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Sample records for sar image processing

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. SAR processing using SHARC signal processing systems

    Science.gov (United States)

    Huxtable, Barton D.; Jackson, Christopher R.; Skaron, Steve A.

    1998-09-01

    Synthetic aperture radar (SAR) is uniquely suited to help solve the Search and Rescue problem since it can be utilized either day or night and through both dense fog or thick cloud cover. Other papers in this session, and in this session in 1997, describe the various SAR image processing algorithms that are being developed and evaluated within the Search and Rescue Program. All of these approaches to using SAR data require substantial amounts of digital signal processing: for the SAR image formation, and possibly for the subsequent image processing. In recognition of the demanding processing that will be required for an operational Search and Rescue Data Processing System (SARDPS), NASA/Goddard Space Flight Center and NASA/Stennis Space Center are conducting a technology demonstration utilizing SHARC multi-chip modules from Boeing to perform SAR image formation processing.

  8. SAR Systems and Related Signal Processing

    NARCIS (Netherlands)

    Hoogeboom, P.; Dekker, R.J.; Otten, M.P.G.

    1996-01-01

    Synthetic Aperture Radar (SAR) is today a valuable source of remote sensing information. SAR is a side-looking imaging radar and operates from airborne and spacebome platforms. Coverage, resolution and image quality are strongly influenced by the platform. SAR processing can be performed on standard

  9. SAR Systems and Related Signal Processing

    NARCIS (Netherlands)

    Hoogeboom, P.; Dekker, R.J.; Otten, M.P.G.

    1996-01-01

    Synthetic Aperture Radar (SAR) is today a valuable source of remote sensing information. SAR is a side-looking imaging radar and operates from airborne and spacebome platforms. Coverage, resolution and image quality are strongly influenced by the platform. SAR processing can be performed on standard

  10. 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.

  11. 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....

  12. 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.

  13. 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.

  14. Signal Processing for Digital Beamforming FMCW SAR

    Directory of Open Access Journals (Sweden)

    Qin Xin

    2014-01-01

    Full Text Available According to the limitations of single channel Frequency Modulation Continuous Wave (FMCW Synthetic Aperture Radar (SAR, Digital Beamforming (DBF technology is introduced to improve system performance. Combined with multiple receive apertures, DBF FMCW SAR can obtain high resolution in low pulse repetition frequency, which can increase the processing gain and decrease the sampling frequency. The received signal model of DBF FMCW SAR is derived. The continuous antenna motion which is the main characteristic of FMCW SAR received signal is taken into account in the whole signal processing. The detailed imaging diagram of DBF FMCW SAR is given. A reference system is also demonstrated in the paper by comparing with a single channel FMCW SAR. The validity of the presented diagram is demonstrated with a point target simulation results.

  15. 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.

  16. 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...

  17. 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.

  18. 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...

  19. 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...

  20. 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.

  1. Signal processing for FMCW SAR

    NARCIS (Netherlands)

    Meta, A.; Hoogeboom, P.; Ligthart, L.P.

    2007-01-01

    The combination of frequency-modulated continuous-wave (FMCW) technology and synthetic aperture radar (SAR) techniques leads to lightweight cost-effective imaging sensors of high resolution. One limiting factor to the use of FMCW sensors is the well-known presence of nonlinearities in the

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. Subsidence history of the city of Morelia, Mexico based on InSAR images processed as time series

    Science.gov (United States)

    Jaramillo, S. H.; Suárez, G.; López-Quiroz, P.

    2012-04-01

    The city of Morelia in central Mexico sits on lacustrine and fluvio-lacustrine deposits. Subsidence due to the extraction of water from the subsoil is evidenced by the presence of differential soil compaction, causing faulting and cracking of the ground and adjacent constructions. In order to study the subsidence history of the past nine years, twenty-eight ENVISAT Synthetic Aperture Radar (SAR) images acquired between May 2003 and September 2010 were processed using ROI_PAC. All scenes are descending orbit images. The resulting interferograms were filtered using an adaptive filter and, in order to increase coherence and signal-to-noise ratio, they were unwrapped using the "branch-cut" algorithm. A subset of the resulting interferograms was selected based on the following criteria. Only interferograms with spatial baseline of less than 400 m and a temporal baseline of less than 420 days were considered. The primary objective of our work was to determine the temporal evolution of the subsidence in different parts of the city. To this end, selected pixels are inverted in an independent manner from neighbouring pixels using a time series analysis. Preliminary results suggest that the central part of the basin, near the fault known as the "Central Camionera", the subsidence is almost constant with a value of 3 to 4 cm/yr until 2008. From this date on, the subsidence rates increase to values with an average of 7 to 8 cm/yr. This increase in the subsidence rate is clearly appreciated in the appearance of two clearly visible circular patterns from 2008 to 2010. Currently, an inversion is being conducted to obtain the overall subsidence history of the basin.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Permanent scatterer InSAR processing: Forsmark

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-04-15

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

  19. 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

  20. 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.

  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. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Efficient Time-Domain Imaging Processing for One-Stationary Bistatic Forward-Looking SAR Including Motion Errors

    Directory of Open Access Journals (Sweden)

    Hongtu Xie

    2016-11-01

    Full Text Available With the rapid development of the one-stationary bistatic forward-looking synthetic aperture radar (OS-BFSAR technology, the huge amount of the remote sensing data presents challenges for real-time imaging processing. In this paper, an efficient time-domain algorithm (ETDA considering the motion errors for the OS-BFSAR imaging processing, is presented. This method can not only precisely handle the large spatial variances, serious range-azimuth coupling and motion errors, but can also greatly improve the imaging efficiency compared with the direct time-domain algorithm (DTDA. Besides, it represents the subimages on polar grids in the ground plane instead of the slant-range plane, and derives the sampling requirements considering motion errors for the polar grids to offer a near-optimum tradeoff between the imaging precision and efficiency. First, OS-BFSAR imaging geometry is built, and the DTDA for the OS-BFSAR imaging is provided. Second, the polar grids of subimages are defined, and the subaperture imaging in the ETDA is derived. The sampling requirements for polar grids are derived from the point of view of the bandwidth. Finally, the implementation and computational load of the proposed ETDA are analyzed. Experimental results based on simulated and measured data validate that the proposed ETDA outperforms the DTDA in terms of the efficiency improvement.

