on the downstream ecosystem. The 2009 collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits, unlike the image sensors that GCMRC used in 2002 and 2005. This study examined the performance of the SH52 sensor, on the basis of the collected image data, and determined that the SH52 sensor provided superior data relative to the previously employed sensors (that is, an early ADS40 model and Zeiss Imaging's Digital Mapping Camera) in terms of band-image registration, dynamic range, saturation, linearity to ground reflectance, and noise level. The 2009 image data were provided as orthorectified segments of each flightline to constrain the size of the image files; each river segment was covered by 5 to 6 overlapping, linear flightlines. Most flightline images for each river segment had some surface-smear defects and some river segments had cloud shadows, but these two conditions did not generally coincide in the majority of the overlapping flightlines for a particular river segment. Therefore, the final image mosaic for the 450-kilometer (km)-long river corridor required careful selection and editing of numerous flightline segments (a total of 513 segments, each 3.2 km long) to minimize surface defects and cloud shadows. The final image mosaic has a total of only 3 km of surface defects. The final image mosaic for the western end of the corridor has

  13. EXTRACTION OF COASTLINES WITH FUZZY APPROACH USING SENTINEL-1 SAR IMAGE

    Directory of Open Access Journals (Sweden)

    N. Demir

    2016-06-01

    Full Text Available Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the

  14. Monitoring water level using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) images

    Science.gov (United States)

    Stavroulaki, Eleni; Alexakis, Dimitrios D.; Tsanis, Ioannis K.

    2017-04-01

    Interferometric Synthetic Aperture Radar (SAR) methodology can successfully detect phase variations related to water level changes and produce corresponding water level maps. Two lakes located in Western Crete, Greece, namely Lake Kournas and Lake Agia were used as case studies to study water level change with means of SAR interferometry. The change of the water surface in the lake is examined over a period of two years, 2015-2016 using Sentinel 1 IW mode images and in situ water level data. Initially, all the SAR images were preprocessed in terms of atmospheric and radiometric corrections. Various interferograms were developed to study the multi-temporal regime of water level in both lakes. Optical satellite sensor data (Landsat 8) were used to study the vegetation regime and how this affect the interferogram processing. The results denoted the fact that the combination of SAR backscattering intensity and unwrapped phase water level data can provide additional insight into hydrological state. It is also shown that integrated analysis of the backscattering mechanism and interferometric characteristics can considerably enhance the reliability of the water-level retrieval scheme and optimize the capture of hydrological patterns spatial distribution. Keywords: Sentinel-1, interferogram, water level, Backscattering

  15. Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis

    Science.gov (United States)

    Lee, Isabella K.; Shamsoddini, Ali; Li, Xiaofeng; Trinder, John C.; Li, Zeyu

    2016-07-01

    Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. A morphology-based analyses of the subsequent reconstructions of the hurricane eyes shows a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.

  16. 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.

  17. 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.

  18. The Application of Cloud Computing to the Creation of Image Mosaics and Management of Their Provenance

    CERN Document Server

    Berriman, G Bruce; Groth, Paul; Juve, Gideon

    2010-01-01

    We have used the Montage image mosaic engine to investigate the cost and performance of processing images on the Amazon EC2 cloud, and to inform the requirements that higher-level products impose on provenance management technologies. We will present a detailed comparison of the performance of Montage on the cloud and on the Abe high performance cluster at the National Center for Supercomputing Applications (NCSA). Because Montage generates many intermediate products, we have used it to understand the science requirements that higher-level products impose on provenance management technologies. We describe experiments with provenance management technologies such as the "Provenance Aware Service Oriented Architecture" (PASOA).

  19. Straight Line Extraction by Heuristic Search for SAR Image%SAR 图像启发式搜索直线提取

    Institute of Scientific and Technical Information of China (English)

    曾阳帆; 刘伟; 陈建宏; 赵拥军

    2015-01-01

    Straight line feature is the basis of linear target recognition.The existing heuristic search algorithms are suit-able for straight line feature extraction in optical image while performing poor in SAR image.For this problem,a straight line extraction method for SAR image based on heuristic search is presented.Firstly,SAR image is filtered by Frost filter. Then,edges are detected by ratio of exponential weighted average (ROEWA)operator and non-maxima suppression location algorithm is adopted to obtain the binary edge map.Finally,considering the local information sufficiently,the strategy of search twice and the principle of “go straight”is utilized and the cost function and rules of heuristic search are designed. Then the straight line extraction is completed.The experiment results show good anti-noise performance and fracture resist-ance of the proposed method which can effectively describe the straight line feature of SAR images.%直线特征是识别线状目标的基础,现有启发式搜索算法仅适用于光学图像的直线特征提取,对 SAR 图像效果并不理想。针对该问题,提出一种 SAR 图像直线特征提取的启发式搜索算法。首先对 SAR 图像进行 Frost滤波,然后利用指数加权均值比(ROEWA)算子进行边缘检测,再利用非极值抑制得到边缘二值图,最后采用二次搜索策略及“直线走原则”,充分考虑局部信息,设计启发式搜索的代价函数及搜索规则,实现直线特征提取。实验结果表明,该方法具有较好的抗噪性和抗断裂能力,能够有效地提取出 SAR 图像中的直线特征。

  20. Contextual descriptors and neural networks for scene analysis in VHR SAR images

    Science.gov (United States)

    Del Frate, Fabio; Picchiani, Matteo; Falasco, Alessia; Schiavon, Giovanni

    2016-10-01

    The development of SAR technology during the last decade has made it possible to collect a huge amount of data over many regions of the world. In particular, the availability of SAR images from different sensors, with metric or sub-metric spatial resolution, offers novel opportunities in different fields as land cover, urban monitoring, soil consumption etc. On the other hand, automatic approaches become crucial for the exploitation of such a huge amount of information. In such a scenario, especially if single polarization images are considered, the main issue is to select appropriate contextual descriptors, since the backscattering coefficient of a single pixel may not be sufficient to classify an object on the scene. In this paper a comparison among three different approaches for contextual features definition is presented so as to design optimum procedures for VHR SAR scene understanding. The first approach is based on Gray Level Co- Occurrence Matrix since it is widely accepted and several studies have used it for land cover classification with SAR data. The second approach is based on the Fourier spectra and it has been already proposed with positive results for this kind of problems, the third one is based on Auto-associative Neural Networks which have been already proven effective for features extraction from polarimetric SAR images. The three methods are evaluated in terms of the accuracy of the classified scene when the features extracted using each method are considered as input to a neural network classificator and applied on different Cosmo-SkyMed spotlight products.

  1. The Next Generation of the Montage Image Mosaic Toolkit

    CERN Document Server

    Berriman, G Bruce; Rusholme, B; Robitaille, T

    2016-01-01

    The scientific computing landscape has evolved dramatically in the past few years, with new schemes for organizing and storing data that reflect the growth in size and complexity of astronomical data sets. In response to this changing landscape, we are, over the next two years, deploying the next generation of the Montage toolkit ([ascl:1010.036]). The first release (October 2015) supports multi-dimensional data sets ("data cubes"), and insertion of XMP/AVM tags that allows images to "drop-in" to the WWT. The same release offers a beta-version of web-based interactive visualization of images; this includes wrappers for visualization in Python. Subsequent releases will support HEALPix (now standard in cosmic background experiments); incorporation of Montage into package managers (which enable automated management of software builds), and support for a library that will enable Montage to be called directly from Python. This next generation toolkit will inherit the architectural benefits of the current engine - ...

  2. Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms

    Directory of Open Access Journals (Sweden)

    Konstantinos N. Topouzelis

    2008-10-01

    Full Text Available This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject.

  3. 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.

  4. A SIFT Algorithm for Bistatic SAR Imaging in a Spaceborne Constant-offset Configuration (in English

    Directory of Open Access Journals (Sweden)

    Chen Shi-chao

    2013-03-01

    Full Text Available This paper focuses on the problem of the space-variance of the range-cell migration term for bistatic Synthetic Aperture Radar (SAR and proposes a Scaled Inverse Fourier Transform (SIFT-based imaging algorithm for the constant-offset configuration of bistatic SAR data processing. Range-cell migration correction is realized when two times phase multiplies and a convolution operation are executed. Because the imaging algorithm is based on a precise spectrum that has been deduced from the Geometry-Based Formula (GBF algorithm, the proposed algorithm can handle the bistatic SAR data, which were obtained with a large baseline to ratio. The advantages and effectiveness of the proposed imaging method have been verified by simulated and comparable experiments. Moreover, unlike other scaling-imaging algorithms that are dependent on the frequency modulated characteristics of the signal, the SIFT imaging algorithm is also suitable for phase-coded signals, which are used in a wider range of applications.

  5. High-resolution real-time imaging processor for airborne SAR

    Science.gov (United States)

    Yu, Weidong; Wu, Shumei

    2003-04-01

    Real-time imaging processor can provide Synthetic Aperture Radar (SAR) image in real-time mode, which is necessary for airborne SAR applications such as real-time monitoring and battle reconnaissance. This paper describes the development of high-resolution real-time imaging processor in Institute of Electronic, Chinese Academy of Sciences (IECAS). The processor uses parallel multiple channels to implement large-volume calculation needed for SAR real-time imaging. A sub-aperture method is utilized to divide azimuth Doppler spectrum into two parts, which correspond two looks. With sub-aperture method, high processing efficiency, less range migration effect and reduced memory volume can be achieved. The imaging swath is also divided into two segments, which are processed in a parallel way. Range-Doppler algorithm, which consists of range migration correction and azimuth compression, is implemented in the processor. Elaborate software programming ensures a high efficient utilization of hardware. Experimental simulation and field flight indicate this system is successful. The principles, architecture, hardware implementation of the processor are presented in this paper in details.

  6. 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.

  7. High-Resolution Ceres HAMO Color Mosaics derived from Dawn FC Images

    Science.gov (United States)

    Matz, K. D.; Schroeder, S.; Roatsch, T.; Kersten, E.; Preusker, F.; Scholten, F.; Jaumann, R.; Raymond, C. A.; Russell, C.

    2016-12-01

    Introduction: NASA's Dawn spacecraft orbited the dwarf planet Ceres from August to October 2015 in HAMO (High Altitude Mapping Orbit) with an altitude of about 1,500 km to characterize, among others, the geology, topography, and shape of Ceres. Data: The Dawn mission is equipped with a framing camera (FC) which has one broad band clear filter and seven narrow band color filters. The FC took about 4300 color filter images in HAMO with a resolution of about 140 m/pixel. Data Processing: The first steps of the processing chain towards the mosaics are: radiometric calibration and photometric correction of the images followed by ortho-rectification to the proper scale and map projection type. These steps require detailed information of the Dawn orbit, the orientation of the spacecraft, and of the topography of the target. Both, improved orientation and a high-resolution shape model, are provided by the stereo processing of the HAMO clear filter dataset. Ceres' HAMO shape model is used for the calculation of the ray intersection points and the orientation of the surface normals, while the map projection itself is done onto a reference sphere for Ceres. The final step is the controlled mosaicking of all color images to seven global mosaics of Ceres. True color: True color was achieved by scaling FC images acquired through the red, green, and blue filters (effective wavelength 653, 555, and 438 nm) to RGB values calculated from the CIE color matching functions and a Ceres reflectance spectrum. Color ratios: Color ratio image mosaics were calculated using the images of four different narrow band filters; Red channel: 965/749 nanometers (nm); Green channel: 555/749 nm; Blue channel: 438/749 nm. The color ratio image serves to cancel out the dominant brightness variations of the scene (caused by albedo variations and topographic shading) and enhances color differences related to soil mineralogy and, possibly, maturity. Download: All color mosaics will become available to the

  8. Affine Transformation Based Image Mosaics%基于仿射变换的图像序列拼接方法

    Institute of Scientific and Technical Information of China (English)

    王建华

    2003-01-01

    When Image Mosaics is produced, we optimally solve the registration transformation for adjacent frames with traditional ways. The way is slow, heavy and sometimes gets stuck in local minima. The paper provides the way that solves the transformation with a affine transformation model. The way automatically produces the answer for the frames with larger bias. It greatly speedups the process of image mosaics. It plays important role in quick and real-time making image mosaics.

  9. Stability augmentation and mosaic method of forward-scan sonar images

    Science.gov (United States)

    Xie, Shaorong; Luo, Jun; Chen, Jinbo; Xu, Yuanyu

    2012-06-01

    In recent years, forward-scan sonar is widely applied to the underwater inspection, which is not subject to the influence of light and turbidity. For expanding the monitoring scope, the image sonar is generally mounted on the pan-tilt platform of a ROV (Remotely Operated Vehicle) or survey boat. However, there are still some problems such as: 1) The field-of-view is narrow, i.e. the horizontal view angle of DIDSON (Dual-frequency identification sonar) is 29° 2) The dynamic change of a ROV or survey boat by the water disturbances will cause the target to escape from the sonar image easily; 3) The image sonar is fixed on the pan-tilt platform, and its position and posture are unceasingly changed. As a result of these problems, the obtained images may be distorted and not on the same plane. To solve the above problems, stability augmentation of pan-tilt platform based on the principle of bionic eye movements and a mosaic method of sonar images are presented. According to the principle of the vestibule-ocular reflex, an active compensation control system of the mechanical pan-tilt platform is developed. It can compensate the sonar image instability resulting from attitude variation of a ROV or survey boat during operation. Applying multi-sensor fusion technology can rectify the sonar images with different position and posture to be on a single geodetic coordinate frame for image matching. Finally, sonar images can be mosaic. A stable large-scale sonar image can be obtained. The experimental results validate that the presented method is valid.

  10. NOVEL APPROACH BASED ON DERAMPING TECHNIQUE FOR SQUINTED SLIDING SPOTLIGHT SAR IMAGING

    Institute of Scientific and Technical Information of China (English)

    Mo Yajun; Yan He; Zhao Bingji

    2013-01-01

    This paper investigates a novel approach based on the deramping technique for squinted sliding spotlight Synthetic Aperture Radar (SAR) imaging to resolve the azimuth spectrum aliasing problem.First of all,the properties of the azimuth spectrum and the squint angle impacts on the azimuth spectrum aliasing problem are analyzed.Based on the analysis result,an operation of filtering is added to the azimuth preprocessing step of traditional Two-Step Focusing Approach (TSPA) to resolve the azimuth folding problem and remove the influence of the squint angle on the azimuth spectrum aliasing problem.Then,a modified Range Migration Algorithm (RMA) is performed to obtain the precise focused image.Furthermore,the focused SAR image folding problem of traditional TSPA is illuminated in this paper.An azimuth post-processing step is proposed to unfold the aliased SAR image.Simulation experiment results prove that the proposed approach can solve the spectrum aliasing problem and process squinted sliding spotlight data efficiently.

  11. SAR Image Segmentation with Unknown Number of Classes Combined Voronoi Tessellation and Rjmcmc Algorithm

    Science.gov (United States)

    Zhao, Q. H.; Li, Y.; Wang, Y.

    2016-06-01

    This paper presents a novel segmentation method for automatically determining the number of classes in Synthetic Aperture Radar (SAR) images by combining Voronoi tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC) strategy. Instead of giving the number of classes a priori, it is considered as a random variable and subject to a Poisson distribution. Based on Voronoi tessellation, the image is divided into homogeneous polygons. By Bayesian paradigm, a posterior distribution which characterizes the segmentation and model parameters conditional on a given SAR image can be obtained up to a normalizing constant; Then, a Revisable Jump Markov Chain Monte Carlo(RJMCMC) algorithm involving six move types is designed to simulate the posterior distribution, the move types including: splitting or merging real classes, updating parameter vector, updating label field, moving positions of generating points, birth or death of generating points and birth or death of an empty class. Experimental results with real and simulated SAR images demonstrate that the proposed method can determine the number of classes automatically and segment homogeneous regions well.

  12. SAR Ice Image Classification Using Parallelepiped Classifier Based on Gram-Schmidt Spectral Technique

    Directory of Open Access Journals (Sweden)

    A.Vanitha

    2013-05-01

    Full Text Available Synthetic Aperture Radar (SAR is a special type of imaging radar that involves advanced technology and complex data processing to obtain de tailed images from the lake surface. Lake ice typically reflects more of the radar energy emi tted by the sensor than the surrounding area, which makes it easy to distinguish between the wate r and the ice surface. In this research work, SAR images are used for ice classification based on supervised and unsupervised classification algorithms. In the pre-processing stage, Hue satura tion value (HSV and Gram–Schmidt spectral sharpening techniques are applied for shar pening and resampling to attain high- resolution pixel size. Based on the performance eva luation metrics it is proved that Gram- Schmidt spectral sharpening performs better than sh arpening the HSV between the boundaries. In classification stage, Gram–Schmidt spectral tech nique based sharpened SAR images are used as the input for classifying using parallelepiped a nd ISO data classifier. The performances of the classifiers are evaluated with overall accuracy and kappa coefficient. From the experimental results, ice from water is classified more accurately in the parallelepiped supervised classification algorithm.

  13. 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.

  14. OIL SPILL DETECTION IN SAR IMAGES USING TEXTURE ENTROPY ALGORITHM AND MAHALANOBIS CLASSIFIER

    Directory of Open Access Journals (Sweden)

    POONAM M BHOGLE

    2012-12-01

    Full Text Available Oil spill has become critical in some countries, especially for countries that have seas or oceans. The situation has caused damage to the environment and polluted the water. To reduce environment damage and protect life in water, plants and soil near to disaster area .Study and analysis should be carried out .The causes and factorsthat lead to the disaster of oil spill should be studied or investigated. To analyze the problem of oil spill we consider 2 algorithms. These methods help in the analysis and identification of oil spill in SAR images. Since the 1980s, satellite-borne synthetic aperture radar (SAR has been investigated for early warning andmonitoring of marine oil spills to permit effective satellite surveillance in the marine environment. Synthetic Aperture Radar (SAR imaging system is used to monitor the marine system. Oil spill pollution plays a significant role in damaging marine ecosystem. One main advantages of SAR is that it can generate imagery under all weather conditions. Automated detection of oil spills from satellite SAR intensity imagery consists of three steps: Detection of dark spots , Extraction of features from the detected dark spots and classification of the dark spots into oil spills and look-alikes.Texture Entropy Algorithm is a method based on the utilization of texture algorithms for the discrimination of oil spill areas from the surrounding features, e.g. sea surface and look-alikes. Mahalanobis Classifier method first estimates covariance matrix and then Mahalanobis Distance is calculated for identification of oil spill or lookalike.

  15. Significant wave height estimation using azimuth cutoff of C-band RADARSAT-2 single-polarization SAR images

    Institute of Scientific and Technical Information of China (English)

    REN Lin; YANG Jingsong; ZHENG Gang; WANG Juan

    2015-01-01

    This paper proposes two simple models, look-up table (LUT) model and empirical model, to directly retrieve significant wave height (Hs) using synthetic aperture radar (SAR) azimuth cutoff (λc). Both models aim at C-band VV, HH, VH, and HV single-polarization SAR images. The LUT model relatesHs toλc, while the empirical model relatesHs to bothλc and SAR range-to-velocity (β). The LUT model coefficients are derived by simulation under different sea states and observation conditions, which depend on incidence angle (θ), wave direction (dw), andβbut are independent of polarization. The empirical model coefficients are obtained by fitting the collocated data, which only depend on polarization. To fit empirical model coefficients and validate the two models, C-band RADARSAT-2 fine quad-polarization (VV+HH+VH+HV) single-look complex (SLC) SAR images and collocated buoy data are collected. RetrievedHs, using Yang model and the two models proposed in this paper from four kinds of polarization SAR data, are compared with buoyHs. Results show that both LUT and empirical models have the capacity of retrievingHs from C-band RADARSAT-2 co-polarization SAR data, while Yang model is not suitable for these kinds of SAR data. Moreover, the empirical model is also valid for cross-polarization SAR data showing clear ocean wave stripes.

  16. Speckle reduction of SAR images using ICA basis enhancement and separation

    Institute of Scientific and Technical Information of China (English)

    Yutong Li; Yue zhou

    2007-01-01

    @@ An approach for synthetic aperture radax (SAR) image de-noising based on independent component analysis (ICA) basis images is proposed. Firstly, the basis images and the code matrix of the original image are obtained using ICA algorithm. Then, pointwise H(o)lder exponent of each basis is computed as a cost criterion for basis enhancement, and then the enhanced basis images are classified into two sets according to a separation rule which separates the clean basis from the original basis. After these key procedures for speckle reduction, the clean image is finally obtained by reconstruction on the clean basis and original code matrix. The reconstructed image shows better visual perception and image quality compared with those obtained by other traditional techniques.

  17. On the Effects of Imaging Geometry on Multipolarization SAR Features for Oil Spill Observation

    Science.gov (United States)

    Skrunes, Stine; Jones, Cathleen E.; Brekke, Camilla; Holt, Benjamin; Espeseth, Martine M.

    2016-08-01

    Polarimetric SAR is increasingly used for oil spill observation. In order to develop reliable methods for oil spill detection and characterization, the sensitivity of these measurements to the imaging geometry, including incidence angle and look direction relative to the wind, must be investigated. In this paper, we study the effects of these parameters on L-band SAR data collected with the UAVSAR instrument over experimental oil spills. The relative look direction is found to have a larger effect on the slick detectability than the incidence angle, and the detectability is better in the downwind direction compared to upwind. The features showing the best slick detectability in the conditions investigated here are the VV intensity, HV intensity, the geometric intensity and the polarization difference. The latter feature shows low dependency on imaging geometry.

  18. 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.

  19. Enhancement of SAR Ship Wake Image Based on FABEMD and Goldstein Filter

    Directory of Open Access Journals (Sweden)

    Zhang Wen-yi

    2012-12-01

    Full Text Available Enhanced SAR ship wake images with blur Kelvin wakes and reserved turbulent wakes are very important to the inversions of ship and motion parameters. This paper applies the Fast and Adaptive Bidimensional Empirical Mode Decomposition (FABEMD to decompose the SAR ship wake image into Kelvin wakes, turbulent wakes and other multiscale features, which enhances the gray intensity and spectrum contrast of Kelvin wakes to other features. Based on the FABEMD, a modified Goldstein interferogram filter is developed to further enhance the Kelvin wakes. Moreover, the moment invariants are introduced to evaluate the enhancement. Therefore, the Kelvin wakes are dramatically enhanced and the turbulent wakes are reserved. Algorithm analysis, experiments, subjective and objective evaluations show the reasonable efficiency and capabilities.

  20. Classification of PolSAR image based on quotient space theory

    Science.gov (United States)

    An, Zhihui; Yu, Jie; Liu, Xiaomeng; Liu, Limin; Jiao, Shuai; Zhu, Teng; Wang, Shaohua

    2015-12-01

    In order to improve the classification accuracy, quotient space theory was applied in the classification of polarimetric SAR (PolSAR) image. Firstly, Yamaguchi decomposition method is adopted, which can get the polarimetric characteristic of the image. At the same time, Gray level Co-occurrence Matrix (GLCM) and Gabor wavelet are used to get texture feature, respectively. Secondly, combined with texture feature and polarimetric characteristic, Support Vector Machine (SVM) classifier is used for initial classification to establish different granularity spaces. Finally, according to the quotient space granularity synthetic theory, we merge and reason the different quotient spaces to get the comprehensive classification result. Method proposed in this paper is tested with L-band AIRSAR of San Francisco bay. The result shows that the comprehensive classification result based on the theory of quotient space is superior to the classification result of single granularity space.

  1. Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

    Science.gov (United States)

    Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

    2015-01-01

    This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

  2. MAXIMUM A POSTERIORI-BASED AUTOMATIC TARGET DETECTION IN SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    Wang Yimin; An Jinwen

    2005-01-01

    The paper presents an algorithm of automatic target detection in Synthetic Aperture Radar(SAR) images based on Maximum A Posteriori(MAP). The algorithm is divided into three steps. First, it employs Gaussian mixture distribution to approximate and estimate multi-modal histogram of SAR image. Then, based on the principle of MAP, when a priori probability is both unknown and learned respectively, the sample pixels are classified into different classes c = {target,shadow, background}. Last, it compares the results of two different target detections. Simulation results preferably indicate that the presented algorithm is fast and robust, with the learned a priori probability, an approach to target detection is reliable and promising.

  3. Change Detection of High Resolution SAR Images by the Fusion of Coherent/Incoherent Information

    Directory of Open Access Journals (Sweden)

    Yang Xiang-li

    2015-10-01

    Full Text Available Aiming at detecting the change regions of high resolution Synthetic Aperture Radar (SAR images, we propose to use the Dempster-Shafer (D-S evidence theory to fuse coherent/incoherent features from sensors that form an integral part of the system. First, we use the Simple Linear Iterative Clustering (SLIC segmentation algorithm to implement multi-scale joint segmentation for multi-temporal SAR images. Second, we extract multiple intensity and coherence difference features on each segment level by SLIC using mean operator to complete the fusion of multi-scale features to get the multi-feature difference mapped by a ratio operator. Finally, we fuse the multi-feature difference maps to get the final change detection result using the D-S evidence theory. The experimental results in our study prove the effectiveness of our proposed computational algorithm.

  4. Global error minimization in image mosaicing using graph connectivity and its applications in microscopy

    Directory of Open Access Journals (Sweden)

    Parmeshwar Khurd

    2011-01-01

    Full Text Available Several applications such as multiprojector displays and microscopy require the mosaicing of images (tiles acquired by a camera as it traverses an unknown trajectory in 3D space. A homography relates the image coordinates of a point in each tile to those of a reference tile provided the 3D scene is planar. Our approach in such applications is to first perform pairwise alignment of the tiles that have imaged common regions in order to recover a homography relating the tile pair. We then find the global set of homographies relating each individual tile to a reference tile such that the homographies relating all tile pairs are kept as consistent as possible. Using these global homographies, one can generate a mosaic of the entire scene. We derive a general analytical solution for the global homographies by representing the pair-wise homographies on a connectivity graph. Our solution can accommodate imprecise prior information regarding the global homographies whenever such information is available. We also derive equations for the special case of translation estimation of an X-Y microscopy stage used in histology imaging and present examples of stitched microscopy slices of specimens obtained after radical prostatectomy or prostate biopsy. In addition, we demonstrate the superiority of our approach over tree-structured approaches for global error minimization.

  5. Quantization analysis of the real-time SAR digital image formation processor

    Energy Technology Data Exchange (ETDEWEB)

    Magotra, N.

    1988-12-01

    This report presents a quantization analysis of the digital image formation processor (IFP) of a linear-FM synthetic aperture radar (SAR). The IFP is configured as a patch processor and forms the final image by performing a two dimensional Fast Fourier Transform (FFT). The quantization analysis examines the effects of using fixed precision arithmetic in the image formation process. Theoretical bounds for the worst-case errors introduced by using fixed point arithmetic and experimental results verifying the theoretical bounds are presented. 34 refs., 23 figs., 7 tabs.

  6. Calibration of a flood inundation model using a SAR image: influence of acquisition time

    Science.gov (United States)

    Van Wesemael, Alexandra; Gobeyn, Sacha; Neal, Jeffrey; Lievens, Hans; Van Eerdenbrugh, Katrien; De Vleeschouwer, Niels; Schumann, Guy; Vernieuwe, Hilde; Di Baldassarre, Giuliano; De Baets, Bernard; Bates, Paul; Verhoest, Niko

    2016-04-01

    Flood risk management has always been in a search for effective prediction approaches. As such, the calibration of flood inundation models is continuously improved. In practice, this calibration process consists of finding the optimal roughness parameters, both channel and floodplain Manning coefficients, since these values considerably influence the flood extent in a catchment. In addition, Synthetic Aperture Radar (SAR) images have been proven to be a very useful tool in calibrating the flood extent. These images can distinguish between wet (flooded) and dry (non-flooded) pixels through the intensity of backscattered radio waves. To this date, however, satellite overpass often occurs only once during a flood event. Therefore, this study is specifically concerned with the effect of the timing of the SAR data acquisition on calibration results. In order to model the flood extent, the raster-based inundation model, LISFLOOD-FP, is used together with a high resolution synthetic aperture radar image (ERS-2 SAR) of a flood event of the river Dee, Wales, in December 2006. As only one satellite image of the considered case study is available, a synthetic framework is implemented in order to generate a time series of SAR observations. These synthetic observations are then used to calibrate the model at different time instants. In doing so, the sensitivity of the model output to the channel and floodplain Manning coefficients is studied through time. As results are examined, these suggest that there is a clear difference in the spatial variability to which water is held within the floodplain. Furthermore, these differences seem to be variable through time. Calibration by means of satellite flood observations obtained from the rising or receding limb, would generally lead to more reliable results rather than near peak flow observations.

  7. Edge Detection of PolSAR Image Based on Stochastic Distance

    OpenAIRE

    Wang, Qing; ZENG Qiming; Zhang, Haizhen; JIAO Jian

    2015-01-01

    A new edge detection methodology in PolSAR images is proposed, which is based on stochastic distance in the statistical theory and combined with complex Wishart distribution. Its main principle is inspired from the phenomenon that stochastic distance of two classes separated by an edge is closely related to the edge direction and the contrast of two classes. Simulation experiments are carried out to analyze the performance of the proposed methods. Results prove that methods have better capabi...

  8. "Phase-Enhanced" 3D Snapshot ISAR Imaging and Interferometric SAR

    Science.gov (United States)

    2009-12-28

    contained in the two nearly identical in amplitude data sets. References [5-7] provide a good discussion of the basic principles and associated radar ... Interferometrie SAR J.T. Mayhan Group 32 Technical Report ] 135 28 December 2()(W Approved for public release; distribution is unlimited. Lexington...inverse synthetie aperture radar (ISAR) images based on recent developments in high resolution spectral estimation theory. Because this technique requires

  9. Locations and types of ruptures involved in the 2008 Wenchuan earthquake revealed by SAR image matching

    Science.gov (United States)

    Kobayashi, T.; Takada, Y.; Furuya, M.; Murakami, M.

    2009-12-01

    Introduction: A catastrophic earthquake with a moment magnitude of 7.9 struck China’s Sichuan area on 12 May 2008. The rupture was thought to proceed northeastward along the Longmen Shan fault zone (LMSFZ), but it remained uncertain where and how the faults were involved in the seismic event. Interferometric SAR (InSAR) analysis has an advantage of detecting ground deformation in a vast region with high precision. However, for the Sichuan event, the standard InSAR approach was not helpful in knowing the faults directly related to the seismic rupture, due to a wide coherent loss area in the proximity of the fault zone. Thus, in order to reveal the unknown surface displacements, we conducted a SAR image matching procedure that enables us to robustly detect large ground deformation even in an incoherent area. Although similar approaches can be taken with optical images to detect surface displacements, SAR images are advantageous because of the radar’s all-weather detection capability. In this presentation we will show a strong advantage of SAR data for inland large earthquakes. Analysis Method: We use ALOS/PALSAR data on the ascending orbital paths. We process the SAR data from a level-1.0 product using a software package Gamma. After conducting coregistration between two images acquired before and after the mainshock, we divide the single-look SAR amplitude images into patches and calculate an offset between the corresponding patches by an intensity tracking method. This method is performed by cross-correlating samples of backscatter intensity of a master image with those of a slave image. To reduce the artificial offsets in range component, we apply an elevation dependent correction incorporating SRTM3 DEM data. Results: We have successfully obtained the surface deformation in range component: A sharp displacement discontinuity with a relative motion of 1-2 m appears over a length of 200 km along the LMSFZ, which demonstrates that the main rupture has proceeded

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

    Directory of Open Access Journals (Sweden)

    Tao Zhou

    2017-05-01

    Full Text Available 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.

  11. Land cover detection with SAR images of Delta del Llobregat

    Science.gov (United States)

    Godinho, R.; Borges, P. A. V.; Calado, H.; Broquetas, A.

    2016-08-01

    This work presents a study of a multitemporal set of C-band images collected by ERS-2, aiming to understand the differentiations of the backscatter intensity and the phase coherence of different land covers to find possible synergies that could improve land cover detection. The land cover analysis allowed to observe the perfect differentiation of urban areas from intensity images. The observation of multitemporal RGB compositions combining key dates of the different points of crops growth make possible to differentiate this land cover and also to observe fluctuations inside the class itself. This fluctuations present a pattern that correspond to the crop field structure, which suggests that more information can be obtained. The shrubs are difficult to detect from the intensity images, but once the observation is combined with coherence images the detection is possible. However, the coherence image must be generated from pairs of images with a temporal interval lower than three months, independently from the year of registration of each image due to the general decrease of coherence when larger intervals are used. The analysis allowed to observe the potential of this data to perfect distinguish urban, crops and shrubs. The study of the seasonal fluctuations of intensity for the crops land cover with precise ground truth for crops type and points of growth is proposed as a future line of research.

  12. Spotlight SAR sparse sampling and imaging method based on compressive sensing

    Institute of Scientific and Technical Information of China (English)

    XU HuaPing; YOU YaNan; LI ChunSheng; ZHANG LvQian

    2012-01-01

    Spotlight synthetic aperture radar (SAR) emits a chirp signal and the echo bandwidth can be reduced through dechirp processing,where the A/D sampling rate decreases accordingly at the receiver.Compressive sensing allows the compressible signal to be reconstructed with a high probability using only a few samples by solving a linear program problem.This paper presents a novel signal sampling and imaging method for application to spotlight SAR based on compressive sensing.The signal is randomly sampled after dechirp processing to form a low-dimensional sample set,and the dechirp basis is imported to reconstruct the dechirp signal.Matching pursuit (MP) is used as a reconstruction algorithm.The reconstructed signal uses polar format algorithm (PFA) for imaging.Although our novel mechanism increases the system complexity to an extent,the data storage requirements can be compressed considerably. Several simulations verify the feasibility and accuracy of spotlight SAR signal processing via compressive sensing,and the method still obtains acceptable imaging results with 10% of the original echo data.

  13. a SAR Intensity Images Change Detection Method Based on Fusion Difference Detector and Statistical Properties

    Science.gov (United States)

    Cui, B.; Zhang, Y.; Yan, L.; Cai, X.

    2017-09-01

    Detecting the land cover changes is an important application of multi-temporal synthetic aperture radar (SAR) images. This study puts forward a novel SAR change detection method which has two-steps: change detector construction and change threshold selection. For change detector construction, considering the SAR intensity images follow the gamma distribution, the conditional probabilities of the binary hypothesis test are provided, then the log likelihood ratio (LLR) combined with the log ratio (LR) to construct a detector which can enhance the degree of change to calculate the diversity degree convenient between the two images; for change threshold selection, owing to the characteristic that the curve about the ratio value of adjacent grey-level (GL) values in normalized difference map, the normalized difference map can be segmented in three parts by two thresholds selected which correspond to the regions of unchanged, backscatter enhanced and weakened separately. And as this, the change areas can be also determined simultaneously. The experimental results on different areas and sensors indicate that the proposed algorithm is effective and feasible.

  14. Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

    Science.gov (United States)

    Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

    1999-01-01

    In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

  15. Generalized interpretation scheme for arbitrary HR InSAR image pairs

    Science.gov (United States)

    Boldt, Markus; Thiele, Antje; Schulz, Karsten

    2013-10-01

    Land cover classification of remote sensing imagery is an important topic of research. For example, different applications require precise and fast information about the land cover of the imaged scenery (e.g., disaster management and change detection). Focusing on high resolution (HR) spaceborne remote sensing imagery, the user has the choice between passive and active sensor systems. Passive systems, such as multispectral sensors, have the disadvantage of being dependent from weather influences (fog, dust, clouds, etc.) and time of day, since they work in the visible part of the electromagnetic spectrum. Here, active systems like Synthetic Aperture Radar (SAR) provide improved capabilities. As an interactive method analyzing HR InSAR image pairs, the CovAmCohTM method was introduced in former studies. CovAmCoh represents the joint analysis of locality (coefficient of variation - Cov), backscatter (amplitude - Am) and temporal stability (coherence - Coh). It delivers information on physical backscatter characteristics of imaged scene objects or structures and provides the opportunity to detect different classes of land cover (e.g., urban, rural, infrastructure and activity areas). As example, railway tracks are easily distinguishable from other infrastructure due to their characteristic bluish coloring caused by the gravel between the sleepers. In consequence, imaged objects or structures have a characteristic appearance in CovAmCoh images which allows the development of classification rules. In this paper, a generalized interpretation scheme for arbitrary InSAR image pairs using the CovAmCoh method is proposed. This scheme bases on analyzing the information content of typical CovAmCoh imagery using the semisupervised k-means clustering. It is shown that eight classes model the main local information content of CovAmCoh images sufficiently and can be used as basis for a classification scheme.

  16. The Anisotropy of the Microwave Background to l = 3500 Mosaic Observations with the Cosmic Background Imager

    CERN Document Server

    Pearson, T J; Readhead, A C S; Shepherd, M C; Sievers, J L; Udomprasert, P S; Cartwright, J K; Farmer, A J; Padin, S; Myers, S T; Bond, J R; Contaldi, C R; Pen, U L; Prunet, S; Pogosyan, D; Carlstrom, J E; Kovács, J; Leitch, E M; Pryke, C L; Halverson, N W; Holzapfel, W L; Altamirano, P; Bronfman, L; Casassus, S; May, J; Joy, M

    2003-01-01

    Using the Cosmic Background Imager, a 13-element interferometer array operating in the 26-36 GHz frequency band, we have observed 40 sq deg of sky in three pairs of fields, each ~ 145 x 165 arcmin, using overlapping pointings (mosaicing). We present images and power spectra of the cosmic microwave background radiation in these mosaic fields. We remove ground radiation and other low-level contaminating signals by differencing matched observations of the fields in each pair. The primary foreground contamination is due to point sources (radio galaxies and quasars). We have subtracted the strongest sources from the data using higher-resolution measurements, and we have projected out the response to other sources of known position in the power-spectrum analysis. The images show features on scales ~ 6 - 15 arcmin, corresponding to masses ~ (5 - 80)*10^{14} Msun at the surface of last scattering, which are likely to be the seeds of clusters of galaxies. The power spectrum estimates have a resolution Delta-l = 200 an...

  17. 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.

  18. 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.