  9. Efficient Time-Domain Imaging Processing for One-Stationary Bistatic Forward-Looking SAR Including Motion Errors.

    Science.gov (United States)

    Xie, Hongtu; Shi, Shaoying; Xiao, Hui; Xie, Chao; Wang, Feng; Fang, Qunle

    2016-11-12

    With the rapid development of the one-stationary bistatic forward-looking synthetic aperture radar (OS-BFSAR) technology, the huge amount of the remote sensing data presents challenges for real-time imaging processing. In this paper, an efficient time-domain algorithm (ETDA) considering the motion errors for the OS-BFSAR imaging processing, is presented. This method can not only precisely handle the large spatial variances, serious range-azimuth coupling and motion errors, but can also greatly improve the imaging efficiency compared with the direct time-domain algorithm (DTDA). Besides, it represents the subimages on polar grids in the ground plane instead of the slant-range plane, and derives the sampling requirements considering motion errors for the polar grids to offer a near-optimum tradeoff between the imaging precision and efficiency. First, OS-BFSAR imaging geometry is built, and the DTDA for the OS-BFSAR imaging is provided. Second, the polar grids of subimages are defined, and the subaperture imaging in the ETDA is derived. The sampling requirements for polar grids are derived from the point of view of the bandwidth. Finally, the implementation and computational load of the proposed ETDA are analyzed. Experimental results based on simulated and measured data validate that the proposed ETDA outperforms the DTDA in terms of the efficiency improvement.

  10. 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.

  11. 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.

  12. Scale transform algorithm used in FMCW SAR data processing

    Institute of Scientific and Technical Information of China (English)

    Jiang Zhihong; Kan Huangfu; Wan Jianwei

    2007-01-01

    The frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) is a light-weight,cost-effective, high-resolution imaging radar, which is suitable for a small flight platform. The signal model is derived for FMCW SAR used in unmanned aerial vehicles (UAV) reconnaissance and remote sensing. An appropriate algorithm is proposed. The algorithm performs the range cell migration correction (RCMC) for continuous nonchirped raw data using the energy invariance of the scaling of a signal in the scale domain. The azimuth processing is based on step transform without geometric resampling operation. The complete derivation of the algorithm is presented. The algorithm performance is shown by simulation results.

  13. The capability of time- and frequency-domain algorithms for bistatic SAR processing

    Science.gov (United States)

    Vu, Viet T.; Sjögren, Thomas K.; Pettersson, Mats I.

    2013-05-01

    The paper presents a study of the capability of time- and frequency-domain algorithms for bistatic SAR processing. Two typical algorithms, Bistatic Fast Backprojection (BiFBP) and Bistatic Range Doppler (BiRDA), which are both available for general bistatic geometry, are selected as the examples of time- and frequency-domain algorithms in this study. Their capability is evaluated based on some criteria such as processing time required by the algorithms to reconstruct SAR images from bistatic SAR data and the quality assessments of those SAR images.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. GNSS-based bistatic SAR: a signal processing view

    Science.gov (United States)

    Antoniou, Michail; Cherniakov, Mikhail

    2013-12-01

    This article presents signal processing algorithms used as a new remote sensing tool, that is passive bistatic SAR with navigation satellites (e.g. GPS, GLONASS or Galileo) as transmitters of opportunity. Signal synchronisation and image formation algorithms are described for two system variants: one where the receiver is moving and one where it is fixed on the ground. The applicability and functionality of the algorithms described is demonstrated through experimental imagery that ultimately confirms the feasibility of the overall technology.

  7. 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.

  8. 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.

  9. Modified Frequency Scaling Algorithm for FMCW SAR Data Processing

    Institute of Scientific and Technical Information of China (English)

    Jiang Zhihong; Huang Fukan; Wan Jianwei; Cheng Zhu

    2007-01-01

    This paper presents a modified frequency scaling algorithm for frequency modulated continuous wave synthetic aperture radar(FMCW SAR) data processing. The relative motion between radar and target in FMCW SAR during reception and between transmission and reception will introduce serious dilation in the received signal. The dilation can cause serious distortions in the reconstructed images using conventional signal processing methods. The received signal is derived and the received signal in range-Doppler domain is given.The relation between the phase resulting from antenna motion and the azimuth frequency is analyzed. The modified frequency scaling algorithm is proposed to process the received signal with serious dilation. The algorithm can effectively eliminate the impact of the dilation. The algorithm performances are shown by the simulation results.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. Accelerated Scientific InSAR Processing Project

    Data.gov (United States)

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

  20. 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.

  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. 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.

  3. The Role of Feature Enhanced Processing for Automatic Target Recognition using High Resolution Polarimetric SAR Data

    NARCIS (Netherlands)

    Broek, A.C. van den; Steeghs, T.P.H.; Dekker, R.J.

    2005-01-01

    We have studied the effect of feature enhanced processing on the discrimination of targets in highresolution polarimetric ISAR and SAR images. This is done by comparing feature-based classification results for original images and images which have been pre-processed to enhance target features. The d

  4. 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.

  5. 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...

  6. Signal Processing for High Resolution FMCW SAR and Moving Target

    NARCIS (Netherlands)

    Meta, A.; Hoogeboom, P.

    2005-01-01

    The combination of Frequency Modulated ContinuousWave (FMCW) technology and Synthetic Aperture Radar (SAR) leads to lightweight, cost-effective imaging sensors of high resolution. In FMCW SAR applications the conventional stop-and-go approximation used in pulse radar algorithms cannot be considered

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. The Capability of Time- And Frequency-domain Algorithms for Bistatic SAR Processing

    OpenAIRE

    Vu, Viet; Sjögren, Thomas; Pettersson, Mats

    2013-01-01

    The paper presents a study of the capability of time- And frequency-domain algorithms for bistatic SAR processing. Two typical algorithms, Bistatic Fast Backprojection (BiFBP) and Bistatic Range Doppler (BiRDA), which are both available for general bistatic geometry, are selected as the examples of time- And frequency-domain algorithms in this study. Their capability is evaluated based on some criteria such as processing time required by the algorithms to reconstruct SAR images from bistatic ...

  12. TanDEM-X Bistatic SAR Processing

    OpenAIRE

    Balss, Ulrich; Niedermeier, Andreas; Breit, Helko

    2010-01-01

    In June, 2010 the German SAR satellite TanDEM-X (TerraSAR-X-Add-on for Digital Elevation Measurements) will be launched. Together with TerraSAR-X, launched June 15, 2007, it will form the first spaceborne bistatic SAR platform. Usually one of the satellite is transmitting (active satellite), while both are receiving. As both satellites fly in a helix orbit constellation, during a recording a satellite has to be passive, if the other one is close to the line of sight to the observation targ...