  19. SAR moving target imaging using sparse and low-rank decomposition

    Science.gov (United States)

    Ni, Kang-Yu; Rao, Shankar

    2014-05-01

    We propose a method to image a complex scene with spotlight synthetic aperture radar (SAR) despite the presence of multiple moving targets. Many recent methods use sparsity-based reconstruction coupled with phase error corrections of moving targets to reconstruct stationary scenes. However, these methods rely on the assumption that the scene itself is sparse and thus unfortunately cannot handle realistic SAR scenarios with complex backgrounds consisting of more than just a few point targets. Our method makes use of sparse and low-rank (SLR) matrix decomposition, an efficient method for decomposing a low-rank matrix and sparse matrix from their sum. For detecting the moving targets and reconstructing the stationary background, SLR uses a convex optimization model that penalizes the nuclear norm of the low rank background structure and the L1 norm of the sparse moving targets. We propose an L1-norm regularization reconstruction method to form the input data matrix, which is grossly corrupted by the moving targets. Each column of the input matrix is a reconstructed SAR image with measurements from a small number of azimuth angles. The use of the L1-norm regularization and a sparse transform permits us to reconstruct the scene with significantly fewer measurements so that moving targets are approximately stationary. We demonstrate our SLR-based approach using simulations adapted from the GOTCHA Volumetric SAR data set. These simulations show that SLR can accurately image multiple moving targets with different individual motions in complex scenes where methods that assume a sparse scene would fail.

  20. Prediction of water quality parameters from SAR images by using multivariate and texture analysis models

    Science.gov (United States)

    Shareef, Muntadher A.; Toumi, Abdelmalek; Khenchaf, Ali

    2014-10-01

    Remote sensing is one of the most important tools for monitoring and assisting to estimate and predict Water Quality parameters (WQPs). The traditional methods used for monitoring pollutants are generally relied on optical images. In this paper, we present a new approach based on the Synthetic Aperture Radar (SAR) images which we used to map the region of interest and to estimate the WQPs. To achieve this estimation quality, the texture analysis is exploited to improve the regression models. These models are established and developed to estimate six common concerned water quality parameters from texture parameters extracted from Terra SAR-X data. In this purpose, the Gray Level Cooccurrence Matrix (GLCM) is used to estimate several regression models using six texture parameters such as contrast, correlation, energy, homogeneity, entropy and variance. For each predicted model, an accuracy value is computed from the probability value given by the regression analysis model of each parameter. In order to validate our approach, we have used tow dataset of water region for training and test process. To evaluate and validate the proposed model, we applied it on the training set. In the last stage, we used the fuzzy K-means clustering to generalize the water quality estimation on the whole of water region extracted from segmented Terra SAR-X image. Also, the obtained results showed that there are a good statistical correlation between the in situ water quality and Terra SAR-X data, and also demonstrated that the characteristics obtained by texture analysis are able to monitor and predicate the distribution of WQPs in large rivers with high accuracy.

  1. The imaging algorithm of millimeter-wave forward-looking SAR

    Science.gov (United States)

    Chen, Lei; Li, Xingguang; Chen, Dianren

    2017-01-01

    It is studied a new type millimeter-wave forward-looking synthetic aperture radar (SAR) imaging algorithm in this paper, analyzes the imaging principle, echo model of point target is given, deduced the forward-looking synthetic aperture radar RD imaging algorithm, and using MATLAB imaging simulation of point target in 6, a point target simulation results from the peak of 64 * 64 slice contour and azimuth, distance to the envelope of the imaging results were analyzed, found that the distance and azimuth focusing effect is good and the side lobe does not appear distorted and tilted, proved that the system of the millimeter wave synthetic aperture radar imaging of forward-looking , simulation results demonstrate the validity of the system.

  2. Batch Co-Registration of Mars High-Resolution Images to HRSC MC11-E Mosaic

    Science.gov (United States)

    Sidiropoulos, Panagiotis; Muller, Jan-Peter

    2016-06-01

    Four NASA missions over the last forty years with onboard instruments for high-resolution orbital imaging have achieved both global coverage (with 6m CTX, 20m THEMIS-VIS and >8m Viking Orbiter cameras) as well as imaging with very high resolution in specific regions of interest (e.g. 25cm HiRISE and ≈1.5-12m MOC-NA cameras). Overall, this set of cameras have acquired more than 400,000 high-quality images of Mars with resolution between 25cm/pixel and 100m/pixel (Sidiropoulos and Muller, 2015). On the other hand, ESA has sent the only high-resolution stereo photogrammetric camera around Mars, HRSC onboard the Mars Express spacecraft, which has been mapping the Martian surface since 2004 with a resolution of 12.5 m/pixel (Jaumann et al., 2015). Initially the raw images are combined through an elaborate photogrammetric process to get (single-strip) 3D products (i.e. digital terrain models (DTMs) and derived orthorectified images (ORIs)). However, recently the processing chain has changed, and the single-strip product release was temporarily halted to be replaced by the production and release of mosaics of Mars quadrangles. The first product of this kind is the mosaic for the East part of quadrangle MC11 (i.e. the MC11-E mosaic), a product with 12.5 metres per pixel resolution in the panchromatic image and 50 metres per pixel resolution in the corresponding DTM (Gwinner et al., 2015). Such a product provides an excellent basemap to co-register and orthorectify all NASA high-resolution (≤100m/pixel) orbital images. The need for this co-registration to HRSC comes from their poor areo-referencing, which often leads to large deviations (reaching up to several kilometres) between the area they are supposed to image and the area they are actually imaging. After co-registration, all products are projected onto an common 3D coordinate system, which allows an examination of dynamic features of Mars through the changes that happen on its surface. In this work, we present the

  3. MAPSAR Image Simulation Based on L-band Polarimetric Data from the SAR-R99B Airborne Sensor (SIVAM System

    Directory of Open Access Journals (Sweden)

    Wagner Fernando da Silva

    2009-01-01

    Full Text Available This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR satellite from the airborne SAR R99B sensor (SIVAM System. MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research and DLR (German Aerospace Center targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed.

  4. Case study on the extraction of land cover information from the SAR image of a coal mining area

    Institute of Scientific and Technical Information of China (English)

    HU Zhao-ling; LI Hai-quan; DU Pei-jun

    2009-01-01

    In this study, analyses are conducted on the information features of a construction site, a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area, on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image, we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next, a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis, a classification is conducted selectively on three principal component bands with the most information. Finally, through training and experimenting with the samples, a better three-layered BP neural network was established to classify the SAR image. The results show that, assisted by texture information, the neural network classification improved the accuracy of SAR image clas-sification by 14.6%, compared with a classification by maximum likelihood estimation without texture information.

  5. New Approach for Unambiguous High-Resolution Wide-Swath SAR Imaging

    Directory of Open Access Journals (Sweden)

    Yueguan Lin

    2014-01-01

    Full Text Available The high-resolution wide-swath (HRWS SAR system uses a small antenna for transmitting waveform and multiple antennas both in elevation and azimuth for receiving echoes. It has the potential to achieve wide spatial coverage and fine azimuth resolution, while it suffers from elevation pattern loss caused by the presence of topographic height and impaired azimuth resolution caused by nonuniform sampling. A new approach for HRWS SAR imaging based on compressed sensing (CS is introduced. The data after range compression of multiple elevation apertures are used to estimate direction of arrival (DOA of targets via CS, and the adaptive digital beamforming in elevation is achieved accordingly, which avoids the pattern loss of scan-on-receive (SCORE algorithm when topographic height exists. The effective phase centers of the system are nonuniformly distributed when displaced phase center antenna (DPCA technology is adopted, which causes Doppler ambiguities under traditional SAR imaging algorithms. Azimuth reconstruction based on CS can resolve this problem via precisely modeling the nonuniform sampling. Validation with simulations and experiment in an anechoic chamber are presented.

  6. Imaging of buried and foliage-obscured objects with an ultrawide-bandwidth polarimetric SAR

    Science.gov (United States)

    Sheen, Dan R.; Lewis, Terry B.; Wei, Susan C.; Kletzli, D. W., Jr.

    1993-11-01

    The Environmental Research Institute of Michigan (ERIM) has developed a unique ground- based, portable, synthetic aperture radar (SAR). This SAR images targets in their natural backgrounds without the expense of an airborne sensor and with higher performance (bandwidth, resolution) than existing airborne systems. A horizontal 36-foot long aluminum truss supports a rail and an antenna cartridge, which is moved along the rail to allow synthetic aperture focusing. The system is fully-polarimetric and has collected data over the frequency band of 400 - 1300 MHz resulting in a nominal resolution of 0.17 m in range and 0.5 m in cross-range. The low frequency range of the system allows for penetration of soil (to shallow depths) as well as foliage and the system has been used to collect images of buried and foliage- obscured targets. The ground imagery collected to date includes steel oil drums buried at depths of up to one-meter. Both the drums as well as the disturbances due to digging the holes are visible in the imagery. Foliage imagery includes portions of a Lear jet under a mature hardwood forest. Due to the low frequency and wide bandwidth of the sensor (400 - 1300 MHz), obscured objects are clearly visible in the SAR imagery. Other responses in the foliage imagery are due to the dihedral-like ground-trunk reflections.

  7. Land Cover Classification for Polarimetric SAR Images Based on Mixture Models

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2014-04-01

    Full Text Available In this paper, two mixture models are proposed for modeling heterogeneous regions in single-look and multi-look polarimetric SAR images, along with their corresponding maximum likelihood classifiers for land cover classification. The classical Gaussian and Wishart models are suitable for modeling scattering vectors and covariance matrices from homogeneous regions, while their performance deteriorates for regions that are heterogeneous. By comparison, the proposed mixture models reduce the modeling error by expressing the data distribution as a weighted sum of multiple component distributions. For single-look and multi-look polarimetric SAR data, complex Gaussian and complex Wishart components are adopted, respectively. Model parameters are determined by employing the expectation-maximization (EM algorithm. Two maximum likelihood classifiers are then constructed based on the proposed mixture models. These classifiers are assessed using polarimetric SAR images from the RADARSAT-2 sensor of the Canadian Space Agency (CSA, the AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the EMISAR sensor of the Technical University of Denmark (DTU. Experiment results demonstrate that the new models fit heterogeneous regions preferably to the classical models and are especially appropriate for extremely heterogeneous regions, such as urban areas. The overall accuracy of land cover classification is also improved due to the more refined modeling.

  8. A novel polar format algorithm for SAR images utilizing post azimuth transform interpolation.

    Energy Technology Data Exchange (ETDEWEB)

    Holzrichter, Michael Warren; Martin, Grant D.; Doerry, Armin Walter

    2005-09-01

    SAR phase history data represents a polar array in the Fourier space of a scene being imaged. Polar Format processing is about reformatting the collected SAR data to a Cartesian data location array for efficient processing and image formation. In a real-time system, this reformatting or ''re-gridding'' operation is the most processing intensive, consuming the majority of the processing time; it also is a source of error in the final image. Therefore, any effort to reduce processing time while not degrading image quality is valued. What is proposed in this document is a new way of implementing real-time polar-format processing through a variation on the traditional interpolation/2-D Fast Fourier Transform (FFT) algorithm. The proposed change is based upon the frequency scaling property of the Fourier Transform, which allows a post azimuth FFT interpolation. A post azimuth processing interpolation provides overall benefits to image quality and potentially more efficient implementation of the polar format image formation process.

  9. 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

  10. 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.

  11. A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR.

    Science.gov (United States)

    Zeng, Hong-Cheng; Wang, Peng-Bo; Chen, Jie; Liu, Wei; Ge, LinLin; Yang, Wei

    2016-02-26

    Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost and real-time global coverage capability. In this paper, a general imaging formation algorithm was proposed for accurately and efficiently focusing GNSS-based bistatic SAR data, which avoids the interpolation processing in traditional back projection algorithms (BPAs). A two-dimensional point target spectrum model was firstly presented, and the bulk range cell migration correction (RCMC) was consequently derived for reducing range cell migration (RCM) and coarse focusing. As the bulk RCMC seriously changes the range history of the radar signal, a modified and much more efficient hybrid correlation operation was introduced for compensating residual phase errors. Simulation results were presented based on a general geometric topology with non-parallel trajectories and unequal velocities for both transmitter and receiver platforms, showing a satisfactory performance by the proposed method.

  12. First Experiment of IECAS P-Band Quad-Pol SAR System in Circular Imaging Mode

    Science.gov (United States)

    Hong, Wen; Li, Yang; Yin, Qiang; Lin, Yun; Chen, Erxue; Pottier, Eric

    2013-01-01

    Within the framework of the DRAGON2 project, the Institute of Electronics, Chinese Academy of Sciences (IECAS) continuously had a tight collaboration with the European and the Chinese partners. Our contribution to the joint research, separated by 4 working packages: land cover analysis, earth surface deformation monitoring and DEM extraction, forest vertical structure parameters extraction, and PolSARpro software continued development, is reviewed in the beginning. Furthermore, a joint study between IECAS - NKLMIT and University of Rennes-1 -Institute of Electronics and Telecommunications, about DEM based soil moisture inversion using POLSAR data is reviewed. Besides, a compact-pol calibration algorithm for a wide-band ground-based SAR system and a supervised land cover classification method are proposed here. Finally, the first experiment of IECAS P-band quad-pol SAR system in circular imaging mode is introduced.

  13. PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform

    Institute of Scientific and Technical Information of China (English)

    LIU Meijie; DAI Yongshou; ZHANG Jie; ZHANG Xi; MENG Junmin; XIE Qinchuan

    2015-01-01

    Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral in-formation, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be im-proved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transfor-mation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar (ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensi-ty-saturation (HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue (RGB) space, and the optical image from the China-Brazil Earth Resources Satellite (CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis (PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea

  14. Improved Early Crop Type Identification By Joint Use of High Temporal Resolution SAR And Optical Image Time Series

    Directory of Open Access Journals (Sweden)

    Jordi Inglada

    2016-04-01

    Full Text Available High temporal and spatial resolution optical image time series have been proven efficient for crop type mapping at the end of the agricultural season. However, due to cloud cover and image availability, crop identification earlier in the season is difficult. The recent availability of high temporal and spatial resolution SAR image time series, opens the possibility of improving early crop type mapping. This paper studies the impact of such SAR image time series when used in complement of optical imagery. The pertinent SAR image features, the optimal working resolution, the effect of speckle filtering and the use of temporal gap-filling of the optical image time series are assessed. SAR image time series as those provided by the Sentinel-1 satellites allow significant improvements in terms of land cover classification, both in terms of accuracy at the end of the season and for early crop identification. Haralik textures (Entropy, Inertia, the polarization ratio and the local mean together with the VV imagery were found to be the most pertinent features. Working at at 10 m resolution and using speckle filtering yield better results than other configurations. Finally it was shown that the use of SAR imagery allows to use optical data without gap-filling yielding results which are equivalent to the use of gap-filling in the case of perfect cloud screening, and better results in the case of cloud screening errors.

  15. Detection and Imaging of Slowly Moving Target of Airborne SAR Based on the GMCWD-Hough Transform

    Institute of Scientific and Technical Information of China (English)

    WANGLing; TAORar; ZHOUSiyong; WANGYue

    2004-01-01

    In this paper, the features of airborne SAR moving target echoes are analysed, the Generalizedmarginal Choi-Williams Distribution-Hough transform (GMCWD-HT) is also introduced. According to the echo model of airborne SAR, a new method based on the Generalized-marginal Choi-Williams Distribution-Hough transform for detecting and imaging the slowly moving targets of airborne SAR is proposed in the paper. This method can be used to perform the slowly moving target detection and imaging of airborne SAR in the low signal to clutter ratio, its detecting performance is better than the common method based on Wigner-Ville distribution. Computer simulation results have proven the validity of the approach.

  16. In vivo imaging of a cone mosaic in a patient with achromatopsia associated with a GNAT2 variant.

    Science.gov (United States)

    Ueno, Shinji; Nakanishi, Ayami; Kominami, Taro; Ito, Yasuki; Hayashi, Takaaki; Yoshitake, Kazutoshi; Kawamura, Yuichi; Tsunoda, Kazushige; Iwata, Takeshi; Terasaki, Hiroko

    2017-01-01

    The 2 most common causative genes for achromatopsia (ACHM) are CNGA3 and CNGB3; other genes including GNAT2 account for only a small portion of ACHM cases. The cone mosaics in eyes with CNGA3 and CNGB3 variants are severely disrupted; the cone mosaics in patients with GNAT2-associated ACHM; however, have been reported to show a contiguous pattern in adaptive optics (AO) retinal images. The purpose of this study was to analyze the cone mosaic of another case of GNAT2-associated ACHM. The patient was a 17-year-old Japanese boy. Comprehensive ocular examinations including fundus photography, electroretinography (ERGs), optical coherence tomography (OCT), and whole-exome analysis were performed. The cone mosaic was recorded with a flood-illuminated AO fundus camera, and the cone density was compared with those of 10 normal control eyes. The patient had the typical phenotype of ACHM, and a novel homozygous variant, c.730_743del, in GNAT2 was identified. The fundus did not show any specific abnormalities, and the OCT images showed the presence of the ellipsoid zone. The AO fundus image showed a clearly defined cone mosaic around the fovea. The cone density at 500 μm from the fovea was reduced by 15-30 % as compared with those of the normal eyes. This is the first description of a Japanese patient with ACHM with a novel GNAT2 variant. The eyes of this patient had a preserved cone structure with loss of function.

  17. Digital image mosaics of the nearshore coastal waters of Kawaihae on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains an image mosaic of the Kawaihae area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated...

  18. Impact of the timing of a SAR image acquisition on the calibration of a flood inundation model

    Science.gov (United States)

    Gobeyn, Sacha; Van Wesemael, Alexandra; Neal, Jeffrey; Lievens, Hans; Eerdenbrugh, Katrien Van; De Vleeschouwer, Niels; Vernieuwe, Hilde; Schumann, Guy J.-P.; Di Baldassarre, Giuliano; Baets, Bernard De; Bates, Paul D.; Verhoest, Niko E. C.

    2017-02-01

    Synthetic Aperture Radar (SAR) data have proven to be a very useful source of information for the calibration of flood inundation models. Previous studies have focused on assigning uncertainties to SAR images in order to improve flood forecast systems (e.g. Giustarini et al. (2015) and Stephens et al. (2012)). This paper investigates whether the timing of a SAR acquisition of a flood has an important impact on the calibration of a flood inundation model. As no suitable time series of SAR data exists, we generate a sequence of consistent SAR images through the use of a synthetic framework. This framework uses two available ERS-2 SAR images of the study area, one taken during the flood event of interest, the second taken during a dry reference period. The obtained synthetic observations at different points in time during the flood event are used to calibrate the flood inundation model. The results of this study indicate that the uncertainty of the roughness parameters is lower when the model is calibrated with an image taken before rather than during or after the flood peak. The results also show that the error on the modelled extent is much lower when the model is calibrated with a pre-flood peak image than when calibrated with a near-flood peak or a post-flood peak image. It is concluded that the timing of the SAR image acquisition of the flood has a clear impact on the model calibration and consequently on the precision of the predicted flood extent.

  19. Group sparsity based airborne wide angle SAR imaging

    Science.gov (United States)

    Wei, Zhonghao; Zhang, Bingchen; Bi, Hui; Lin, Yun; Wu, Yirong

    2016-10-01

    In this paper, we develop a group sparsity based wide angle synthetic aperture radar (WASAR) imaging model and propose a novel algorithm called backprojection based group complex approximate message passing (GCAMP-BP) to recover the anisotropic scene. Compare to conventional backprojection based complex approximate message passing (CAMP-BP) algorithm for the recovery of isotropic scene, the proposed method accommodates aspect dependent scattering behavior better and can produce better imagery. Simulated and experimental results are presented to demonstrate the validity of the proposed algorithm.

  20. Digital image mosaic of the nearshore coastal waters of the Napili-Honokowai area on the northwest coast of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains an image mosaic of the Napili-Honokowai area on the northwest coast of Maui. This image mosaic was generated using...

  1. QBP Imaging Algorithm for the Bistatic SAR%双基地SAR的QBP成像算法

    Institute of Scientific and Technical Information of China (English)

    徐三元; 王建国

    2011-01-01

    The standard backprojection ( BP) algorithm can flexibly deal with bistatic SAR signal data , but its computational load is heavy. It is shown that the azimuth bandwidth of the bistatic SAR is proportional to the size of the imaging patch after SAR signal is spotlighted , and the quadtree backprojeetion ( BP) algorithm can provide a large reduccion of the computational load compared to the standard backprojection algorithm. The effect on change in spotlight reference points signal bandwidth is discussed and an implementation of the quadtree backprojection algorithm is presented. Computational complexity of the algorithm is analyzed. The theoretical analysis, simulation results and the experimental data processing confirm that the algorithm is effective.%时域BP算法能够灵活处理双基地SAR信号,但是运算量很大.本文根据系统工作模型,推导出SAR信号聚束化后方位向带宽与成像区域的尺寸成正比,适合采用QBP算法进行成像;研究了聚束参考点的变化对信号带宽的影响.给出了双基地QBP算法的具体实现步骤,分析了QBP算法的运算复杂度.理论分析、仿真实验和实测数据结果验证了QBP算法的有效性.

  2. Dual-Branch Deep Convolution Neural Network for Polarimetric SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Fei Gao

    2017-04-01

    Full Text Available The deep convolution neural network (CNN, which has prominent advantages in feature learning, can learn and extract features from data automatically. Existing polarimetric synthetic aperture radar (PolSAR image classification methods based on the CNN only consider the polarization information of the image, instead of incorporating the image’s spatial information. In this paper, a novel method based on a dual-branch deep convolution neural network (Dual-CNN is proposed to realize the classification of PolSAR images. The proposed method is built on two deep CNNs: one is used to extract the polarization features from the 6-channel real matrix (6Ch which is derived from the complex coherency matrix. The other is utilized to extract the spatial features of a Pauli RGB (Red Green Blue image. These extracted features are first combined into a fully connected layer sharing the polarization and spatial property. Then, the Softmax classifier is employed to classify these features. The experiments are conducted on the Airborne Synthetic Aperture Radar (AIRSAR data of Flevoland and the results show that the classification accuracy on 14 types of land cover is up to 98.56%. Such results are promising in comparison with other state-of-the-art methods.

  3. An improved PolSAR image speckle reduction algorithm based on LMMSE and RICA

    Science.gov (United States)

    Jiang, Chang; He, Xiufeng

    2017-07-01

    Although the linear minimum mean square error (LMMSE) filter removes speckle in polarimetric synthetic aperture radar (PolSAR) images, it has the disadvantage of losing edge detail. In this paper, we propose a new filter based on robust independent component analysis (RICA) and LMMSE. This approach describes edge features in a span image by selecting the adaptive direction window and calculating the edge weight value of the spatial domain, and improves the objective function by using a step polynomial to extract the estimate of the source image with minimum noise. This technique preserves not only the edge information in the images, but also the polarimetric information. Experiments were conducted on the NASA/JPL AIRSAR L-band of the San Francisco area, and evaluated by means of the speckle reduction index and the edge preservation index. The experimental results show that the proposed method effectively reduces speckle, retains edges, and preserves the polarimetric scattering mechanisms.

  4. RPC Modeling For Spaceborne SAR And Its Application In Radar Image Geocoding

    Science.gov (United States)

    Wei, Xiaohong; He, Xueyan; Zhang, Lu; Balz, Timo; Liao, Mingsheng

    2010-10-01

    The Rational Polynomial Coefficient (RPC) model is a typical replacement sensor model which relates image coordinates and object coordinates through rational polynomial functions. This paper investigates the methodology of RPC modeling for spaceborne SAR and its application in radar image geocoding. A hybrid approach is proposed to combine the L-curve and the IMCCV (Iteration method by correcting characteristic value) methods for RPC modeling. Experimental results show that the hybrid approach is superior to traditional methods in terms of both fitting accuracy and computation time cost. The results of different settings in RPC modeling will be shown. To ensure high accuracy of image geocoding, an additional mathematical transformation is used to remove the systematic errors in the RPC model. An Envisat ASAR image is used as experimental data to verify the application.

  5. 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.

  6. SARS Basics

    Science.gov (United States)

    ... and Resources Related Links Clinician Registry Travelers' Health SARS Basics Fact Sheet Language: English Español (Spanish) Format: ... 3 pages] SARS [3 pages] SARS [3 pages] SARS? Severe acute respiratory syndrome (SARS) is a viral ...

  7. Detecting Subsidence Along a High Speed Railway by Ultrashort Baseline TCP-InSAR with High Resolution Images

    Science.gov (United States)

    Dai, K. R.; Liu, G. X.; Yu, B.; Jia, H. G.; Ma, D. Y.; Wang, X. W.

    2013-10-01

    A High Speed Railway goes across Wuqing district of Tianjin, China. Historical studies showed that the land subsidence of this area was very serious, which would give rise to huge security risk to the high speed railway. For detecting the detailed subsidence related to the high speed railway, we use the multi-temporal InSAR (MT-InSAR) technique to extract regional scale subsidence of Wuqing district. Take it into consideration that Wuqing district is a suburban region with large area of low coherence farmland, we select the temporarily coherent point InSAR (TCP-InSAR) approach for MT-InSAR analysis. The TCP-InSAR is a potential approach for detecting land subsidence in low coherence areas as it can identify and analysis coherent points between just two images and can acquire a reliable solution without conventional phase unwrapping. This paper extended the TCP-InSAR with use of ultrashort spatial baseline (USB) interferograms. As thetopographic effects are negligible in the USB interferograms, an external digital elevation model (DEM) is no longer needed in interferometric processing, and the parameters needed to be estimated were simplified at the same time. With use of 17 TerraSAR-X (TSX) images acquired from 2009 to 2010 over Wuqing district, the annual subsidence rates along the high speed railway were derived by the USB-TCPInSAR approach. Two subsidence funnels were found at ShuangJie town and around Wuqing Station with subsidence rate of -17 ∼ -27 mm/year and -7 ∼ -17 mm/year, respectively. The subsidence rates derived by USB-TCPInSAR were compared with those derived by the conventional TCP-InSAR that uses an external DEM for differential interferometry. The mean and the standard deviation of the differences between two types of results at 370697 TCPs are -4.43 × 10-6 mm/year and ±1.4673 mm/year, respectively. Further comparison with the subsidence results mentioned in several other studies were made, which shows good consistencies. The results verify

  8. Integration of SAR features into multispectral images based on the nonsubsampled contourlet and IHS transform

    Science.gov (United States)

    Yang, Zhixiang; He, Xiufeng; Xu, Jia

    2011-10-01

    As a new image multiscale geometric analysis tool, the nonsubsampled contourlet transform (NSCT) has many advantages such as multiscale, localization and multidirection, and can efficiently capture the geometric information of images. Therefore, when the NSCT is introduced to image fusion, the characteristics of original images can be taken better and more information for fusion can be obtained. In this paper, a novel fusion algorithm for fusion of the synthetic aperture radar (SAR) image and multispectral images using conjointly the intensity-hue-saturation (IHS) transform and NSCT is proposed. In the proposed method, atrous wavelet is adopted to extract the detail information in low frequency parts fusion, and a new salience measure named as local inner product is introduced to select the high frequency coefficients. A PALSAR HH image of ALOS satellite despeckled by the Lee-sigma filter and HJ-1 multispectral images are used to evaluate the performance and efficiency of the proposed method. The fused images of each method are evaluated by qualitative and quantitative comparison and analysis compared with some traditional fusion rules. The experimental results indicate that the proposed method has the merits of better preservation of image definition and less loss of spectral information.

  9. Ship Targets Discrimination Algorithm in SAR Images Based on Hu Moment Feature and Texture Feature

    Directory of Open Access Journals (Sweden)

    Liu Lei

    2016-01-01

    Full Text Available To discriminate the ship targets in SAR images, this paper proposed the method based on combination of Hu moment feature and texture feature. Firstly,7 Hu moment features should be extracted, while gray level co-occurrence matrix is then used to extract the features of mean, variance, uniformity, energy, entropy, inertia moment, correlation and differences. Finally the k-neighbour classifier was used to analysis the 15 dimensional feature vectors. The experimental results show that the method of this paper has a good effect.

  10. The Landsat Image Mosaic of Antarctica (LIMA): A Cutting-Edge Way for Students and Teachers to Learn about Antarctica

    Science.gov (United States)

    Campbell, Brian; Bindschadler, Robert

    2009-01-01

    By studying Antarctica via satellite and through ground-truthing research, we can learn where the ice is melting and why. The Landsat Image Mosaic of Antarctica (LIMA), a new and cutting-edge way for scientists, researchers, educators, students, and the public to look at Antarctica, supports this research and allows for unprecedented views of our…

  11. 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.

  12. Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems

    Directory of Open Access Journals (Sweden)

    Stewart Santos

    2011-04-01

    Full Text Available We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA-based image enhancement approach and the “model-based” descriptive experiment design (DEED regularization paradigm are unified into a new dynamic experiment design (DYED regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

  13. A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

    Science.gov (United States)

    Vickers, H.; Eckerstorfer, M.; Malnes, E.; Larsen, Y.; Hindberg, H.

    2016-11-01

    Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide.

  14. CROSS-TRACK THREE APERTURES MILLIMETER WAVE SAR SIDE-LOOKING THREE-DIMENSIONAL IMAGING

    Institute of Scientific and Technical Information of China (English)

    Teng Xiumin; Li Daojing; Li Liechen; Liu Bo; Pan Zhouhao

    2012-01-01

    The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper.Three apertures are distributed along the cross-track direction,and three virtual phase centers will be obtained through one-input and three-output.These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution.Because the cross-track array is short,the cross-track resolution is low.When the system works in side-looking mode,the cross-track resolution and height resolution will be coupling,and the low cross-track resolution will partly be transformed into the height uncertainty.The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array.In order to suppress the high cross-track sidelobes,a weighting preprocessing method is proposed.The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method.And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.

  15. Ubiquitous and continuous SAR imaging for natural hazards: present and future of remote sensing

    Science.gov (United States)

    Monti Guarnieri, Andrea; Rocca, Fabio

    2017-04-01

    Constellation of optical and SAR sensors have achieved unprecedented performances: dense constellation of cubesats - like the next constellation of 88 Dove satellites (Planet labs), launched simultaneously this February - reduce the revisit time to nearly daily. This brings great value to many domains, like the assessment of risk and damage in natural hazards, post-earthquake response, real time flood monitoring. The limits to optical imaging due to cloud coverage could then be removed with drones. Alternatively, decades of coherent exploitation of Synthetic Aperture Radars have demonstrated their unique capabilities in precise deformation monitoring, penetration in canopies and subsurfaces (glacier and deserts), 3D imaging of volumes, sensitivity to soil moisture and generation of water vapor maps. Thanks to these capabilities, for one, early warning was possible for a landslide at Bingham Canyon Mine (one of the largest in history), whereas monitoring of infrastructures, natural gas and carbon dioxide storage reservoirs, dams, mines is already an established business. Many of these applications are made possible by the Sentinel-1 SAR constellation, the first to provide systematic coherent acquisitions and free and open data. More than 50000 products are downloaded daily. Nonetheless, the present revisit times of this constellation (1-3 days), or the future 6 hours of Cosmo-SKYmed I and II constellations, will leave a gap that cannot be fruitfully exploited for early warning of landslides, real time mapping of flooding, hydrometeor forecasts, real-time regional alerts of collapse, continuous soil moisture mapping for precision farming. On the other side, the limited penetration capabilities of C-band (Sentinel-1) and X band (Cosmo, TerraSAR constellations) would not allow sufficient penetration to monitor volumes, like ice, sands and forests. In order to fill these gaps, two novel SAR systems are under study and will possibly appear in the next decades

  16. Analysis of Spectral Characteristics Based on Optical Remote Sensing and SAR Image Fusion

    Institute of Scientific and Technical Information of China (English)

    Weiguo LI; Nan JIANG; Guangxiu GE

    2014-01-01

    Because of cloudy and rainy weather in south China, optical remote sens-ing images often can't be obtained easily. With the regional trial results in Baoying, Jiangsu province, this paper explored the fusion model and effect of ENVISAT/SAR and HJ-1A satel ite multispectral remote sensing images. Based on the ARSIS strat-egy, using the wavelet transform and the Interaction between the Band Structure Model (IBSM), the research progressed the ENVISAT satel ite SAR and the HJ-1A satel ite CCD images wavelet decomposition, and low/high frequency coefficient re-construction, and obtained the fusion images through the inverse wavelet transform. In the light of low and high-frequency images have different characteristics in differ-ent areas, different fusion rules which can enhance the integration process of self-adaptive were taken, with comparisons with the PCA transformation, IHS transfor-mation and other traditional methods by subjective and the corresponding quantita-tive evaluation. Furthermore, the research extracted the bands and NDVI values around the fusion with GPS samples, analyzed and explained the fusion effect. The results showed that the spectral distortion of wavelet fusion, IHS transform, PCA transform images was 0.101 6, 0.326 1 and 1.277 2, respectively and entropy was 14.701 5, 11.899 3 and 13.229 3, respectively, the wavelet fusion is the highest. The method of wavelet maintained good spectral capability, and visual effects while improved the spatial resolution, the information interpretation effect was much better than other two methods.

  17. Comparative study of sampling strategies for sparse photon multispectral lidar imaging: towards mosaic filter arrays

    Science.gov (United States)

    Tobin, Rachael; Altmann, Yoann; Ren, Ximing; McCarthy, Aongus; Lamb, Robert A.; McLaughlin, Stephen; Buller, Gerald S.

    2017-09-01

    In this paper, we investigate the recovery of range and spectral profiles associated with remote three-dimensional scenes sensed via single-photon multispectral lidar (MSL). We consider two different spatial/spectral sampling strategies and compare their performance for a similar overall number of detected photons. For a regular spatial grid of pixels, the first strategy consists of sampling all the spatial locations of the grid for each of the L wavelengths. The second strategy is consistent with the use of mosaic filter-based arrays and consists of acquiring only one wavelength (out of L) per spatial location. Despite the reduction of spectral content observed in each location, the second strategy has clear potential advantages for fast multispectral imaging using only a single frame read out. We propose a fully automated computational method, adapted for each of the two sampling strategies in order to recover the target range profile, as well as the reflectivity profiles associated with the different wavelengths. These strategies were also assessed with high ambient background. The performance of the two sampling strategies is illustrated using a single-photon MSL system with L = 4 wavelengths (473, 532, 589 and 640 nm). The results presented demonstrate that although the first strategy usually provides more accurate results, the second strategy does not exhibit a significant performance degradation, particularly for sparse photon data (down to 1 photon per pixel on average). These results suggest a way forward for the integration of single-photon detector arrays with mosaic filters for use in a range of emerging photon-starved two-dimensional and three-dimensional imaging applications.

  18. Expanding indole diversity: direct 1-step synthesis of 1,2-fused indoles and spiroindolines from 2-halo anilines for fast SAR antiviral elucidation against tobacco mosaic virus (TMV).

    Science.gov (United States)

    Chen, Linwei; Liu, Yongxian; Song, Hongjian; Liu, Yuxiu; Wang, Lizhong; Wang, Qingmin

    2017-02-01

    To systematically investigate the influence of the variation of the original skeletons and spatial configuration of 2,3-fused indole natural products on antiviral activities, two types of structurally novel and potent pseudo-indole natural product derivatives, 1,2-fused indole and spiroindoline, with different substituents were direct synthesized from 2-halo anilines, and their antiviral activities against tobacco mosaic virus (TMV) were evaluated. The results showed that these compounds exhibited good anti-TMV activity, especially 3f, 3g, 3i, 5e, 5h, and 5l, which were more potent than the commercial anti-virus agent ribavirin. An SAR investigation demonstrates that the original ring size, arrangement, and planarity are not optimal; their anti-TMV activities can be improved by skeleton modification and spatial configuration variation. Both of the structurally novel skeletons provide a new template for antiviral studies, which may also provide some useful information for antiviral mechanism elucidation.

  19. Mosaic of the Curved Human Retinal Images Based on the Scale-Invariant Feature Transform

    Institute of Scientific and Technical Information of China (English)

    LI Ju-peng; CHEN Hou-jin; ZHANG Xin-yuan; YAO Chang

    2008-01-01

    .To meet the needs in the fundus examination, including outlook widening, pathology tracking, etc., this paper describes a robust feature-based method for fully-automatic mosaic of the curved human retinal images photographed by a fundus microscope. The kernel of this new algorithm is the scale-, rotation-and illumination-invariant interest point detector & feature descriptor-Scale-Invariant Feature Transform. When matched interest points according to second-nearest-neighbor strategy, the parameters of the model are estimated using the correct matches of the interest points,extracted by a new inlier identification scheme based on Sampson distance from putative sets. In order to preserve image features, bilinear warping and multi-band blending techniques are used to create panoramic retinal images. Experiments show that the proposed method works well with rejection error in 0.3 pixels, even for those cases where the retinal images without discernable vascular structure in contrast to the state-of-the-art algorithms.

  20. Terrain Imaging Using a SAR System Based on Reflected GPS Signals

    Institute of Scientific and Technical Information of China (English)

    Li Yong-hong; C. Rizos; E. Donskoi; J. Homer; B. Mojarrabi

    2003-01-01

    This paper describes a 3D multi-static synthetic aperture radar (SAR) imaging system which utilises reflected GPS signals from moving objects on the Earth's surface. The principle of bi-static radar is used to model the reflected GPS signals. The movement of a visible GPS satellite serves as a base for a synthetic aperture over an observation time period. As an example, a MATLAB simulation has been carried out in order to detect the movement of imaged object sunder the assumption of one static GPS receiver with two targets which move with different speeds. The influence of the visible satellite'sposition and velocity on the spatial resolution of such a SAR system isdiscussed. Simulation results show that by measuring the cross-correlation of the reflected GPS signal from the terrain and objects on it,the detection of the objects can enjoy a good spatial resolution for thecase of moving objects and a moving GPS receiver. Furthermore, thespatial resolution is also related to the selection of visible GPS satelliteswith respect to their azimuths, elevations and velocities. This systemhas the following useful features: (a) no dedicated signal transmitter is required; (b) the GPS signal frequency is reused; (c) GPS operates round-the-clock and its signals cover the entire Earth's surface; (d) low power consumption; and (e) known GPS signal structure.

  1. 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.

  2. Ship heading and velocity analysis by wake detection in SAR images

    Science.gov (United States)

    Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo

    2016-11-01

    With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.

  3. 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.

  4. 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.

  5. 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.