  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. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 一种基于RD成像逆处理的双基地SAR回波模拟算法%An Echo Simulation Algorithm Based on Inverse Processing of RD Imaging for Bistatic SAR

    Institute of Scientific and Technical Information of China (English)

    张顺生; 陆逸; 曹建蜀

    2013-01-01

    与传统单基地SAR相比,双基地SAR具有获取信息丰富、抗电子干扰、抗摧毁、抗截获等优点,因而其应用场景更加广阔.然而,由于双基地SAR系统面临空时频同步等技术难题,获取实际的双基地SAR回波数据非常困难.因此,本文提出一种基于RD成像逆处理的双基地SAR回波模拟算法.该算法基于二维驻定相位原理和RD成像处理的逆过程,实现了双基地SAR回波数据的快速模拟.这种算法的运算速度与距离时域叠加算法和一维FFT算法相比有显著提高,且可以适用于移变模式.点目标和自然场景的仿真结果验证了算法的有效性.仿真速度的测试结果验证了算法的高效性.%Compared with traditional monostatic SAR, Bistatic synthetic aperture radar has the advantages of obtaining richer information, anti-electronic jamming, anti-destroy, anti-intercept. So, it has broader application prospect. However, bistatic SAR system is confronted with the space, time and frequency synchronization and other technical problems. It is very difficult to obtain the actual bistatic SAR echo data. So, a fast echo simulation algorithm based on two-dimensional principle of stationary phase (2D-PSP) and inverse processing of RD imaging algorithm was proposed in this paper. Firstly, the two-dimensional spectrum of bistatic SAR echo was deduced by using the theory of two-dimensional principle of stationary phase. Then corresponding inverse processing was taken in accordance with the steps of imaging process. At last, a fast echo data simulation for bistatic SAR was achieved. Comparing to distance time-domain overlay algorithm and one-dimensional FFT algorithm, this algorithm's simulating speed has a significant improvement and it can be used on shift-variant mode. The simulation results of a point target and natural scene verify the effectiveness of the algorithm. The test result of simulating speed can verify high efficiency of the algorithm.

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. Image processing

    NARCIS (Netherlands)

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

    2007-01-01

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

  1. 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.

  2. 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.

  3. 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%.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. Bistatic SAR tomography: processing and experimental results

    OpenAIRE

    Duque Biarge, Sergio; López Dekker, Francisco J.; Merlano Duncan, Juan Carlos; Mallorquí Franquet, Jordi Joan

    2010-01-01

    This paper presents across-track tomography applied to a bistatic geometry with fixed receivers. This kind of geometry can overcome some of the classical monostatic tomography limitations such as temporal decorrelation and irregular baseline distribution. The Remote Sensing Laboratory (RSLab)of the Universitat Politècnica de Catalunya (UPC) has implemented a SAR Bistatic Receiver for INterferometric Applications,SABRINA, with 4-channels. SABRINA has been used to carry out a bistatic tomogr...

  19. High Resolution Processing with an Active Phased Array SAR

    NARCIS (Netherlands)

    Nijenboer, F.J.; Otten, M.P.G.

    1999-01-01

    The Dutch PHARUS system is a polarimetric active phased array SAR capable of performing advanced SAR modes. Advanced SAR modes that are being investigated are: spotlight SAR, sliding spotlight SAR, stepped frequency SAR and interferometric SAR. The flight experiments and automatic beam steering

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Using Open-Source Components to Process Interferometric TerraSAR-X Spotlight Data

    Directory of Open Access Journals (Sweden)

    Michael Jendryke

    2013-01-01

    Full Text Available We address the processing of interferometric TerraSAR-X and TanDEM-X spotlight data. Processing steps necessary to derive interferograms at high spatial resolution from bi- and monostatic satellite images will be explained. The spotlight image mode is a beam steering technique focusing the antenna on a specific ground area. This results in a linear Doppler shift frequency in azimuth direction, which has to be matched to the master image. While shifting the interpolation kernel in azimuth during resampling, the frequency spectrum of the slave image is aligned to the master image. We show how to process bistatic TanDEM-X images and propose an integrated processing option for monostatic TerraSAR-X data in the Delft Object-oriented Radar Interferometric Software (DORIS. The paper focuses on the implementation of this algorithm for high-resolution spotlight InSAR in a public domain tool; hence, it becomes available to a larger research community. The results are presented for three test areas: Uluru in Australia, Las Vegas in the USA, and Lüneburg in Germany.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Antiparallel Aspects of Airborne Dual-antenna InSAR Data Processing and Analysis

    Directory of Open Access Journals (Sweden)

    Li Fang-fang

    2015-02-01

    Full Text Available Interferometric Synthetic Aperture Radar (InSAR is a powerful technique for precise topographic mapping. However, owing to the side-looking SAR imaging geometry, geometry distortions appear in mountainous scenarios. Because of phase discontinuities or the absence of a valid phase, it is difficult to recover accurate DEM in such areas with single-aspect InSAR data. Fusion of two or more different aspects of InSAR data can deal with this problem in practice. Experiments using two antiparallel aspects of airborne InSAR data are carried out based on this idea. To decrease the processing error in single-aspect data and fuse them seamlessly, a MOtion COmpensation (MOCO method using iterative DEM is used to reduce the MOCO error. Besides, phase-unwrapping methods based on terrain characteristics are proposed to avoid phase-unwrapping error owing to phase discontinuities in areas of shadow and layover. Experimental results verify the effectiveness of the processing methods.

  14. SAR Processing Based On Two-Dimensional Transfer Function

    Science.gov (United States)

    Chang, Chi-Yung; Jin, Michael Y.; Curlander, John C.

    1994-01-01

    Exact transfer function, ETF, is two-dimensional transfer function that constitutes basis of improved frequency-domain-convolution algorithm for processing synthetic-aperture-radar, SAR data. ETF incorporates terms that account for Doppler effect of motion of radar relative to scanned ground area and for antenna squint angle. Algorithm based on ETF outperforms others.

  15. 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.

  16. 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.

  17. Image Processing

    Science.gov (United States)

    1993-01-01

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

  18. ISCE: A Modular, Reusable Library for Scalable SAR/InSAR Processing

    Science.gov (United States)

    Agram, P. S.; Lavalle, M.; Gurrola, E. M.; Sacco, G. F.; Rosen, P. A.