  6. A Downward-looking Three-dimensional Imaging Method for Airborne FMCW SAR Based on Array Antennas

    Institute of Scientific and Technical Information of China (English)

    HOU Haiping; QU Changwen; ZHOU Qiang; XIANG Yingchun

    2011-01-01

    With regard to problems in conventional synthetic aperture radar (SAR), such as imaging distortion, beam limitation and failure in acquiring three-dimensional (3-D) information, a downward-looking 3-D imaging method based on frequency modulated continuous wave (FMCW) and digital beamforming (DBF) technology for airbome SAR is presented in this study. Downward-looking 3-D SAR signal model is established first, followed by introduction of virtual antenna optimization factor and discussion of equivalent-phase-center compensation. Then, compensation method is provided according to reside video phase (RVP) and slope term for FMCW SAR. As multiple receiving antennas are applied to downward-looking 3-D imaging SAR,range cell migration correction (RCMC) tums to be more complex, and corrective measures are proposed. In addition, DBF technology is applied in realizing cross-track resolution. Finally, to validate the proposed method, magnitude of slice, peak sidelobe ratio (PSLR), integrated sidelobe ratio (ISLR) and two-dimensional (2-D) contour plot of impulse response function (IRF) of point target in three dimensions are demonstrated. Satisfactory performances are shown by simulation results.

  7. A Sparse Manifold Classification Method Based on a Multi-Dimensional Descriptive Primitive of Polarimetric SAR Image Time Series

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-03-01

    Full Text Available Classification using the rich information provided by time-series and polarimetric Synthetic Aperture Radar (SAR images has attracted much attention. The key point is to effectively reveal the correlation between different dimensions of information and form a joint feature. In this paper, a multi-dimensional SAR descriptive primitive for each single pixel is firstly constructed, which in the polarimetric scale obtains incoherent information through target decompositions while in the time scale obtains coherent information through stochastic walk. Secondly, for the purpose of feature extraction and dimension reduction, a special feature space mapping for the descriptive primitive of the whole image is proposed based on sparse manifold expression and compressed sensing. Finally, the above feature is inputted into a support vector machine (SVM classifier. This proposed method can inherently integrate the features of polarimetric SAR times series. Experiment results on three real time-series polarimetric SAR data sets show the effectiveness of our presented approach. The idea of a multi-dimensional descriptive primitive as a convenient tool also opens a new spectrum of potential for further processing of polarimetric SAR image time series.

  8. A Combined Use of Decomposition and Texture for Terrain Classification of Fully Polarimetric SAR Images

    Science.gov (United States)

    Rodionova, N. V.

    2007-03-01

    This p aper presents two-stag e unsupervised terrain classification of fully polarimetr ic SA R data using Freeman and Durden decomposition based on three simp le scattering mechanisms: surface, volume and double bounce (first step), and textur al features (uncorrelated uniformity , contr ast, inv erse mo men t and entropy) obtained from grey lev el co-occurrence matr ices (GLCM) (second step). Textural f eatures ar e defined in moving w indow 5x5 pixels w ith N=32 (N - number of grey lev els) . This algorith m preserves th e purity of domin ant polarimetric scattering properties and defines textural features in each scatter ing category. It is shown better object discrimin ation after app lying textur e w ith in fix ed scattering category. Speckle r eduction is one of th e main mo ments in imag e interpr etation improvement because of its great influen ce on textur e. Results from unfiltered and Lee filtered polar imetr ic SAR imag es show that the v alues of contrast and en tropy decr ease and th e values of uniformity and inverse moment increase with speckle reduction, that's tru e for all polarizations (HH, VV, HV). Th e d iscr imination b etw een objects increases after speckle f ilter ing. Polar ization influen ce on textur e features is def ined by calculating th e features in SAR images w ith HH , VV and HV polarizations before and after speck le filter ing, and then creating RG B images. It is shown mor e polarization inf luence on textur e features (uniformity , inverse mo ment and entropy) before filtering and less influen ce - after speck le f iltering. I t's not true for contrast wher e polar ization influen ce is not ch anged practically w ith filtering. SIR-C/X-SA R SLC L-band imag es of Moscow r egion are used for illustr ation.

  9. Low-energy electron holographic imaging of individual tobacco mosaic virions

    Energy Technology Data Exchange (ETDEWEB)

    Longchamp, Jean-Nicolas, E-mail: longchamp@physik.uzh.ch; Latychevskaia, Tatiana; Escher, Conrad; Fink, Hans-Werner [Physics Department, University of Zurich, Winterthurerstrasse 190, 8057 Zurich (Switzerland)

    2015-09-28

    Modern structural biology relies on Nuclear Magnetic Resonance (NMR), X-ray crystallography, and cryo-electron microscopy for gaining information on biomolecules at nanometer, sub-nanometer, or atomic resolution. All these methods, however, require averaging over a vast ensemble of entities, and hence knowledge on the conformational landscape of an individual particle is lost. Unfortunately, there are now strong indications that even X-ray free electron lasers will not be able to image individual molecules but will require nanocrystal samples. Here, we show that non-destructive structural biology of single particles has now become possible by means of low-energy electron holography. As an example, individual tobacco mosaic virions deposited on ultraclean freestanding graphene are imaged at 1 nm resolution revealing structural details arising from the helical arrangement of the outer protein shell of the virus. Since low-energy electron holography is a lens-less technique and since electrons with a deBroglie wavelength of approximately 1 Å do not impose radiation damage to biomolecules, the method has the potential for Angstrom resolution imaging of single biomolecules.

  10. Bridge recognition of median-resolution SAR images using pun histogram entropy

    Institute of Scientific and Technical Information of China (English)

    Wenyu Wu; Dong Yin; Rong Zhang; Yan Liu; Jia Pan

    2009-01-01

    A novel algorithm for bridge recognition of median synthetic aperture radar (SAR) images using histogram entropy presented by Pun is proposed. Firstly, Lee filter and histogram proportion are used to denoise the original image and to make the target evident. Then, water regions are gained through histogram segmentation and the contours of water regions are extracted. After these, the potential bridge targets are obtained based on the space relativity between bridges and water regions using improved contour search. At last, bridges are recognized by extracting the feature of Pun histogram entropy (PHE) of these potential bridge targets. Experimental results show the good qualities of the algorithm, such as fast speed, high rate of recognition, and low rate of false target.

  11. 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.

  12. Bayesian-based Wavelet Shrinkage for SAR Image Despeckling Using Cycle Spinning

    Institute of Scientific and Technical Information of China (English)

    ZHANG De-xiang; GAO Qing-wei; CHEN Jun-ning

    2006-01-01

    A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown. Then, a Bayesian wavelet shrinkage factor is applied to the decomposed data to estimate noise-free wavelet coefficients. The method is based on the Mixture Gaussian Distributed (MGD) modeling of sub-band coefficients. Finally, multi-resolution wavelet coefficients are reconstructed by wavelet-threshold using cycle spinning. Experimental results show that the proposed despeckling algorithm is possible to achieve an excellent balance between suppresses speckle effectively and preserves as many image details and sharpness as possible. The new method indicated its higher performance than the other speckle noise reduction techniques and minimizing the effect of pseudo-Gibbs phenomena.

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

    DEFF Research Database (Denmark)

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

    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...... holds a strong potential for change detection studies in remote sensing. In polarimetric synthetic aperture radar we measure the amplitude and phase of backscattered signals in four combinations of the linear horizontal and vertical receive and transmit polarizations. These signals form a complex...... 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....

  14. Use of Digitally Stained Multimodal Confocal Mosaic Images to Screen for Nonmelanoma Skin Cancer.

    Science.gov (United States)

    Mu, Euphemia W; Lewin, Jesse M; Stevenson, Mary L; Meehan, Shane A; Carucci, John A; Gareau, Daniel S

    2016-12-01

    Confocal microscopy has the potential to provide rapid bedside pathologic analysis, but clinical adoption has been limited in part by the need for physician retraining to interpret grayscale images. Digitally stained confocal mosaics (DSCMs) mimic the colors of routine histologic specimens and may increase adaptability of this technology. To evaluate the accuracy and precision of 3 physicians using DSCMs before and after training to detect basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) in Mohs micrographic surgery fresh-tissue specimens. This retrospective study used 133 DSCMs from 64 Mohs tissue excisions, which included clear margins, residual BCC, or residual SCC. Discarded tissue from Mohs surgical excisions from the dermatologic surgery units at Memorial Sloan Kettering Cancer Center and Oregon Health & Science University were collected for confocal imaging from 2006 to 2011. Final data analysis and interpretation took place between 2014 and 2016. Two Mohs surgeons and a Mohs fellow, who were blinded to the correlating gold standard frozen section diagnoses, independently reviewed the DSCMs for residual nonmelanoma skin cancer (NMSC) before and after a brief training session (about 5 minutes). The 2 assessments were separated by a 6-month washout period. Diagnostic accuracy was characterized by sensitivity and specificity of detecting NMSC using DSCMs vs standard frozen histopathologic specimens. The diagnostic precision was calculated based on interobserver agreement and κ scores. Paired 2-sample t tests were used for comparative means analyses before and after training. The average respective sensitivities and specificities of detecting NMSC were 90% (95% CI, 89%-91%) and 79% (95% CI, 52%-100%) before training and 99% (95% CI, 99%-99%) (P = .001) and 93% (95% CI, 90%-96%) (P = .18) after training; for BCC, they were 83% (95% CI, 59%-100%) and 92% (95% CI, 81%-100%) before training and 98% (95% CI, 98%-98%) (P = .18) and 97% (95% CI

  15. 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

  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. Digital image mosaic of the nearshore coastal waters from Waikiki to Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot...

  18. Shaded-relief image mosaic of the nearshore coastal waters from Waikiki to Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot...

  19. 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.

  20. Synthetic aperture radar imaging algorithm customized for programmable optronic processor in the application of full-scene synthetic aperture radar image formation

    Science.gov (United States)

    Sheng, Hui; Gao, Yesheng; Zhu, Bingqi; Wang, Kaizhi; Liu, Xingzhao

    2015-01-01

    With the high programmability of a spatial light modulator (SLM), a newly developed synthetic aperture radar (SAR) optronic processor is capable of focusing SAR data with different parameters. The embedded SLM, encoding SAR data into light signal in the processor, has a limited loading resolution of 1920×1080. When the dimension of processed SAR data increases to tens of thousands in either range or azimuth direction, SAR data should be input and focused block by block. And then, part of the imaging results is mosaicked to offer a full-scene SAR image. In squint mode, however, Doppler centroid will shift signal spectrum in the azimuth direction and make phase filters, loaded by another SLM, unable to cover the entire signal spectrum. It brings about a poor imaging result. Meanwhile, the imaging result, shifted away from the center of light output, will cause difficulties in subsequent image mosaic. We present an SAR image formation algorithm designed to solve these problems when processing SAR data of a large volume in low-squint case. It could not only obtain high-quality imaging results, but also optimize the subsequent process of image mosaic with optimal system cost and efficiency. Experimental results validate the performance of this proposed algorithm in optical full-scene SAR imaging.

  1. Restoration and enhancement of textural properties in SAR images using second-order statistics

    Science.gov (United States)

    Nezry, Edmond; Kohl, Hans-Guenther; De Groof, Hugo

    1994-12-01

    Local second order properties, describing spatial relations between pixels are introduced into the single-point speckle adaptive filtering processes, in order to account for the effects of speckle spatial correlation and to enhance scene textural properties in the restored image. To this end, texture measures originating, first from local grey level co-occurrence matrices (GLCM), and second from the local autocorrelation functions (ACF) are used. Results obtained on 3-look processed ERS-1 FDC and PRI spaceborne images illustrate the performance allowed by the introduction of these texture measures in the structure retaining speckle adaptive filters. The observable texture in remote sensing images is related to the physical spatial resolution of the sensor. For this reason, other spatial speckle decorrelation methods, more simple and easier to implement, for example post-filtering and linear image resampling, are also presented in this paper. In the particular case of spaceborne SAR imagery, all these methods lead to visually similar results. They produce filtered (radar reflectivity) images visually comparable to optical images.

  2. Multichannel and Wide-Angle SAR Imaging Based on Compressed Sensing

    Science.gov (United States)

    Sun, Chao; Wang, Baoping; Fang, Yang; Song, Zuxun; Wang, Shuzhen

    2017-01-01

    The multichannel or wide-angle imaging performance of synthetic aperture radar (SAR) can be improved by applying the compressed sensing (CS) theory to each channel or sub-aperture image formation independently. However, this not only neglects the complementary information between signals of each channel or sub-aperture, but also may lead to failure in guaranteeing the consistency of the position of a scatterer in different channel or sub-aperture images which will make the extraction of some scattering information become difficult. By exploiting the joint sparsity of the signal ensemble, this paper proposes a novel CS-based method for joint sparse recovery of all channel or sub-aperture images. Solving the joint sparse recovery problem with a modified orthogonal matching pursuit algorithm, the recovery precision of scatterers is effectively improved and the scattering information is also preserved during the image formation process. Finally, the simulation and real data is used for verifying the effectiveness of the proposed method. Compared with single channel or sub-aperture independent CS processing, the proposed method can not only obtain better imaging performance with fewer measurements, but also preserve more valuable scattering information for target recognition. PMID:28165433

  3. Bayesian Fusion of Multi-Scale Detectors for Road Extraction from SAR Images

    Directory of Open Access Journals (Sweden)

    Rui Xu

    2017-01-01

    Full Text Available This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR imagery for improving the accuracy of road extraction. The state-of-the-art approaches, such as fraction extraction and road network optimization, failed to obtain continuous road segments in separate successions, since the optimization could not change the parts ignored by the fraction extraction. In this paper, the proposed algorithm integrates the fraction extraction and optimization procedure simultaneously to extract the road network: (1 the Bayesian framework is utilized to transfer the road network extraction to joint reasoning of the likelihood of fraction extraction and the priority of network optimization; (2 the multi-scale linear feature detector (MLFD and the network optimization beamlet are introduced; (3 the conditional random field (CRF is used to reason jointly. The result is the global optimum since the fraction extraction and network optimization are exploited at the same time. The proposed algorithm solves the problem that the fractions are bound to reduce in the process of network optimization and has demonstrated effectiveness in real SAR images applications.

  4. Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm

    Science.gov (United States)

    Zhang, Siqian; Kuang, Gangyao

    2014-10-01

    In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.

  5. 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.

  6. Retrieval of Both Soil Moisture and Texture Using one configuration TerraSAR-X radar Images

    Science.gov (United States)

    Zribi, M., Sr.; Gorrab, A.; Baghdadi, N.; Lili-Chabaane, Z.

    2015-12-01

    The aim of this study is to propose a methodology combing multi-temporal X-band SAR images (TerraSAR-X) with continuous ground thetaprobe measurements, for the retrieval of surface soil moisture and texture at a high spatial resolution. Our analysis is based on seven radar images acquired at a 36° incidence angle in the HH polarization, over a semi-arid site in Tunisia (North Africa). All ground measurements of surface soil parameters were carried out over several bare soil reference fields located at the Kairouan site. Between November 2013 and January 2014 (three months), ground campaigns were carried out at the same time as the seven satellite acquisitions. The soil moisture estimations are based on an empirical change detection approach using TerraSAR-X data and ground auxiliary thetaprobe network measurements. Two assumptions were tested: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. For the two considered approaches, the soil moisture estimations were validated using ground measurements acquired over fifteen test fields, under different moisture conditions. These comparisons lead to a volumetric moisture RMSE equal to 3.8% and 3.3%, and a bias equal to 0.5% and 0.3%, respectively. By considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved. For clay and sand, we retrieve an rms error equal to 10.8% (equivalent to 108 g/kg) and 18.6% (equivalent to 186 g/kg), respectively. Maps of soil moisture, clay

  7. An Improved Phase Correlation Method for Obtaining Dynamic Feature of the Ocean from Sequential SAR Sub-aperture Images (in English

    Directory of Open Access Journals (Sweden)

    Wang Xiao-qing

    2013-03-01

    Full Text Available Dynamic features are important aspects of the ocean. However the dynamic information is lost in most conventional Synthetic Aperture Radar (SAR image processing methods, because they treat the image as an instantaneous state of the observed area. In fact, we can obtain dynamic features of the ocean from sequential sub-aperture images, because we know that the different parts of the azimuthal aperture correspond to different imaging instances. A key step for retrieving the dynamic features from sequential images is image-matching. However, the heavy noise characteristic of sub-aperture SAR images renders the traditional image-matching methods ineffective. In this paper we propose an image matching method based on improved phase correlation to deal with the heavy noise problem of SAR sub-aperture images. Experimental results show that the improved image-matching method presents an accuracy of 0.15 pixel and noise robustness. The analysis indicates that the improved algorithm is competent for obtaining dynamic information from the medium resolution airborne SAR images or high resolution spaceborne SAR images with 0.15-0.3 m/s estimation precision under most SNR conditions. The improved algorithm was used on an airborne SAR data to retrieve the movement velocity. The retrieved velocity ranged from 0.05-0.5 m/s, which seems to be reasonable value for the ocean current velocity.

  8. Texture analysis and classification of ERS SAR images for map updating of urban areas in The Netherlands

    NARCIS (Netherlands)

    Dekker, R.J.

    2003-01-01

    In single-band and single-polarized synthetic aperture radar (SAR) image classification, texture holds useful information. In a study to assess the map-updating capabilities of such sensors in urban areas, some modern texture measures were investigated. Among them were histogram measures, wavelet

  9. Image exploitation for MISAR

    Science.gov (United States)

    Heinze, N.; Edrich, M.; Saur, G.; Krüger, W.

    2007-04-01

    The miniature SAR-system MiSAR has been developed by EADS Germany for lightweight UAVs like the LUNASystem. MiSAR adds to these tactical UAV-systems the all-weather reconnaissance capability, which is missing until now. Unlike other SAR sensors, that produce large strip maps at update rates of several seconds, MiSAR generates sequences of SAR images with approximately 1 Hz frame rate. photo interpreters (PI) of tactical drones, now mainly experienced with visual interpretation, are not used to SARimages, especially not with SAR-image sequence characteristics. So they should be supported to improve their ability to carry out their task with a new, demanding sensor system. We have therefore analyzed and discussed with military PIs in which task MiSAR can be used and how the PIs can be supported by special algorithms. We developed image processing- and exploitation-algorithms for such SAR-image sequences. A main component is the generation of image sequence mosaics to get more oversight. This mosaicing has the advantage that also non straight /linear flight-paths and varying squint angles can be processed. Another component is a screening-component for manmade objects to mark regions of interest in the image sequences. We use a classification based approach, which can be easily adapted to new sensors and scenes. These algorithms are integrated into an image exploitation system to improve the image interpreters ability to get a better oversight, better orientation and helping them to detect relevant objects, especially considering long endurance reconnaissance missions.

  10. HIERARCHICAL CLASSIFICATION OF POLARIMETRIC SAR IMAGE BASED ON STATISTICAL REGION MERGING

    Directory of Open Access Journals (Sweden)

    F. Lang

    2012-07-01

    Full Text Available Segmentation and classification of polarimetric SAR (PolSAR imagery are very important for interpretation of PolSAR data. This paper presents a new object-oriented classification method which is based on Statistical Region Merging (SRM segmentation algorithm and a two-level hierarchical clustering technique. The proposed method takes full advantage of the polarimetric information contained in the PolSAR data, and takes both effectiveness and efficiency into account according to the characteristic of PolSAR. A modification of over-merging to over-segmentation technique and a post processing of segmentation for SRM is proposed according to the application of classification. And a revised symmetric Wishart distance is derived from the Wishart PDF. Segmentation and classification results of AirSAR L-band PolSAR data over the Flevoland test site is shown to demonstrate the validity of the proposed method.

  11. NOAA TIFF Image- 0.5 meter Backscatter Mosaic of Mid Shelf Reef (St. Thomas), US Virgin Islands, Project NF-05-05, 2005, UTM 20 NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 0.5 meter resolution backscatter mosaic of the Mid Shelf Reef south of St. Thomas, US Virgin IslandsNOAA's NOS/NCCOS/CCMA Biogeography Team,...

  12. NOAA TIFF Image- 0.5 meter Backscatter Mosaic of Grammanik Bank - East (St. Thomas), US Virgin Islands, Project NF-05-05, 2005, UTM 20 NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 0.5 meter resolution backscatter mosaic of Grammanik Bank, south of St. Thomas, US Virgin Islands.NOAA's NOS/NCCOS/CCMA Biogeography Team, in...

  13. NOAA TIFF Image - 1 m Backscatter Mosaic of Bajo de Cico, Puerto Rico, Project NF-07-06, 2007, UTM 19 NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 1 meter resolution backscatter mosaic of Bajo de Cico off the coast of western Puerto Rico, collected using a Kongsberg EM 1002 (95 kHz)...

  14. NOAA TIFF Image - 2 m Backscatter Mosaic of Isla de Mona, Puerto Rico, Project NF-07-06, 2007, UTM 19 NAD83 (NCEI Accession 0131853)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 2 meter resolution backscatter mosaic of the southern coast of Isla de Mona, collected using a Kongsberg EM 1002 (95 kHz) multibeam...

  15. Digital image mosaics of the nearshore coastal waters of selected areas on the island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and...

  16. NOAA TIFF Image - 1 m Backscatter Mosaic of Bajo de Cico, Puerto Rico, Project NF-07-06, 2007, UTM 19 NAD83 (NCEI Accession 0131853)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 1 meter resolution backscatter mosaic of Bajo de Cico off the coast of western Puerto Rico, collected using a Kongsberg EM 1002 (95 kHz)...

  17. NOAA TIFF Image - 1 m Backscatter Mosaic of Abrir La Sierra Bank, PR (2007) collected using a SeaBat Reson 8124 (200 kHz) multibeam echosounder

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 1 meter resolution backscatter mosaic of the Abrir La Sierra Bank off the coast of western Puerto Rico, collected using a SeaBat Reson 8124...

  18. NOAA TIFF Image - 2 m Backscatter Mosaic of Isla de Mona, PR, Project NF-07-06, 2007, UTM 19 NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 2 meter resolution backscatter mosaic of the southern coast of Isla de Mona, collected using a Kongsberg EM 1002 (95 kHz) multibeam...

  19. NOS TIFF Image, 3M Backscatter Mosaic La Parguera, Puerto Rico, 2006 : Project NF-06-03, UTM 19 NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 3 meter resolution backscatter mosaic of the south west shore (La Parguera) of Puerto Rico. NOAA's NOS/NCCOS/CCMA Biogeography Team, in...

  20. NOAA TIFF Image - 3 m Backscatter Mosaic of the south west shore (La Parguera) of Puerto Rico, Project NF-06-03, 2006, UTM 19 WGS84

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 3 meter resolution backscatter mosaic of the south west shore (La Parguera) of Puerto Rico. NOAA's NOS/NCCOS/CCMA Biogeography Team, in...

  1. NOAA TIFF Image - 1 m Backscatter Mosaic of Abrir La Sierra Bank, PR (2007) collected using a Kongsberg EM 1002 (95 kHz) multibeam echosounder

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 1 meter resolution backscatter mosaic of the Abrir La Sierra Bank off the coast of western Puerto Rico, collected using a Kongsberg EM 1002...

  2. NOAA TIFF Image - 1 m Backscatter Mosaic of the St. John Shelf, U.S. Virgin Islands, Project NF-10-03, 2010, UTM 20 WGS84

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a 1 meter resolution backscatter mosaic of the St. John Shelf, US Virgin Islands. NOAA's NOS/NCCOS/CCMA Biogeography Team, in collaboration...

  3. Detection of UXO contaminated land fields using hidden Markov models in the SAR images generated by airborne radar system

    Science.gov (United States)

    Damarla, Thyagaraju; Nguyen, Lam H.; Ranney, Kenneth I.

    2001-08-01

    We present an algorithm based on hidden Markov models (HMM) to detect several types of unexploded ordinance (UXO). We use the synthetic aperture radar (SAR) images simulated for 155 mm artillery shell, 2.75 in rocket and 105 mm mortar to generate the codebook. The algorithm is used on the data collected at Yuma Proving ground (YPG). YPG is seeded with several types of UXOs for testing purposes. The data is collected using an ultra wideband SAR mounted on a telescoping boom to simulate the airborne radar. The algorithm has detected all the targets for which it is trained for and it also detected other UXOs that are similar in shape.

  4. OPTIMIZING THE DISTRIBUTION OF TIE POINTS FOR THE BUNDLE ADJUSTMENT OF HRSC IMAGE MOSAICS

    Directory of Open Access Journals (Sweden)

    J. Bostelmann

    2017-07-01

    Full Text Available For a systematic mapping of the Martian surface, the Mars Express orbiter is equipped with a multi-line scanner: Since the beginning of 2004 the High Resolution Stereo Camera (HRSC regularly acquires long image strips. By now more than 4,000 strips covering nearly the whole planet are available. Due to the nine channels, each with different viewing direction, and partly with different optical filters, each strip provides 3D and color information and allows the generation of digital terrain models (DTMs and orthophotos. To map larger regions, neighboring HRSC strips can be combined to build DTM and orthophoto mosaics. The global mapping scheme Mars Chart 30 is used to define the extent of these mosaics. In order to avoid unreasonably large data volumes, each MC-30 tile is divided into two parts, combining about 90 strips each. To ensure a seamless fit of these strips, several radiometric and geometric corrections are applied in the photogrammetric process. A simultaneous bundle adjustment of all strips as a block is carried out to estimate their precise exterior orientation. Because size, position, resolution and image quality of the strips in these blocks are heterogeneous, also the quality and distribution of the tie points vary. In absence of ground control points, heights of a global terrain model are used as reference information, and for this task a regular distribution of these tie points is preferable. Besides, their total number should be limited because of computational reasons. In this paper, we present an algorithm, which optimizes the distribution of tie points under these constraints. A large number of tie points used as input is reduced without affecting the geometric stability of the block by preserving connections between strips. This stability is achieved by using a regular grid in object space and discarding, for each grid cell, points which are redundant for the block adjustment. The set of tie points, filtered by the

  5. Optimizing the Distribution of Tie Points for the Bundle Adjustment of HRSC Image Mosaics

    Science.gov (United States)

    Bostelmann, J.; Breitkopf, U.; Heipke, C.

    2017-07-01

    For a systematic mapping of the Martian surface, the Mars Express orbiter is equipped with a multi-line scanner: Since the beginning of 2004 the High Resolution Stereo Camera (HRSC) regularly acquires long image strips. By now more than 4,000 strips covering nearly the whole planet are available. Due to the nine channels, each with different viewing direction, and partly with different optical filters, each strip provides 3D and color information and allows the generation of digital terrain models (DTMs) and orthophotos. To map larger regions, neighboring HRSC strips can be combined to build DTM and orthophoto mosaics. The global mapping scheme Mars Chart 30 is used to define the extent of these mosaics. In order to avoid unreasonably large data volumes, each MC-30 tile is divided into two parts, combining about 90 strips each. To ensure a seamless fit of these strips, several radiometric and geometric corrections are applied in the photogrammetric process. A simultaneous bundle adjustment of all strips as a block is carried out to estimate their precise exterior orientation. Because size, position, resolution and image quality of the strips in these blocks are heterogeneous, also the quality and distribution of the tie points vary. In absence of ground control points, heights of a global terrain model are used as reference information, and for this task a regular distribution of these tie points is preferable. Besides, their total number should be limited because of computational reasons. In this paper, we present an algorithm, which optimizes the distribution of tie points under these constraints. A large number of tie points used as input is reduced without affecting the geometric stability of the block by preserving connections between strips. This stability is achieved by using a regular grid in object space and discarding, for each grid cell, points which are redundant for the block adjustment. The set of tie points, filtered by the algorithm, shows a more

  6. Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching

    Science.gov (United States)

    Hu, Jun; Li, Zhi-Wei; Ding, Xiao-Li; Zhu, Jian-Jun

    2008-01-01

    The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS) direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D) co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction), with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground). Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more advantageous than the DInSAR

  7. Novel Polarimetric SAR Interferometry Algorithms Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Polarimetric SAR interferometry (PolInSAR) is a recently developed synthetic aperture radar (SAR) imaging mode that combines the capabilities of radar polarimetry...

  8. Origins and features of oil slicks in the Bohai Sea detected from satellite SAR images.

    Science.gov (United States)

    Ding, Yi; Cao, Conghua; Huang, Juan; Song, Yan; Liu, Guiyan; Wu, Lingjuan; Wan, Zhenwen

    2016-05-15

    Oil slicks were detected using satellite Synthetic Aperture Radar (SAR) images in 2011. We investigated potential origins and regional and seasonal features of oil slick in the Bohai Sea. Distance between oil slicks and potential origins (ships, seaports, and oil exploitation platforms) and the angle at which oil slicks move relative to potential driving forces were evaluated. Most oil slicks were detected along main ship routes rather than around seaports and oil exploitation platforms. Few oil slicks were detected within 20km of seaports. Directions of oil slicks movement were much more strongly correlated with directions of ship routes than with directions of winds and currents. These findings support the premise that oil slicks in the Bohai Sea most likely originate from illegal disposal of oil-polluted wastes from ships. Seasonal variation of oil slicks followed an annual cycle, with a peak in August and a trough in December.

  9. Optimizing Kernel PCA Using Sparse Representation-Based Classifier for MSTAR SAR Image Target Recognition

    Directory of Open Access Journals (Sweden)

    Chuang Lin

    2013-01-01

    Full Text Available Different kernels cause various class discriminations owing to their different geometrical structures of the data in the feature space. In this paper, a method of kernel optimization by maximizing a measure of class separability in the empirical feature space with sparse representation-based classifier (SRC is proposed to solve the problem of automatically choosing kernel functions and their parameters in kernel learning. The proposed method first adopts a so-called data-dependent kernel to generate an efficient kernel optimization algorithm. Then, a constrained optimization function using general gradient descent method is created to find combination coefficients varied with the input data. After that, optimized kernel PCA (KOPCA is obtained via combination coefficients to extract features. Finally, the sparse representation-based classifier is used to perform pattern classification task. Experimental results on MSTAR SAR images show the effectiveness of the proposed method.

  10. 并行机载双站斜视SAR ELBF-CS成像算法%ELBF-CS imaging algorithm for parallel airborne bistatic squint SAR

    Institute of Scientific and Technical Information of China (English)

    冉金和; 张剑云; 武拥军; 李小波

    2013-01-01

    论文建立了并行机载斜视双站SAR的结构模型和信号模型,用收发载机多普勒贡献比为加权系数推导了点目标回波的扩展Loffeld频谱公式(ELBF).在二维频域内补偿双站扭曲项,然后对剩余相位项做Taylor展开,利用Chirp Scaling (CS)方法,推导了并行机载双站斜视SAR的ELBF-CS成像算法.双站结构参数及双站扭曲项的距离向空变性用回波数据的距离向分块处理,推导了数据分块条件,由此可以实现宽场景成像.算法基于更精确的ELBF,并用CS方法校正点目标距离徙动,处理流程更简单,成像效率更高,仿真验证了本文算法处理并行机载双站斜视SAR数据的有效性.%Based on the geometrical model and signal model of parallel airborne bistatic squint SAR(Bi-SAR),extended Loffeld bistatic formula (ELBF) of point target echo is derived by using the weighting factors that is defined bythe Doppler contribution ratios of the transmitter and receiver.Bistatic deformation is compensated in the two-dimensional (2-D) frequency domain,residual phase items in spectrum expressions are expanded using Taylor series expansion,and the ELBF-CS imaging algorithm of parallel airborne bistatic squint SAR is deduced combining with the CS theory.The variance of bistatic parameters and bistatic deformation in range can be compensated by data blocking in range,so the algorithm can be easily expanded to wide scene focusing.With more accurate 2-D frequency spectrum formula and good range cell migration correction (RCMC) method,the processing procedure of algorithm is simplified and imaging efficiency is also improved.Simulations validate the proposed algorithm to process the parallel airborne bistatic squint SAR data.

  11. SAR River Image Segmentation Based on Reciprocal Gray Entropy and Improved Chan-Vese Model

    Directory of Open Access Journals (Sweden)

    WU Shihua

    2015-11-01

    Full Text Available To further improve the accuracy and speed of river segmentation on synthetic aperture radar(SAR images, a segmentation method is proposed, which is based on improved Chan-Vese(CV model combining with reciprocal gray entropy multi-threshold selection optimized by artificial bee colony algorithm. Considering the uniformity of the gray level within river object cluster and background cluster, a coarse river image segmentation is made by using the multi-threshold selection algorithm based on reciprocal gray entropy and artificial bee colony optimization; Contrapose the low convergence speed and the sensitivity to initial conditions of basic CV model, the Dirac function is replaced with the image edge intensity and the coarse segmentation results serve as the initial condition of improved CV model which is utilized to make a fine segmentation for the river image. A large number of experimental results show that, the proposed segmentation method needs not set initial conditions and has high running speed as well as segmentation accuracy.

  12. 一种极化SAR图像模糊分类方法%Fuzzy classification of polarimetric SAR images

    Institute of Scientific and Technical Information of China (English)

    张涛; 孙建涛; 杨汝良

    2011-01-01

    针对极化合成孔径雷达图像模糊非监督分类问题,给出了一种改进的极化合成孔径雷达图像模糊分类方法.该方法通过引入极化总功率参数span,改进极化合成孔径雷达图像模糊H/a分类方法,进行极化合成孔径雷达数据模糊H/a/Span非监督分类.利用机载极化合成孔径雷达数据进行实验.实验结果表明,改进的方法提高了分类性能,聚类中心更为合理.%For the problem of unsupervised classification of polarimetric SAR images based on fuzzy theory,an improved fuzzy classification method of polarimetric SAR images is presented. The fuzzy H/α classification method is improved by introducing the total polarimetric power parameter span. The polarimetric SAR image is classified by the fuzzy H/α/span method. A classified experiment for airborne polarimetric SAR data is carried out by this method. Experimental results indicate that this method can improve the performance of classification and the cluster centers are more reasonable.

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

    Institute of Scientific and Technical Information of China (English)

    朱小满; 王钧; 李军; 景宁

    2011-01-01

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

  14. 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.

  15. Filtering of Interferometric SAR Phase Images as a Fuzzy Matching-Pursuit Blind Estimation

    Directory of Open Access Journals (Sweden)

    Bianchini Massimo

    2005-01-01

    Full Text Available We present an original application of fuzzy logic to restoration of phase images from interferometric synthetic aperture radar (InSAR, which are affected by zero-mean uncorrelated noise, whose variance depends on the underlying coherence, thereby yielding a nonstationary random noise process. Spatial filtering of the phase noise is recommended, either before phase unwrapping is accomplished, or simultaneously with it. In fact, phase unwrapping basically relies on a smoothness constraint of the phase field, which is severely hampered by the noise. Space-varying linear MMSE estimation is stated as a problem of matching pursuit, in which the estimator is obtained as an expansion in series of a finite number of prototype estimators, fitting the spatial features of the different statistical classes encountered, for example, fringes and steep slope areas. Such estimators are calculated in a fuzzy fashion through an automatic training procedure. The space-varying coefficients of the expansion are stated as degrees of fuzzy membership of a pixel to each of the estimators. Neither a priori knowledge on the noise variance is required nor particular signal and noise models are assumed. Filtering performances on simulated phase images show a steady SNR improvement over conventional box filtering. Applications of the proposed filter to interferometric phase images demonstrate a superior ability of restoring fringes yet preserving their discontinuities, together with an effective noise smoothing performance, irrespective of locally varying coherence characteristics.

  16. An improved Otsu method for oil spill detection from SAR images

    Directory of Open Access Journals (Sweden)

    Fangjie Yu

    2017-07-01

    Full Text Available In recent years, oil spill accidents have become increasingly frequent due to the development of marine transportation and massive oil exploitation. At present, satellite remote sensing is the principal method used to monitor oil spills. Extracting the locations and extent of oil spill spots accurately in remote sensing images reaps significant benefits in terms of risk assessment and clean-up work. Nowadays the method of edge detection combined with threshold segmentation (EDCTS to extract oil information is becoming increasingly popular. However, the current method has some limitations in terms of accurately extracting oil spills in synthetic aperture radar (SAR images, where heterogeneous background noise exists. In this study, we propose an adaptive mechanism based on Otsu method, which applies region growing combined with both edge detection and threshold segmentation (RGEDOM to extract oil spills. Remote sensing images from the Bohai Sea on June 11, 2011 and the Gulf of Dalian on July 17, 2010 are utilized to validate the accuracy of our algorithm and the reliability of extraction results. In addition, results according to EDCTS are used as a comparator to further explore validity. The comparison with results according to EDCTS using the same dataset demonstrates that the proposed self-adapting algorithm is more robust and boasts high-accuracy. The accuracy computing by the adaptive algorithm is significantly improved compared with EDCTS and threshold method.

  17. Northeast Puerto Rico and Culebra Island World View 2 Satellite Mosaic - NOAA TIFF Image

    Data.gov (United States)

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

  18. A method to calibrate channel friction and bathymetry parameters of a Sub-Grid hydraulic model using SAR flood images

    Science.gov (United States)

    Wood, M.; Neal, J. C.; Hostache, R.; Corato, G.; Chini, M.; Giustarini, L.; Matgen, P.; Wagener, T.; Bates, P. D.

    2015-12-01

    Synthetic Aperture Radar (SAR) satellites are capable of all-weather day and night observations that can discriminate between land and smooth open water surfaces over large scales. Because of this there has been much interest in the use of SAR satellite data to improve our understanding of water processes, in particular for fluvial flood inundation mechanisms. Past studies prove that integrating SAR derived data with hydraulic models can improve simulations of flooding. However while much of this work focusses on improving model channel roughness values or inflows in ungauged catchments, improvement of model bathymetry is often overlooked. The provision of good bathymetric data is critical to the performance of hydraulic models but there are only a small number of ways to obtain bathymetry information where no direct measurements exist. Spatially distributed river depths are also rarely available. We present a methodology for calibration of model average channel depth and roughness parameters concurrently using SAR images of flood extent and a Sub-Grid model utilising hydraulic geometry concepts. The methodology uses real data from the European Space Agency's archive of ENVISAT[1] Wide Swath Mode images of the River Severn between Worcester and Tewkesbury during flood peaks between 2007 and 2010. Historic ENVISAT WSM images are currently free and easy to access from archive but the methodology can be applied with any available SAR data. The approach makes use of the SAR image processing algorithm of Giustarini[2] et al. (2013) to generate binary flood maps. A unique feature of the calibration methodology is to also use parameter 'identifiability' to locate the parameters with higher accuracy from a pre-assigned range (adopting the DYNIA method proposed by Wagener[3] et al., 2003). [1] https://gpod.eo.esa.int/services/ [2] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote

  19. 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

  20. 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.