    2016-12-01

    Traditional community SAR/InSAR processing software tools have primarily focused on differential interferometry and Solid Earth applications. The InSAR Scientific Computing Environment (ISCE) was specifically designed to support the Earth Sciences user community as well as large scale operational processing tasks, thanks to its two-layered (Python+C/Fortran) architecture and modular framework. ISCE is freely distributed as a source tarball, allowing advanced users to modify and extend it for their research purposes and developing exploratory applications, while providing a relatively simple user interface for novice users to perform routine data analysis efficiently. Modular design of the ISCE library also enables easier development of applications to address the needs of Ecosystems, Cryosphere and Disaster Response communities in addition to the traditional Solid Earth applications. In this talk, we would like to emphasize the broader purview of the ISCE library and some of its unique features that sets it apart from other freely available community software like GMTSAR and DORIS, including: Support for multiple geometry regimes - Native Doppler (ALOS-1) as well Zero Doppler (ESA missions) systems. Support for data acquired by airborne platforms - e.g, JPL's UAVSAR and AirMOSS, DLR's F-SAR. Radiometric Terrain Correction - Auxiliary output layers from the geometry modules include projection angles, incidence angles, shadow-layover masks. Dense pixel offsets - Parallelized amplitude cross correlation for cryosphere / ionospheric correction applications. Rubber sheeting - Pixel-by-pixel offsets fields for resampling slave imagery for geometric co-registration/ ionospheric corrections. Preliminary Tandem-X processing support - Bistatic geometry modules. Extensibility to support other non-Solid Earth missions - Modules can be directly adopted for use with other SAR missions, e.g., SWOT. Preliminary support for multi-dimensional data products- multi-polarization, multi

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

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

    Science.gov (United States)

    Bahr, Thomas

    2014-05-01

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

  14. 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.

  15. 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.

  16. 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.

  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. 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.

  19. 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.

  20. 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.

  1. 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.

  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. 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.

  4. 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

  5. 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.

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    A. Castillo Atoche

    2013-01-01

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

  8. 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.

  9. 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.

  10. 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

  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. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

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

    Science.gov (United States)

    Casu, Francesco; Manunta, Michele

    2016-04-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

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

    Science.gov (United States)

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

    2017-04-01

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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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。

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

    Directory of Open Access Journals (Sweden)

    Zhi Zhao

    2013-01-01

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

  19. 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...

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

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

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

  1. 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.

  2. 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.

  3. Planned Data Products and Science Processing Paradigm for the Proposed NASA-ISRO SAR Mission

    Science.gov (United States)

    Rosen, P. A.

    2014-12-01

    The proposed NASA-ISRO Synthetic Aperture Radar (SAR), or NISAR, Mission will make global integrated measurements of the causes and consequences of land surface changes. NISAR would provide a means of disentangling highly spatial and temporally complex processes ranging from ecosystem disturbances, to ice sheet collapse and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. The mission would capable of performing repeat-pass interferometry and collecting polarimetric data. The core of the payload would consist of an L-band SAR to meet all of the NASA science requirements. A secondary S-band SAR would be contributed by ISRO, the Indian Space Research Organisation. The instrument would comprise a large diameter deployable reflector and a dual frequency antenna feed and associated electronics to implement the fine-resolution, polarimetric, 240-km swath imaging system. Combined with an ambitious data acquisition plan that supports continuous mapping of Earth's land and ice-covered surfaces at every opportunity over the life of the mission, the mission would generate over 1 Petabyte of raw data each year, which expands to greater data volumes for higher level products. Since many of the science requirements propose time-series analysis, which often involve combinatorial manipulation of images acquired over time, it would be impractical and inadvisable to create global time-series science products. As a result, the processing plan for the mission would be for the project to create a complete set of products through Level 2, and only selected Level 3 products over extended areas of calibration and validation. These sites would be chosen to be scientifically interesting, so that the mission products would include significant scientific results. In addition, the project will develop higher-level processing software to the community that will allow scientists to apply the mission data from Level 0 to 2 to their science problems.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ryan, T.G.

    1995-03-01

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

  18. 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.

  19. 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.

  20. 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

  1. 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)...

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Landslide monitoring by Terrestrial SAR Interferometry: critical analysis of different data processing approaches

    Science.gov (United States)

    Brunetti, Alessandro; Crosetto, Michele; Mazzanti, Paolo; Monserrat, Oriol

    2015-04-01

    In last years, Terrestrial Synthetic Aperture Radar Interferometry (TInSAR) became a key technology in the field of landslide and structures/infrastructures displacement monitoring. Thanks to undoubted advantages such as i) widespread information, ii) fully remote applicability over long ranges and iii) high accuracy, this technique promises to be a very effective solution for a lot of geological and engineering issues. Even if this technique was born for interferometric analyses (basing on the phase differences between SAR images collected at different time intervals), recent studies demonstrated its reliability also with non-interferometric processing approaches, based on the amplitude tracking of high-reflectivity objects (i.e. corner reflectors). Furthermore, both approaches can be used for both continuous and discontinuous monitoring, thus opening to a wide spectrum of applications for different purposes. The aim of this work is to provide information about the reliability and the accuracy of TInSAR technique in its different kind of applications. In the frame of this work, two case studies of landslides monitored with a continuous acquisition mode (about 5 minutes sampling rate) have been investigated. The first case study consists of superficial instability problems mainly related to huge rainfalls and works, leading to non-linear displacements up to 10 mm/day. In order to assess the impact of discontinuous acquisition mode, data subsampling of one data/day for an overall monitoring period of about 3 months has been performed. The comparison between discontinuous and continuous interferometric processing approach allowed the identification of some aliasing and ambiguity problems in the discontinuous approach, especially in periods when high displacement rates were affecting the slope. Nevertheless, in most of such cases, it was still possible to provide qualitative information about criticalities, even if a precise estimation of displacement entities was

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

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

    Directory of Open Access Journals (Sweden)

    Enrico Stein

    2013-10-01

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

  5. 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.

  6. 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.

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

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    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.

  8. 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.

  9. 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.

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

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    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.

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

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    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.

  12. 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

  13. Progress on the calibration of channel geometry and friction parameters of the LISFLOOD-FP hydraulic model using time series of SAR flood images

    Science.gov (United States)

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

    2014-12-01

    The objective of this work is to calibrate channel depth and roughness parameters of the LISFLOOD-FP Sub-Grid 2D hydraulic model using SAR image-derived flood extent maps. The aim is to reduce uncertainty in flood model predictions for those rivers where channel geometry is unknown and/or cannot be easily measured. In particular we consider the effectiveness of using real SAR data for calibration and whether the number and timings of SAR acquisitions is of benefit to the final result. Terrain data are processed from 2m LiDAR images and inflows to the model are taken from gauged data. As a test case we applied the method to the River Severn between Worcester and Tewkesbury. We firstly applied the automatic flood mapping algorithm of Giustarini[1] et al. (2013) to ENVISAT ASAR (wide swath mode) flood images; generating a series of flood maps. We then created an ensemble of flood extent maps with the hydraulic model (each model representing a unique parameter set). Where there is a favourable comparison between the modelled flood map and the SAR obtained flood map we may suggest an optimal parameter set. Applying the method to a sequence of SAR acquisitions provides insight into the advantages, disadvantages and limitations of using series of acquired images. To complete the investigation we simultaneously explore parameter 'identifiabilty' within a sequence of available satellite observations by adopting the DYNIA method proposed by Wagener[2] et al. (2003). We show where we might most easily detect the depth and roughness parameters within the SAR acquisition sequence. [1] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 4. [2] Wagener. 2003. 'Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis'. Hydrol. Process. 17, 455-476.