  1. Free-breathing variable flip angle balanced SSFP cardiac cine imaging with reduced SAR at 3T.

    Science.gov (United States)

    Srinivasan, Subashini; Kroeker, Randall M; Gabriel, Simon; Plotnik, Adam; Godinez, Sergio R; Hu, Peng; Halnon, Nancy; Finn, J Paul; Ennis, Daniel B

    2016-10-01

    To develop a free-breathing variable flip angle (VFA) balanced steady-state free precession (bSSFP) cardiac cine imaging technique with reduced specific absorption rate (SAR) at 3 Tesla. Free-breathing VFA (FB-VFA) images in the short-axis and four-chamber views were acquired using an optimal VFA scheme, then compared with conventional breath-hold constant flip angle (BH-CFA) acquisitions. Two cardiac MRI experts used a 5-point scale to score images from healthy subjects (N = 10). The left ventricular ejection fraction, end diastolic volume (LVEDV), end systolic volume, stroke volume (LVSV), and end diastolic myocardial mass (LVEDM) were determined by manual contour analysis for BH-CFA and FB-VFA. A pilot evaluation of FB-VFA was performed in one patient with Duchenne muscular dystrophy. FB-VFA SAR was 25% lower than BH-CFA with similar blood-myocardium contrast. The qualitative FB-VFA score was lower than the BH-CFA for the short-axis (3.1 ± 0.5 versus 4.3 ± 0.8; P cine imaging decreased the SAR at 3T with image quality sufficient to perform cardiac functional analysis. Magn Reson Med 76:1210-1216, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  2. Integrated SAR Technologies for Monitoring the Stability of Mine Sites: Application Using Terrasar-X and RADARSAT-2 Images

    Science.gov (United States)

    Rheault, M.; Bouroubi, Y.; Sarago, V.; Nguyen-Xuan, P. T.; Bugnet, P.; Gosselin, C.; Benoit, M.

    2015-04-01

    The last three decades have seen significant mining development in the northern regions of Canada, where the freeze and thaw cycle of permafrost and corresponding surface subsidence and heave represent a significant challenge at all mining stages, from the design of infrastructures to the monitoring of restored areas. Over the past ten years, SAR interferometry has been widely used to monitor ground surface deformation. With this technique, changes in phase between two SAR acquisitions are used to detect centimetre to millimetre surface displacements over a large area with high spatial resolution. This paper presents the results of a project that aims to develop a SAR solution to provide useful information for environmental monitoring and assessing the stability of mining sites. RADARSAT-2 and TerraSAR-X images acquired during the summer of 2014 were used to measure the displacements of ground surface, infrastructures and stockpiles caused by seasonal changes in permafrost extent. The study area is an open-pit mine located in Nunavut, northern Canada, in the continuous permafrost zone. Results shown that surface displacements calculated from RADARSAT-2 and TerraSAR-X are very similar and in agreement with scientific and terrain knowledge. Significant displacements were observed in loose soil areas while none was detected in bedrock and rock outcrop areas. The areas most affected by active layer changes showed surface subsidence during the thaw settlement period. Thus, InSAR can be used as a tool to guide the siting and design of new infrastructure as well as highlighting risks in areas of unstable terrain.

  3. The research of auto-focusing method for the image mosaic and fusion system with multi-sensor

    Science.gov (United States)

    Pang, Ke; Yao, Suying; Shi, Zaifeng; Xu, Jiangtao; Liu, Jiangming

    2013-09-01

    In modern image processing, due to the development of digital image processing, the focus of the sensor can be automatically set by the digital processing system through computation. In the other hand, the auto-focusing synchronously and consistently is one of the most important factors for image mosaic and fusion processing, especially for the system with multi-sensor which are put on one line in order to gain the wide angle video information. Different images sampled by the sensors with different focal length values will always increase the complexity of the affine matrix of the image mosaic and fusion in next, which potentially reducing the efficiency of the system and consuming more power. Here, a new fast evaluation method based on the gray value variance of the image pixel is proposed to find the common focal length value for all sensors to achieve the better image sharpness. For the multi-frame pictures that are sampled from different sensors that have been adjusted and been regarded as time synchronization, the gray value variances of the adjacent pixels are determined to generate one curve. This curve is the focus measure function which describes the relationship between the image sharpness and the focal length value of the sensor. On the basis of all focus measure functions of all sensors in the image processing system, this paper uses least square method to carry out the data fitting to imitate the disperse curves and give one objective function for the multi-sensor system, and then find the optimal solution corresponding to the extreme value of the image sharpness according to the evaluation of the objective function. This optimal focal length value is the common parameter for all sensors in this system. By setting the common focal length value, in the premise of ensuring the image sharpness, the computing of the affine matrix which is the core processing of the image mosaic and fusion which stitching all those pictures into one wide angle image will be

  4. Forward-looking three dimensional imaging technique for InSAR mounted on ground vehicles%车载 InSAR 前视三维成像技术

    Institute of Scientific and Technical Information of China (English)

    王建; 李杨寰; 张汉华; 陆必应; 宋千; 周智敏

    2014-01-01

    It is a difficult task for an unmanned ground vehicle (UGV)to sense obstacles in out fields or unstructured environments.Because the height information is a vital feature to boost the performance of obstacle discrimination,the three-dimensional imaging technique for sensing obstacles ahead UGV of interferometric synthetic aperture radar (InSAR)was presented.The basic signal process flow of InSAR was reviewed. Special factors of the UGV platform that impact the digital elevation model (DEM)measurement precision were analyzed,such as the baseline length,platform motion errors.The DEMof a partial sight-blocked obstacle scene was obtained by processing the three-dimensional InSAR image, which proved the feasibility of applying InSAR to obstacle sensing of UGV.%野外和非结构化环境下的障碍探测是无人驾驶车(UGV)环境感知的难题之一。基于高度识别障碍是一种有效的解决途径,提出了干涉合成孔径雷达(InSAR)的三维障碍物成像策略,研究了 InSAR 信息处理流程,分析了干涉基线和运动误差对车载 InSAR 高程测量精度的影响,仿真了无人车前场景存在遮挡时的 InSAR 高程测量,证明了 InSAR 用于 UGV 前方环境感知的可行性。

  5. 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.

  6. The ZpiM algorithm: a method for interferometric image reconstruction in SAR/SAS.

    Science.gov (United States)

    Dias, José M B; Leitao, José M N

    2002-01-01

    This paper presents an effective algorithm for absolute phase (not simply modulo-2-pi) estimation from incomplete, noisy and modulo-2pi observations in interferometric aperture radar and sonar (InSAR/InSAS). The adopted framework is also representative of other applications such as optical interferometry, magnetic resonance imaging and diffraction tomography. The Bayesian viewpoint is adopted; the observation density is 2-pi-periodic and accounts for the interferometric pair decorrelation and system noise; the a priori probability of the absolute phase is modeled by a compound Gauss-Markov random field (CGMRF) tailored to piecewise smooth absolute phase images. We propose an iterative scheme for the computation of the maximum a posteriori probability (MAP) absolute phase estimate. Each iteration embodies a discrete optimization step (Z-step), implemented by network programming techniques and an iterative conditional modes (ICM) step (pi-step). Accordingly, the algorithm is termed ZpiM, where the letter M stands for maximization. An important contribution of the paper is the simultaneous implementation of phase unwrapping (inference of the 2pi-multiples) and smoothing (denoising of the observations). This improves considerably the accuracy of the absolute phase estimates compared to methods in which the data is low-pass filtered prior to unwrapping. A set of experimental results, comparing the proposed algorithm with alternative methods, illustrates the effectiveness of our approach.

  7. A Novel Imaging Algorithm for Airborne Bistatic Squint SAR with Unparallel Trajectories

    Institute of Scientific and Technical Information of China (English)

    WU Yongjun; HUANG Ye

    2012-01-01

    A novel analytical imaging algorithm is proposed for the strip-map mode of airborne bistatic squint SAR with unparallel trajectories.The algorithm derives the two-dimensional (2D) spectrum formula of the point target echo by using the contribution ratios of Doppler frequency modulation ratios of the transmitter and receiver as the weighting coefficients.Through decoupling the target position against the tracks of the transmitter and receiver,the range parameter and the azimuth one in the spectrum formula are separated.In 2D frequency domain,2D Chirp-Z transform (2D-CZT) is applied to correcting the migrations of the echo along the range and azimuth after the bistatic deformation term has been compensated,so the target image is precisely focused.The advantage of the algorithm is easy to be expanded to the virtual wide swath by blocking the radar data along the range and azimuth to limit the 2D residual migrations.Simulation results confirm the validity of the 2D-CZT algorithm.

  8. An Associate Rules Mining Algorithm Based on Artificial Immune Network for SAR Image Segmentation

    Directory of Open Access Journals (Sweden)

    Mengling Zhao

    2015-01-01

    Full Text Available As a computational intelligence method, artificial immune network (AIN algorithm has been widely applied to pattern recognition and data classification. In the existing artificial immune network algorithms, the calculating affinity for classifying is based on calculating a certain distance, which may lead to some unsatisfactory results in dealing with data with nominal attributes. To overcome the shortcoming, the association rules are introduced into AIN algorithm, and we propose a new classification algorithm an associate rules mining algorithm based on artificial immune network (ARM-AIN. The new method uses the association rules to represent immune cells and mine the best association rules rather than searching optimal clustering centers. The proposed algorithm has been extensively compared with artificial immune network classification (AINC algorithm, artificial immune network classification algorithm based on self-adaptive PSO (SPSO-AINC, and PSO-AINC over several large-scale data sets, target recognition of remote sensing image, and segmentation of three different SAR images. The result of experiment indicates the superiority of ARM-AIN in classification accuracy and running time.

  9. Coastal Monitoring Using L-band Synthetic Aperture Radar (SAR) Image Data - Some Case Studies in Asian Delta Areas

    Science.gov (United States)

    Tanaka, A.

    2014-12-01

    Coastal geomorphology is highly variable as it is affected by sea-level changes and other naturally- and human-induced fluctuations. To effectively assess and monitor geomorphological changes in various time scales is thus critical for coastal management. Asian mega deltas are vulnerable to a sea-level rise due to its low-lying delta plain, and are dynamic region given a large amount of sediment supply. However, limited data availability and accessibility in the deltas have prevented establishment of systematic coastal monitoring. A variety of remote sensing systems can be used to monitor geomorphological changes in coastal areas as it has wide spatial coverage and high temporal repeatability. Especially, analysis using SAR (Synthetic Aperture Radar) data not affected by the cloud conditions offer potential for monitoring in the monsoon Asia region. We will present some case studies of Asian coastal regions using L-band SAR data, ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band SAR) and JERS-1 (Japanese Earth Resource Satellite-1) SAR data. One example is that time-series of radar amplitude images can be used to delineate changes quantitatively of the areal extent of river-mouth bars in distributaries of the Mekong River delta. It shows that the estimated areas of river mouthbars gradually increase on an annual time scale, and seasonal variations of areas were also recognized. Another example is that differential SAR interferometry is applied to the coast of the Yellow River delta in China. It shows very high subsidence rates, likely due to groundwater pumping. A further example is that we apply a SAR interferometry time series analysis to monitor ground deformations in the lower Chao Phraya delta plain, Thailand. A single reference time series interferogram from the stacking of unwrapped phases were applied. The subsidence and uplift pattern observed using the SAR interferometry time series analysis highlights the spatial complexity

  10. Stereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions

    Science.gov (United States)

    Soergel, Uwe; Michaelsen, Eckart; Thiele, Antje; Cadario, Erich; Thoennessen, Ulrich

    SAR stereo image analysis for 3D information extraction is mostly carried out based on imagery taken under same-side or opposite-side viewing conditions. For urban scenes in practice stereo is up to now usually restricted to the first configuration, because increasing image dissimilarity connected with rising illumination direction differences leads to a lack of suitable features for matching, especially in the case of low or medium resolution data. However, due to two developments SAR stereo from arbitrary viewing conditions becomes an interesting option for urban information extraction. The first one is the availability of airborne sensor systems, which are capable of more flexible data acquisition in comparison to satellite sensors. This flexibility enables multi-aspect analysis of objects in built-up areas for various kinds of purpose, such as building recognition, road network extraction, or traffic monitoring. The second development is the significant improvement of the geometric resolution providing a high level of detail especially of roof features, which can be observed from a wide span of viewpoints. In this paper, high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their height from the different layover effects in views taken from orthogonal aspect angles. High level object matching is proposed that relies on symbolic data, representing suitable features of urban objects. Here, a knowledge-based approach is applied, which is realized by a production system that codes a set of suitable principles of perceptual grouping in its production rules. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows of point targets, rectangular structures or symmetries. The stereo analysis is then accomplished by means of productions that combine and match these 2D image objects and infer their height by 3D clustering. The approach

  11. Exploitation of amplitude and phase of satellite SAR images for landslide mapping: the case of Montescaglioso (South Italy)

    Science.gov (United States)

    Raspini, Federico; Ciampalini, Andrea; Lombardi, Luca; Nocentini, Massimiliano; Gigli, Giovanni; Casagli, Nicola; Del Conte, Sara; Ferretti, Alessandro

    2016-04-01

    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). The event, triggered by prolonged rainfalls, created significant damage to buildings and local infrastructures. 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. This work demonstrates that this complementary approach, based on the synergistic exploitation of phase and amplitude SAR data, can become a powerful tool for landslide investigation, allowing the detection of slow, precursory deformation patterns as well the retrieval of full 3D surface displacement fields caused by large

  12. Labeled co-occurrence matrix for the detection of built-up areas in high-resolution SAR images

    Science.gov (United States)

    Li, Na; Bruzzone, Lorenzo; Chen, Zengping; Liu, Fang

    2013-10-01

    The characterization of urban environments in synthetic aperture radar (SAR) images is becoming increasingly challenging with the increased spatial ground resolutions. In SAR images having a geometrical resolution of few meters (e.g. 3 m), urban scenes are roughly speaking characterized by three main types of backscattering: low intensity, medium intensity, and high intensity, which correspond to different land-cover types. Based on the observations of the behavior of the backscattering, in this paper we propose the labeled co-occurrence matrix (LCM) technique to detect and extract built-up areas. Two textural features, autocorrelation and entropy, are derived from LCM. The image classification is based on a similarity classifier defined in the general Lukasiewicz structure. Experiments have been carried out on TerraSAR-X images acquired on Nanjing (China) and Barcelona (Spain), respectively. The obtained classification accuracies point out the effectiveness of the proposed technique in identifying and detecting built-up areas compared with the traditional grey level co-occurrence matrix (GLCM) texture features.

  13. Anatomy of a SAR impulse response.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2007-08-01

    A principal measure of Synthetic Aperture Radar (SAR) image quality is the manifestation in the SAR image of a spatial impulse, that is, the SAR's Impulse Response (IPR). IPR requirements direct certain design decisions in a SAR. Anomalies in the IPR can point to specific anomalous behavior in the radar's hardware and/or software.

  14. Parameterized first-guess spectrum method for retrieving directional spectrum of swell-dominated waves and huge waves from SAR images

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method (PFSM), was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of the retrieving model generally used. In this method, with additional information and satellite parameters, the separating wave-number is first calculated to determine the maximum wave-number beyond which the linear relation can be used. The separating wave-number can be calculated using the additional information on wind velocity and parameters of SAR satellite. And then the SAR spectrum can be divided into SAR spectrum of wind wave and of swell according to the result of separating wave-number. The portion of SAR spectrum generated by wind wave, is used to search for the most suitable parameters of ocean wind wave spectrum, including propagation direction of ocean wave, phase speed of dominating wave and the angle spreading coefficient. The swell spectrum is acquired by directly inversing the linear relation of ocean wave spectrum to SAR spectrum given the portion of SAR spectrum generated by swell. We used the proposed method to retrieve the ocean wave spectrum from ERS-SAR data from the South China Sea and compared the result with altimeter data. The agreement indicates that the PFSM is reliable.

  15. Image enhancements of Landsat 8 (OLI) and SAR data for preliminary landslide identification and mapping applied to the central region of Kenya

    Science.gov (United States)

    Mwaniki, M. W.; Kuria, D. N.; Boitt, M. K.; Ngigi, T. G.

    2017-04-01

    Image enhancements lead to improved performance and increased accuracy of feature extraction, recognition, identification, classification and hence change detection. This increases the utility of remote sensing to suit environmental applications and aid disaster monitoring of geohazards involving large areas. The main aim of this study was to compare the effect of image enhancement applied to synthetic aperture radar (SAR) data and Landsat 8 imagery in landslide identification and mapping. The methodology involved pre-processing Landsat 8 imagery, image co-registration, despeckling of the SAR data, after which Landsat 8 imagery was enhanced by Principal and Independent Component Analysis (PCA and ICA), a spectral index involving bands 7 and 4, and using a False Colour Composite (FCC) with the components bearing the most geologic information. The SAR data were processed using textural and edge filters, and computation of SAR incoherence. The enhanced spatial, textural and edge information from the SAR data was incorporated to the spectral information from Landsat 8 imagery during the knowledge based classification. The methodology was tested in the central highlands of Kenya, characterized by rugged terrain and frequent rainfall induced landslides. The results showed that the SAR data complemented Landsat 8 data which had enriched spectral information afforded by the FCC with enhanced geologic information. The SAR classification depicted landslides along the ridges and lineaments, important information lacking in the Landsat 8 image classification. The success of landslide identification and classification was attributed to the enhanced geologic features by spectral, textural and roughness properties.

  16. Geo-correction Algorithm Based on Equivalent RD Model for ScanSAR of HJ-1-C Satellite

    Directory of Open Access Journals (Sweden)

    Liu Jia-yin

    2014-06-01

    Full Text Available HJ-1-C satellite is the first Synthetic Aperture Radar (SAR satellite for civilian use in China, and it has a strip and scan mode. According to the characteristics of the ScanSAR of the HJ-1-C satellite, a geo-correction algorithm based on an equivalent RD model has been outlined in this paper on the basis of an ECS image processing algorithm and a traditional Range-Doppler location method. An azimuth mosaic was presented by a time series relationship, then the different burst was stitched by range, and the equivalent parameters were fitted to locations on the RD model. Finally, the ScanSAR image was geo-corrected. The HJ-1-C satellite data results showed that the location accuracy of ScanSAR for the HJ-1-C satellite was less than 100 m, and the geo-correction algorithm was realized in 10 s in fewer than 24 parallel cores.

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

    Science.gov (United States)

    Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong

    2015-12-26

    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.

  18. Sub-urban landscape characterization by very high-resolution X-band COSMO-Skymed SAR images: first results

    Science.gov (United States)

    Del Frate, Fabio; Loschiavo, Domenico; Pratola, Chiara; Schiavon, Giovanni; Solimini, Domenico

    2010-10-01

    The very-high spatial resolution provided by COSMO-Skymed products, also considering the concurrent TerraSAR-X mission, opens new challenges in the field of SAR image processing for remote sensing applications, maybe comparable to those represented by the first optical commercial satellites at the beginning of last decade. The Tor Vergata-Frascati test site, where extensive ground-truth data are available, was imaged by the COSMO constellation at two different days in summer 2010. This enabled first investigations on the potential of this type of imagery in providing a characterization of sub-urban areas by exploitation of both amplitude and phase information contained in the radar return. In particular this paper deals with the set-up of preliminary chains of automatic processing based on Multi-Layer Perceptron neural networks for pixel based analysis. Also some comments concerning the retrieval of information on the vertical properties of a single building are reported.