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

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    Huaizong Shao

    2013-03-01

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

  15. 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.

  16. 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.

  17. 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.

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

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    Dongqing Peng

    2016-11-01

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

  19. Automatic Geocoding of SAR Image Using SRTM DEM and Landsat TM Image%基于SRTM DEM和Landsat TM数据的SAR图像自动地理编码

    Institute of Scientific and Technical Information of China (English)

    黄燕平; 凌飞龙; 吴波

    2013-01-01

    The special slant-range imaging mode of Radar image makes it difficult to use traditional correction method to geocode it.Commonly we simulate a radar image using DEM and SAR geometry information to geocode a real SAR image.In the application of regional cartographic imaging,when we encounter flat areas,the features of simulated SAR image are not so obvious,making its failure to match the real SAR image and failure of automatic correction of a wide range of SAR image.In this paper,we analyzed and discussed the principle and process of the image simulation and image matching.By achieving the automatic determination of the offset between radar image and simulated SAR image matching the signal-noise ratio requirements or not,we can automatically determine whether or not to use the TM image which contain thematic information of feature,instead of the simulated SAR image for matching with the real radar image.The method achieves automatic geocoding of mass SAR image as the same time.%合成孔径雷达(SAR)图像特殊的斜距成像方式使得利用传统的校正方法很难校正雷达图像.常用的方法是利用DEM和SAR成像几何信息模拟的SAR图像对真实SAR图像进行校正.在区域制图中,平坦地区由于没有地形起伏特征,使得模拟SAR图像特征不明显,无法建立与真实SAR图像的配准关系.本文在研究大范围SAR图像自动化地理编码的过程中,分析讨论了图像模拟和图像匹配的原理和过程,实现了自动判断模拟SAR图像与真实SAR图像的匹配偏移量是否达到信噪比要求,从而自动判断是否使用具有地物专题信息的TM图像代替模拟SAR图像和真实SAR图像进行匹配,实现了海量SAR图像地理编码的自动化.

  20. 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.

  1. 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.

  2. 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.

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

    Science.gov (United States)

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

    2013-04-01

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

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

    Science.gov (United States)

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

    2014-11-01

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

  5. 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.

  6. Monitoring land subsidence process in the urban area of Ho Chi Minh city, Vietnam using multi-temporal SAR Interferometry

    Science.gov (United States)

    Nguyen, Xuan; Chang, Chung-Pai; Le, Tuan

    2016-04-01

    Land subsidence has become the most common hazard in urban area that could led to cracking buildings and infrastructures, extending the flooding area or even change the river path. Despite deriving precise information, conventional subsidence monitoring techniques are considered as costly, man-power consuming and lack of comprehensive information. Recently, SAR Interferometry (InSAR) has become a widely used geodetic technique for monitoring the deformation of the Earth's surface, especially methods based on the use of a multi-temporal dataset. In this study, we use a stack of 18 SAR images acquired from L-band PALSAR sensor onboard the ALOS satellite to derive the subsidence information of Ho Chi Minh city, Vietnam over the period of December 2006 to December 2010. The Stanford Method for Persistent Scatterers (StaMPS) Multi-Temporal Interferometry (MTI) approach is chosen to take advantages of both the persistent scatterers and the distributed scatterers, which could be used as monitoring points to measure the subsidence process. Assume the subsidence in this area mostly corresponds to vertical components, we found subsidence patterns along Saigon river and in the South of the city. Maximum subsidence rate reaches up to -66 mm/year in vertical direction. Finally, InSAR derived result and previous levelling data are taken into comparison to find the correlation between the two results.

  7. Analytical SAR-GMTI principles

    Science.gov (United States)

    Soumekh, Mehrdad; Majumder, Uttam K.; Barnes, Christopher; Sobota, David; Minardi, Michael

    2016-05-01

    This paper provides analytical principles to relate the signature of a moving target to parameters in a SAR system. Our objective is to establish analytical tools that could predict the shift and smearing of a moving target in a subaperture SAR image. Hence, a user could identify the system parameters such as the coherent processing interval for a subaperture that is suitable to localize the signature of a moving target for detection, tracking and geolocating the moving target. The paper begins by outlining two well-known SAR data collection methods to detect moving targets. One uses a scanning beam in the azimuth domain with a relatively high PRF to separate the moving targets and the stationary background (clutter); this is also known as Doppler Beam Sharpening. The other scheme uses two receivers along the track to null the clutter and, thus, provide GMTI. We also present results on implementing our SAR-GMTI analytical principles for the anticipated shift and smearing of a moving target in a simulated code. The code would provide a tool for the user to change the SAR system and moving target parameters, and predict the properties of a moving target signature in a subaperture SAR image for a scene that is composed of both stationary and moving targets. Hence, the SAR simulation and imaging code could be used to demonstrate the validity and accuracy of the above analytical principles to predict the properties of a moving target signature in a subaperture SAR image.

  8. 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.

  9. 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.

  10. 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).

  11. 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

  12. 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....

  13. 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.

  14. 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.

  15. SAR processing based on the exact two-dimensional transfer function

    Science.gov (United States)

    Chang, C. Y.; Jin, M. Y.; Curlander, J. C.

    1992-01-01

    The two-dimensional transfer functions of several synthetic aperture radar (SAR) focusing algorithms are derived considering the spaceborne SAR environments. The formulation includes the factors of the earth rotation and the antenna squint angles. The resultant transfer functions are explicitly expressed in terms of Doppler centroid frequency and Doppler frequency rate, which can be accurately estimated from the SAR data. Point target simulation results show that the algorithm based on the two-dimensional Fourier transformation outperforms the one-dimensional one for processing data acquired from high squint angles. The two-dimensional Fourier transformation approach appears to be a viable and simple solution for the processor design of future spaceborne SAR systems.

  16. 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.

  17. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1995-03-01

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

  19. 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.

  20. 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.

  1. 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.

  2. 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%.

  3. 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.

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

    NARCIS (Netherlands)

    Meta, A.; Hoogeboom, P.