  19. SAR Image Segmentation Based on SRADPRO and SCM Model%融合SRADPRO和SCM模型的SAR图像分割

    Institute of Scientific and Technical Information of China (English)

    寇光杰; 马云艳; 岳峻

    2016-01-01

    An improved speckle reducing anisotropic diffusion ( SRADPRO) algorithm was adopted to re-duce the speckle in synthetic aperture radar ( SAR) image. An adaptive SAR image segmentation algo-rithm speckle reducing spiking cortical model ( SRSCM) was proposed when SRADPRO and spiking cor-tical model ( SCM) was combined. In SRSCM, the standard deviation was calculated through a uniform sample region in the SAR image, and then the effect degree of speckle can be estimated as a result whether to employ the operator of SRADPRO was determined. At the second stage, the SCM operator was executed. Because of the auto wave characteristic of SCM, the segmented image and edge detection result can be obtained together. The effectiveness of SRSCM was proved by the comparisons with several tradi-tional algorithms.%将改进后各向异性扩散相干斑抑制算法(SRADPRO)用于合成孔径雷达(SAR)图像相干斑抑制,并和脉冲发放皮层模型(SCM)结合,提出一种自适应SAR图像分割算法.该算法首先计算SAR图像均匀采样区的标准差,并以此评价SAR图像中相干斑的影响程度,进而自适应地决定是否采用SRADPRO进行降斑处理,然后再利用SCM进行图像分割.由于SCM的自动波扩散机理,使得该算法在获得分割后的SAR目标的同时,也得到了目标边缘检测结果.与多种常规算法的比较结果证明了SAR图像分割算法的有效性.

  20. Discovery and SARs of trans-3-aryl acrylic acids and their analogs as novel anti-tobacco mosaic virus (TMV) agents.

    Science.gov (United States)

    Wu, Meng; Wang, Ziwen; Meng, Chuisong; Wang, Kailiang; Hu, Yanna; Wang, Lizhong; Wang, Qingmin

    2013-01-01

    A series of trans-3-aryl acrylic acids 1-27 and their derivatives 28-34 were prepared and evaluated for their antiviral activity against tobacco mosaic virus (TMV) for the first time. The bioassay results showed that most of these compounds exhibited good antiviral activity against TMV, of which compounds 1, 5, 6, 20, 27 and 34 exhibited significantly higher activity against TMV than commercial Ribavirin both in vitro and in vivo. Furthermore, these compounds have more simple structure than commercial Ribavirin, and can be synthesized more efficiently. These new findings demonstrate that trans-3-aryl acrylic acids and their derivatives represent a new template for antiviral studies and could be considered for novel therapy against plant virus infection.

  1. Discovery and SARs of trans-3-aryl acrylic acids and their analogs as novel anti-tobacco mosaic virus (TMV agents.

    Directory of Open Access Journals (Sweden)

    Meng Wu

    Full Text Available A series of trans-3-aryl acrylic acids 1-27 and their derivatives 28-34 were prepared and evaluated for their antiviral activity against tobacco mosaic virus (TMV for the first time. The bioassay results showed that most of these compounds exhibited good antiviral activity against TMV, of which compounds 1, 5, 6, 20, 27 and 34 exhibited significantly higher activity against TMV than commercial Ribavirin both in vitro and in vivo. Furthermore, these compounds have more simple structure than commercial Ribavirin, and can be synthesized more efficiently. These new findings demonstrate that trans-3-aryl acrylic acids and their derivatives represent a new template for antiviral studies and could be considered for novel therapy against plant virus infection.

  2. Image mosaic based on the camera self-calibration of combining two vanishing points and pure rotational motion

    Science.gov (United States)

    Duan, Shaoli; Zang, Huaping; Zhang, Xiaofang; Gong, Qiaoxia; Tian, Yongzhi; Wang, Junqiao; Liang, Erjun; Liu, Xiaomin; Zhao, Shujun

    2016-10-01

    Camera calibration is one of the indispensable processes to obtain 3D depth information from 2D images in the field of computer vision. Camera self-calibration is more convenient and flexible, especially in the application of large depth of fields, wide fields of view, and scene conversion, as well as other occasions like zooms. In this paper, two selfcalibration methods respectively based on two vanishing points and homography are studied, and finally realizing the image mosaic based on self-calibration of the camera purely rotating around optical center. The geometric characteristic of disappear points formed by two groups of orthogonal parallel lines is applied to self-calibration based on two vanishing points. By using the vectors' orthogonal properties of connection optical centers and the vanishing points, the constraint equations on the camera intrinsic parameters are established. By this method, four internal parameters of the camera can be solved though only four images taked from different viewpoints in a scene. Compared with the other selfcalibration based on homography, the method based on two vanishing points has more convenient calibration process and simple algorithm. To check the quality of the self-calibration, we create a spherical mosaic of the images that were used for the self-calibration based on homography. Compared with the experimental results of two methods respectively based on calibration plate and self-calibration method using machine vision software Halcon, the practicability and effectiveness of self-calibration respectively based on two vanishing points and homography is verified.

  3. 浅析复制拼接图像检验技术%Analysis of Copy Mosaic Image Inspection Technology

    Institute of Scientific and Technical Information of China (English)

    韦强宝

    2016-01-01

    基于图像拍摄设备和数字图像自动化编辑软件的普及型,在使用Photoshop对照片进行复制拼接后,使得图像表达出的客观信息不完全真实,给社会带来严重信任危机。如何分析判断图像的真实性是当今信息化发展的难题,因此具有重大的研究意义。本文对数字图像复制拼接进行实验并检验其真实性。%Based on image device and digital image editing software for affordable automation,after using Photoshop to copy Mosaic pictures,makes the image expresses the objective information is not completely true,and to the society brings serious crisis of confidence. How to analyse and judge the authenticity of the image is difficult problem of the development of information technology today,so it is of great research significance. In this paper,the digital copy Mosaic experiment and testing its authenticity.

  4. A Fast Superpixel Segmentation Algorithm for PolSAR Images Based on Edge Refinement and Revised Wishart Distance

    Directory of Open Access Journals (Sweden)

    Yue Zhang

    2016-10-01

    Full Text Available The superpixel segmentation algorithm, as a preprocessing technique, should show good performance in fast segmentation speed, accurate boundary adherence and homogeneous regularity. A fast superpixel segmentation algorithm by iterative edge refinement (IER works well on optical images. However, it may generate poor superpixels for Polarimetric synthetic aperture radar (PolSAR images due to the influence of strong speckle noise and many small-sized or slim regions. To solve these problems, we utilized a fast revised Wishart distance instead of Euclidean distance in the local relabeling of unstable pixels, and initialized unstable pixels as all the pixels substituted for the initial grid edge pixels in the initialization step. Then, postprocessing with the dissimilarity measure is employed to remove the generated small isolated regions as well as to preserve strong point targets. Finally, the superiority of the proposed algorithm is validated with extensive experiments on four simulated and two real-world PolSAR images from Experimental Synthetic Aperture Radar (ESAR and Airborne Synthetic Aperture Radar (AirSAR data sets, which demonstrate that the proposed method shows better performance with respect to several commonly used evaluation measures, even with about nine times higher computational efficiency, as well as fine boundary adherence and strong point targets preservation, compared with three state-of-the-art methods.

  5. Building damage assessment using a single post-earthquake PolSAR image: a case of the 2010 Yushu earthquake

    Science.gov (United States)

    Zhai, Wei; Zeng, Wenhao

    2017-02-01

    Earthquakes are one of the most destructive natural disasters. Efficiently and quickly acquiring building earthquake damage information can help to reduce the casualties after an earthquake. In this paper, building damage information is extracted using a single post-earthquake PolSAR image. In PolSAR images, since the undamaged oriented buildings characterized by volume scattering with weaker scattering power are very similar to collapsed buildings, the collapsed buildings are difficult to extract accurately. In this paper, the difference in the relative contribution change rate of scattering components before and after polarization orientation angle (POA) compensation is proposed to enhance the difference between collapsed buildings and oriented buildings, in order that the collapsed buildings can be extracted more accurately. The “4.14” Yushu earthquake, which occurred in Yushu County, Qinghai province of China, is used as the case study to test the proposed method, and an airborne high-resolution PolSAR image of the urban region of Yushu County is used in the experiment. The experimental results show that the accuracy of building damage information extraction can be improved by the use of the proposed method, compared with the traditional polarimetric classification.

  6. 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

  7. Monitoring river morphological changes using high resolution multitemporal sar images: a case study on orco river, italy

    Science.gov (United States)

    Mitidieri, Francesco; Nicolina Papa, Maria; Ruello, Giuseppe; Amitrano, Donato; Bizzi, Simone; Demarchi, Luca

    2016-04-01

    Improving the knowledge about river processes by applying innovative monitoring techniques is extremely needed to face the challenge of a better river management. In this paper we test the capability of satellite synthetic aperture radar (SAR) images to enrich the monitoring of river geomorphological processes. Multitemporal SAR images provide observations and measurements at high spatial (3 m), and in particular temporal resolution (15 days). This information if properly processed and classified may significantly enrich our ability to monitor the evolution of river morphological phenomena (erosion/deposition, narrowing/widening, riparian vegetation's evolution and interferences with river flow). This is expected to lead to an enhancements in the river management capabilities, in particular as regards the assessment of hydro-morphological river quality, as strongly suggested by European Commission's Water Framework Directive (2000/60/EC). A case study on the Italian River Orco is here presented. The case study has used a set of 100 COSMO-SkyMed stripmap images (from October 2008 to November 2014) from Italian Space Agency. All the data were acquired with medium look angle (almost 30°) and HH polarization, also for increasing the land-water contrast. Calibration, registration and despeckling procedures were applied on the acquired dataset. In particular, the optimal weighting multitemporal De Grandi filter was adopted in order to allow an effective extraction of the water surfaces contour. This method was applied to extract water contours over the entire historical series of SAR datasets available. Thanks to the generated information we were able to monitor the lateral dynamic of the water channels and infer on the evolutions of erosion/deposition phenomena. To this aim, an RGB representation of multitemporal SAR data was implemented. The series of detected river channel morphological changes was then analyzed in the light of the series of discharge measurements in

  8. Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

    Science.gov (United States)

    Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe

    2016-11-01

    For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

  9. Mosaic Horses

    Science.gov (United States)

    Rudecki, Maryanna

    2009-01-01

    This article describes a lesson inspired by Sicilian mosaics. The author first presented a PowerPoint presentation of mosaics from the Villa Romana del Casale and reviewed complementary and analogous colors. Students then created mosaics using a variety of art materials. They presented their work to their peers and discussed the thought and…

  10. 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)...

  11. Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image...

  12. Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image...

  13. Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image...

  14. Digital image mosaic of the nearshore coastal waters of Kawela on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image...

  15. Digital image mosaics of the nearshore coastal waters of Kalaeloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kalaeloa area on the south coast of Moloka'i. This image...

  16. Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image...

  17. Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image...

  18. Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image...

  19. Land Surface Water Mapping Using Multi-Scale Level Sets and a Visual Saliency Model from SAR Images

    Directory of Open Access Journals (Sweden)

    Chuan Xu

    2016-05-01

    Full Text Available Land surface water mapping is one of the most basic classification tasks to distinguish water bodies from dry land surfaces. In this paper, a water mapping method was proposed based on multi-scale level sets and a visual saliency model (MLSVS, to overcome the lack of an operational solution for automatically, rapidly and reliably extracting water from large-area and fine spatial resolution Synthetic Aperture Radar (SAR images. This paper has two main contributions, as follows: (1 The method integrated the advantages of both level sets and the visual saliency model. First, the visual saliency map was applied to detect the suspected water regions (SWR, and then the level set method only needed to be applied to the SWR regions to accurately extract the water bodies, thereby yielding a simultaneous reduction in time cost and increase in accuracy; (2 In order to make the classical Itti model more suitable for extracting water in SAR imagery, an improved texture weighted with the Itti model (TW-Itti is employed to detect those suspected water regions, which take into account texture features generated by the Gray Level Co-occurrence Matrix (GLCM algorithm, Furthermore, a novel calculation method for center-surround differences was merged into this model. The proposed method was tested on both Radarsat-2 and TerraSAR-X images, and experiments demonstrated the effectiveness of the proposed method, the overall accuracy of water mapping is 98.48% and the Kappa coefficient is 0.856.

  20. 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.

  1. 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.

  2. Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching

    Directory of Open Access Journals (Sweden)

    Jian-Jun Zhu

    2008-10-01

    Full Text Available The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction, with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground. Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more

  3. 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.

  4. Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey (USGS) periodically collects airborne image data for the Colorado River corridor within Arizona (fig. 1) to allow scientists to study the impacts of Glen Canyon Dam water release on the corridor’s natural and cultural resources. These data are collected from just above Glen Canyon Dam (in Lake Powell) down to the entrance of Lake Mead, for a total distance of 450 kilometers (km) and within a 500-meter (m) swath centered on the river’s mainstem and its seven main tributaries (fig. 1). The most recent airborne data collection in 2009 acquired image data in four wavelength bands (blue, green, red, and near infrared) at a spatial resolution of 20 centimeters (cm). The image collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits. Davis (2012) reported on the performance of the SH52 sensor and on the processing steps required to produce the nearly flawless four-band image mosaic (sectioned into map tiles) for the river corridor. The final image mosaic has a total of only 3 km of surface defects in addition to some areas of cloud shadow because of persistent inclement weather during data collection. The 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River. Some analyses of these image mosaics do not require the full 12-bit dynamic range or all four bands of the calibrated image database, in which atmospheric scattering (or haze) had not been removed from the four bands. To provide scientists and the general public with image products that are more useful for visual interpretation, the 12-bit image data were converted to 8-bit natural-color and color-infrared images, which also removed atmospheric scattering within each wavelength-band image. The conversion required an evaluation of the

  5. Science Results from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR): Progress Report

    Science.gov (United States)

    Evans, Diane L. (Editor); Plaut, Jeffrey (Editor)

    1996-01-01

    The Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) is the most advanced imaging radar system to fly in Earth orbit. Carried in the cargo bay of the Space Shuttle Endeavour in April and October of 1994, SIR-C/X-SAR simultaneously recorded SAR data at three wavelengths (L-, C-, and X-bands; 23.5, 5.8, and 3.1 cm, respectively). The SIR-C/X-SAR Science Team consists of 53 investigator teams from more than a dozen countries. Science investigations were undertaken in the fields of ecology, hydrology, ecology, and oceanography. This report contains 44 investigator team reports and several additional reports from coinvestigators and other researchers.

  6. 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.

  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.

    Gaussian smoothed SAR image spectra have been evaluated from 512 x 512 pixel sub- scenes 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...

  8. 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...

  9. 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

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

    Science.gov (United States)

    Davis, Philip A.

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Li Jing-shan

    2014-06-01

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

  12. ONERA airborne SAR facilities

    Energy Technology Data Exchange (ETDEWEB)

    Boutry, J.M. [Office National d`Etudes et de Recherches Aerospatiales (ONERA), Chatillon (France)

    1996-11-01

    ONERA has developed and operates the RAMSES experimental SAR on board a TRANSALL C160 aircraft. This system has been designed in order to analyze the effect of various parameters, such as frequency, polarization, incidence, resolution,... in the field of air-to-ground radar applications. These applications include SAR imaging for ground radar applications. These applications include SAR imaging for various purposes such as map-matching for navigation update, battlefield surveillance, reconnaissance, treaty applications... It consists of several radar sections operating over a wide range of frequency bands (L, S, C, X, Ku, Ka, W). 7 figs., 3 tabs.

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

    Science.gov (United States)

    Liu, Wei; Wei, Tingcun; Li, Bo; Yang, Lifeng; Xue, Feifei; Hu, Yongcai

    2016-05-01

    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 μm2. 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.

  14. 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.

  15. Structural biology at the single particle level: imaging tobacco mosaic virus by low-energy electron holography

    CERN Document Server

    Longchamp, Jean-Nicolas; Escher, Conrad; Fink, Hans-Werner

    2014-01-01

    Modern structural biology relies on NMR, X-ray crystallography and cryo-electron microscopy for gaining information on biomolecules at nanometer, sub-nanometer or atomic resolution. All these methods, however, require averaging over a vast ensemble of entities and hence knowledge on the conformational landscape of an individual particle is lost. Unfortunately, there are now strong indications that even X-ray free electron lasers will not be able to image individual molecules but will require nanocrystal samples. Here, we show that non-destructive structural biology of single particles has now become possible by means of low-energy electron holography. Individual tobacco mosaic viruses deposited on ultraclean freestanding graphene are imaged at one nanometer resolution revealing structural details arising from the helical arrangement of the outer protein shell of the virus. Since low-energy electron holography is a lens-less technique and since electrons with a deBroglie wavelength of approximately 1 Angstrom ...

  16. 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.

  17. 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.

  18. Geo-correction Algorithm Based on Equivalent RD Model for ScanSAR of HJ-1-C Satellite

    OpenAIRE

    Liu Jia-yin; Wen Shuang-yan; Zhang Hong-yi; Hong Wen

    2014-01-01

    HJ-1-C satellite is the first Synthetic Aperture Radar (SAR) satellite for civilian use in China, and it has a strip and scan mode. According to the characteristics of the ScanSAR of the HJ-1-C satellite, a geo-correction algorithm based on an equivalent RD model has been outlined in this paper on the basis of an ECS image processing algorithm and a traditional Range-Doppler location method. An azimuth mosaic was presented by a time series relationship, then the different burst was stitched b...

  19. Automatic analysis of change detection of multi-temporal ERS-2 SAR images by using two-threshold EM and MRF algorithms

    Institute of Scientific and Technical Information of China (English)

    CHEN Fei; LUO Lin; JIN Yaqiu

    2004-01-01

    To automatically detect and analyze the surface change in the urban area from multi-temporal SAR images, an algorithm of two-threshold expectation maximum (EM) and Markov random field (MRF) is developed. Difference of the SAR images demonstrates variation of backscattering caused by the surface change all over the image pixels. Two thresholds are obtained by the EM iterative process and categorized to three classes: enhanced scattering, reduced scattering and unchanged regimes. Initializing from the EM result, the iterated conditional modes (ICM) algorithm of the MRF is then used to analyze the detection of contexture change in the urban area. As an example, two images of the ERS-2 SAR in 1996 and 2002 over the Shanghai City are studied.

  20. A 12-bit, 1 MS/s SAR-ADC for a CZT-based multi-channel gamma-ray imager using a new digital calibration method

    Science.gov (United States)

    Liu, W.; Wei, T.; Yang, L.; Hu, Y.

    2016-03-01

    The successive approximation register-analog to digital converter (SAR-ADC) is widely used in the CdZnTe-based gamma-ray imager because of its outstanding characteristics of low power consumption, relatively high resolution, and small die size. This study proposes a digital bit-by-bit calibration method using an input ramp signal to further improve the conversion precision and power consumption of an SAR-ADC. The proposed method is based on the sub-radix-2 redundant architecture and the perturbation technique. The proposed calibration algorithm is simpler, more stable, and faster than traditional approaches. The prototype chip of the 12-bit, 1 MS/s radiation-hardened SAR-ADC has been designed and fabricated using the TSMC 0.35 μm 2P4M CMOS process. This SAR-ADC consumes 3 mW power and occupies a core area of 856× 802μm2. The digital bit-by-bit calibration algorithm is implemented via MATLAB for testing flexibility. The effective number of bits for this digitally calibrated SAR-ADC reaches 11.77 bits. The converter exhibits high conversion precision, low power consumption, and radiation-hardened design. Therefore, this SAR-ADC is suitable for multi-channel gamma-ray imager applications.