    2005-01-01

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

  5. 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

  6. Enhanced SAR data processing for land instability forecast.

    Science.gov (United States)

    Argentiero, Ilenia; Pellicani, Roberta; Spilotro, Giuseppe; Parisi, Alessandro; Bovenga, Fabio; Pasquariello, Guido; Refice, Alberto; Nutricato, Raffaele; Nitti, Davide Oscar; Chiaradia, Maria Teresa

    2017-04-01

    Monitoring represents the main tool for carrying out evaluation procedures and criteria for spatial and temporal landslide forecast. The forecast of landslide behaviour depends on the possibility to identify either evidences of activity (displacement, velocity, volume of unstable mass, direction of displacement, and their temporal variation) or triggering parameters (rainfalls). Generally, traditional geotechnical landslide monitoring technologies permit to define, if correctly positioned and with adequate accuracy, the critical value of displacement and/or acceleration into landslide body. In most cases, they do not allow real time warning signs to be generated, due to environmental induced errors, and the information is related to few points on unstable area. Remote-sensing monitoring instruments are capable of inspecting an unstable slope with high spatial and temporal frequency, but allow solely measurements of superficial displacements and deformations. Among these latest technologies, the satellite Persistent Scatterer SAR Interferometry (PSInSAR) is very useful to investigate the unstable area both in terms of space and time. Indeed, this technique allows to analyse wide areas, individuate critical unstable areas, not identifiable by means detailed in situ surveys, and study the phenomenon evolution in a long time-scale. Although this technique usually adopts, as first approximation, a linear model to describe the displacement of the detected targets, also non-linear models can be used. However, the satellite revisit time, which defines the time sampling of the detected displacement signal, limits the maximum measurable velocity and acceleration. This makes it difficult to assess in the short time any acceleration indicating a loss of equilibrium and, therefore, a probable reactivation of the landslide. The recent Sentinel-1 mission from the European Space Agency (ESA), provides a spatial resolution comparable to the previous ESA missions, but a nominal

  7. 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.

  8. 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。

  9. 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.

  10. 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.

  11. 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.

  12. Weighted LBF for spaceborne general bistatic SAR processing

    Institute of Scientific and Technical Information of China (English)

    Jinshan Ding; Otmar Loffeld; Robert Wang; Holger Nies; U1-Ann Qurat; Zheng Bao

    2008-01-01

    Loffeld's bistatic formula (LBF) is the first two-dimensional analytic point target reference spectrum derived for general bistatic SAR frequency domain focusing.The phase history is expanded in Taylor series around the individual points of stationary phase of the transmitter-target and target-receiver phase histories,respectively,and thus the common bistatic stationary phase point can be obtained using the method of stationary phase.Unfortunately,it shows limitations for extreme bistatic configurations,namely the highly squinted mode and space-surface application.The weighted LBF (WLBF) is proposed in this paper based on the different contributions of total phase modulation from the transmitter and receiver.The formulae we derived are compared with that of the original literature.The extreme bistatic stripmap SAR data can be focused using WLBF,which accommodates the spaceborne squint geometry using the modified effective velocity solution.A point target simulation example is presented to verify the accuracy of the new WLBF spectrum.

  13. Hyperspectral image processing methods

    Science.gov (United States)

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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Satellite SAR geocoding with refined RPC model

    Science.gov (United States)

    Zhang, Lu; Balz, Timo; Liao, Mingsheng

    2012-04-01

    Recent studies have proved that the Rational Polynomial Camera (RPC) model is able to act as a reliable replacement of the rigorous Range-Doppler (RD) model for the geometric processing of satellite SAR datasets. But its capability in absolute geolocation of SAR images has not been evaluated quantitatively. Therefore, in this article the problems of error analysis and refinement of SAR RPC model are primarily investigated to improve the absolute accuracy of SAR geolocation. Range propagation delay and azimuth timing error are identified as two major error sources for SAR geolocation. An approach based on SAR image simulation and real-to-simulated image matching is developed to estimate and correct these two errors. Afterwards a refined RPC model can be built from the error-corrected RD model and then used in satellite SAR geocoding. Three experiments with different settings are designed and conducted to comprehensively evaluate the accuracies of SAR geolocation with both ordinary and refined RPC models. All the experimental results demonstrate that with RPC model refinement the absolute location accuracies of geocoded SAR images can be improved significantly, particularly in Easting direction. In another experiment the computation efficiencies of SAR geocoding with both RD and RPC models are compared quantitatively. The results show that by using the RPC model such efficiency can be remarkably improved by at least 16 times. In addition the problem of DEM data selection for SAR image simulation in RPC model refinement is studied by a comparative experiment. The results reveal that the best choice should be using the proper DEM datasets of spatial resolution comparable to that of the SAR images.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  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. 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.

  13. Computerized ionospheric tomography based on geosynchronous SAR

    Science.gov (United States)

    Hu, Cheng; Tian, Ye; Dong, Xichao; Wang, Rui; Long, Teng

    2017-02-01

    Computerized ionospheric tomography (CIT) based on spaceborne synthetic aperture radar (SAR) is an emerging technique to construct the three-dimensional (3-D) image of ionosphere. The current studies are all based on the Low Earth Orbit synthetic aperture radar (LEO SAR) which is limited by long repeat period and small coverage. In this paper, a novel ionospheric 3-D CIT technique based on geosynchronous SAR (GEO SAR) is put forward. First, several influences of complex atmospheric environment on GEO SAR focusing are detailedly analyzed, including background ionosphere and multiple scattering effects (induced by turbulent ionosphere), tropospheric effects, and random noises. Then the corresponding GEO SAR signal model is constructed with consideration of the temporal-variant background ionosphere within the GEO SAR long integration time (typically 100 s to 1000 s level). Concurrently, an accurate total electron content (TEC) retrieval method based on GEO SAR data is put forward through subband division in range and subaperture division in azimuth, obtaining variant TEC value with respect to the azimuth time. The processing steps of GEO SAR CIT are given and discussed. Owing to the short repeat period and large coverage area, GEO SAR CIT has potentials of covering the specific space continuously and completely and resultantly has excellent real-time performance. Finally, the TEC retrieval and GEO SAR CIT construction are performed by employing a numerical study based on the meteorological data. The feasibility and correctness of the proposed methods are verified.

  14. 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.

  15. A Research on Airborne Squint Hybrid SAR

    Institute of Scientific and Technical Information of China (English)

    BIANYong; ZHOUYinqing; LIChunsheng

    2004-01-01

    In this paper, we establish the squint mode hybrid SAR (Synthetic aperture radar) geometry. Based on the squint mode SAR geometry, the hybrid SAR signal model in squint case is derived. Based on this signal model, the hybrid SAR imaging process parameter is discussed. Aimed at the squint case, we analyze not only the relationship between the resolution and SAR system parameters, but also the relation between the time extension of the maximum azimuth signal and SAR system parameters. This research establishes the theoretical foundation for the design of squint hybrid SAR and serves as a good guide for the future work of improving the resolution of squint hybrid SAR. Based on the two-step algorithm, by considering the squint angle and cubic phase term, we are going to use the deramp SC-Chirp Scaling algorithm for squint hybrid SAR imaging. This algorithm uses the deramp method for the first step processing, and the SC-Chirp Scaling algorithm for the second step processing. The process procedure of this algorithm includes the squint angle, has the explicit physical meaning, therefore is convenient for analysis. The computer simulation result proves the validity of the analysis.

  16. 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.

  17. 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.

  18. 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.

  19. Cascades of InSAR in the Cascades - outlook for the use of InSAR and space-based imaging catalogues in a Subduction Zone Observatory

    Science.gov (United States)

    Lohman, R. B.

    2015-12-01

    Interferometric synthetic aperture radar (InSAR) has long demonstrated its utility to studies of subduction zone earthquakes, crustal events and volcanic processes, particularly in regions with very good temporal data coverage (e.g., Japan), or arid regions where the timescale of surface change is long compared to the repeat time of the available SAR imagery (e.g., portions of South America). Recently launched and future SAR missions with open data access will increase the temporal sampling rates further over many areas of the globe, resulting in a new ability to lower the detection threshold for earthquakes and, potentially, interseismic motion and transients associated with subduction zone settings. Here we describe some of the anticipated detection abilities for events ranging from earthquakes and slow slip along the subduction zone interface up to landslides, and examine the variations in land use around the circum-Pacific and how that and its changes over time will affect the use of InSAR. We will show the results of an effort to combine Landsat and other optical imagery with SAR data catalogues in the Pacific Northwest to improve the characterization of ground deformation signals, including the identification of "spurious" signals that are not related to true ground deformation. We also describe prospects for working with other communities that are interested in variations in soil moisture and vegetation structure over the same terrain.

  20. Incorporating uncertanity into Markov random field classification with the combine use of optical and SAR images and aduptive fuzzy mean vector

    Science.gov (United States)

    Welikanna, D. R.; Tamura, M.; Susaki, J.

    2014-09-01

    A Markov Random Field (MRF) model accounting for the classification uncertainty using multisource satellite images and an adaptive fuzzy class mean vector is proposed in this study. The work also highlights the initialization of the class values for an MRF based classification for synthetic aperture radar (SAR) images using optical data. The model uses the contextual information from the optical image pixels and the SAR pixel intensity with corresponding fuzzy grade of memberships respectively, in the classification mechanism. Sub pixel class fractions estimated using Singular Value Decomposition (SVD) from the optical image initializes the class arrangement for the MRF process. Pair-site interactions of the pixels are used to model the prior energy from the initial class arrangement. Fuzzy class mean vector from the SAR intensity pixels is calculated using Fuzzy C-means (FCM) partitioning. Conditional probability for each class was determined by a Gamma distribution for the SAR image. Simulated annealing (SA) to minimize the global energy was executed using a logarithmic and power-law combined annealing schedule. Proposed technique was tested using an Advanced Land Observation Satellite (ALOS) phased array type L-band SAR (PALSAR) and Advanced Visible and Near-Infrared Radiometer-2 (AVNIR-2) data set over a disaster effected urban region in Japan. Proposed method and the conventional MRF results were evaluated with neural network (NN) and support vector machine (SVM) based classifications. The results suggest the possible integration of an adaptive fuzzy class mean vector and multisource data is promising for imprecise class discrimination using a MRF based classification.

  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. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Synthetic aperture radar image processing techniques for damage detection of FRP-concrete systems

    Science.gov (United States)

    Yu, Tzuyang

    2017-04-01

    Electromagnetic imaging enables researchers and engineers to assess the surface and subsurface condition of concrete structures using radar and microwave sensors. Among existing radar imaging methods, synthetic aperture radar (SAR) imaging offers flexible resolution for various purposes in condition assessment. In this paper, two novel SAR image processing techniques are reported for the subsurface condition assessment of FRP(fiber reinforced polymer)-strengthened concrete systems; mathematical morphology (MM) and the K-R-I transform. Glass FRP (GFRP) and carbon CFRP (CFRP) strengthened concrete cylinders are used as examples. From our experimental results, it is found that both techniques are capable of quantifying SAR images for condition assessment. It is also found that Euler's number and the coefficient of correlation of K-R-I curves of SAR images can be used for monitoring subsurface changes in FRP-concrete systems.

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

    KAUST Repository

    Wang, Teng

    2015-02-03

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

  9. 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.

  10. Image processing mini manual

    Science.gov (United States)

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

    1992-01-01

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

  11. Image Processing Software

    Science.gov (United States)

    1992-01-01

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

  12. Motion measurement errors and autofocus in bistatic SAR.

    Science.gov (United States)

    Rigling, Brian D; Moses, Randolph L

    2006-04-01

    This paper discusses the effect of motion measurement errors (MMEs) on measured bistatic synthetic aperture radar (SAR) phase history data that has been motion compensated to the scene origin. We characterize the effect of low-frequency MMEs on bistatic SAR images, and, based on this characterization, we derive limits on the allowable MMEs to be used as system specifications. Finally, we demonstrate that proper orientation of a bistatic SAR image during the image formation process allows application of monostatic SAR autofocus algorithms in postprocessing to mitigate image defocus.

  13. Snow Water Equivalent Retrieval Using Multitemporal COSMO Skymed X-Band SAR Images To Inform Water Systems Operation

    Science.gov (United States)

    Denaro, S.; Del Gobbo, U.; Castelletti, A.; Tebaldini, S.; Monti Guarnieri, A.

    2015-12-01

    In this work, we explore the use of exogenous snow-related information for enhancing the operation of water facilities in snow dominated watersheds. Traditionally, such information is assimilated into short-to-medium term streamflow forecasts, which are then used to inform water systems operation. Here, we adopt an alternative model-free approach, where the policy is directly conditioned upon a small set of selected observational data able to surrogate the snow-pack dynamics. In snow-fed water systems, the Snow Water Equivalent (SWE) stored in the basin often represents the largest contribution to the future season streamflow. The SWE estimation process is challenged by the high temporal and spatial variability of snow-pack and snow properties. Traditional retrieval methods, based on few ground sensors and optical satellites, often fail at representing the spatial diversity of snow conditions over large basins and at producing continuous (gap-free) data at the high sample frequency (e.g. daily) required to optimally control water systems. Against this background, SWE estimates from remote sensed radar products stand out, being able to acquire spatial information with no dependence on cloud coverage. In this work, we propose a technique for retrieving SWE estimates from Synthetic Aperture Radar (SAR) Cosmo SkyMed X-band images: a regression model, calibrated on ground SWE measurements, is implemented on dry snow maps obtained through a multi-temporal approach. The unprecedented spatial scale of this application is novel w.r.t. state of the art radar analysis conducted on limited spatial domains. The operational value of the SAR retrieved SWE estimates is evaluated based on ISA, a recently developed information selection and assessment framework. The method is demonstrated on a snow-rain fed river basin in the Italian Alps. Preliminary results show SAR images have a good potential for monitoring snow conditions and for improving water management operations.

  14. 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

  15. Bistatic Experiment Using TerraSAR-X and DLR’s new F-SAR System

    OpenAIRE

    Baumgartner, Stefan; Rodriguez-Cassolà, Marc; Nottensteiner, Anton; Horn, Ralf; Scheiber, Rolf; Steinbrecher, Ulrich; Metzig, Robert; Limbach, Markus; Mittermayer, Josef; Krieger, Gerhard; Moreira, Alberto; Schwerdt, Marco

    2008-01-01

    A bistatic X-band experiment was successfully performed early November 2007. TerraSAR-X was used as transmitter and DLR’s new airborne radar system F-SAR, which was programmed to acquire data in a quasi-continuous mode to avoid echo window synchronization issues, was used as bistatic receiver. Precise phase and time referencing between both systems, which is essential for obtaining high resolution SAR images, was derived during the bistatic processing. Hardware setup and performance analyses ...

  16. 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.

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    A. Taravat

    2013-09-01

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

  1. Medium Resolution SAR Image Time-series Built-up Area Extraction Based on Multilayer Neural Network

    Directory of Open Access Journals (Sweden)

    Du Kangning

    2016-09-01

    Full Text Available To improve the accuracy and stability of built-up area extraction from Synthetic Aperture Radar (SAR image time series, in this paper, we propose a multilayer neural-network-based built-up area extraction method that combines the characters of time-series images. The proposed method coarsely tags single images and obtains a large number of samples from time-series images that have been processed by a histogram specification procedure. To generate a training sample dataset, we use samples generated from one image to determine network depth and select samples with higher accuracy from the sample set taken from the timeseries images. The final model is trained by the selected large and high quality training dataset. We perform two comparison experiments with 38 25-m resolution ENVISAT ASAR images. Using the proposed method, we achieved 90.2% minima accuracy and a 0.725 minima Kappa coefficient, which are much higher than those of the three conventional methods. Thus, the accuracy and stability of built-up area extraction are significantly improved. In addition, the method proposed in this paper has the advantages of requiring minimal manual operation, well generalization, and training efficiency.

  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. A novel spaceborne SAR wide-swath imaging approach based on Poisson disk-like nonuniform sampling and compressive sensing

    Institute of Scientific and Technical Information of China (English)

    SUN JinPing; ZHANG YuXi; TIAN JiHua; WANG Jun

    2012-01-01

    Since the range swath width in the conventional single channel spaceborne synthetic aperture radar (SAR) is restricted by the system parameters,there is a trade-off between the azimuth resolution and the swath width in order to satisfy the Nyquist sampling criterion.In this paper,we propose a novel spaceborne SAR wide-swath imaging scheme based on compressive sensing (CS) for the sparse scene. The proposed method designs a Poisson disk-like nonuniform sampling pattern in the azimuth direction,which meets the demand of wider swath by restricting the smallest time interval between any two azimuth samples,with the conventional sampling pattern preserved in the range direction. By a similar way to the processing procedure of spectral analysis (SPECAN) algorithm,the linear range migration correction (RMC) is realized while carrying out range compression,which can meet the demand for focusing with middle level resolution.To reduce the computation load of CS reconstruction,we propose a novel fast reconstruction algorithm based on nonuniform fast Fourier transform (NUFFT),which greatly reduces the computation complexity from (O)(2MN) to (O)(4Nlog N).Experiment results validate the effectiveness of the proposed methods via the point target simulation and the Radarsat-1 raw data processing in F2 mode.

  4. Fault and anthropogenic processes in central California constrained by satellite and airborne InSAR and in-situ observations

    Science.gov (United States)

    Liu, Zhen; Lundgren, Paul

    2016-07-01

    The San Andreas Fault (SAF) system is the primary plate boundary in California, with the central SAF (CSAF) lying adjacent to the San Joaquin Valley (SJV), a vast structural trough that accounts for about one-sixth of the United Sates' irrigated land and one-fifth of its extracted groundwater. The CSAF displays a range of fault slip behavior with creeping in its central segment that decreases towards its northwest and southeast ends, where the fault transitions to being fully locked. At least six Mw ~6.0 events since 1857 have occurred near the Parkfield transition, most recently in 2004. Large earthquakes also occurred on secondary faults parallel to the SAF, the result of distributed deformation across the plate boundary zone. Recent studies have revealed the complex interaction between anthropogenic related groundwater depletion and the seismic activity on adjacent faults through stress interaction. Despite recent progress, many questions regarding fault and anthropogenic processes in the region still remain. For example, how is the relative plate motion accommodated between the CSAF and off-fault deformation? What is the distribution of fault creep and slip deficit at shallow depths? What are the spatiotemporal variations of fault slip? What are the spatiotemporal characteristics of anthropogenic and lithospheric processes and how do they interact with each other? To address these, we combine satellite InSAR and NASA airborne UAVSAR data to image on and off-fault deformation. The UAVSAR data cover fault perpendicular swaths imaged from opposing look directions and fault parallel swaths since 2009. The much finer spatial resolution and optimized viewing geometry provide important constraints on near fault deformation and fault slip at very shallow depth. We performed a synoptic InSAR time series analysis using ERS-1/2, Envisat, ALOS and UAVSAR interferograms. The combined C-band ERS-1/2 and Envisat data provide a long time interval of SAR data over the region

  5. Terrain Measurement with SAR/InSAR

    Science.gov (United States)

    Li, Deren; Liao, Mingsheng; Balz, Timo; Zhang, Lu; Yang, Tianliang

    2016-08-01

    Terrain measurement and surface motion estimation are the most important applications for commercial and scientific SAR missions. In Dragon-3, we worked on these applications, especially regarding DEM generation, surface motion estimation with SAR time- series for urban subsidence monitoring and landslide motion estimation, as well as developing tomographic SAR processing methods in urban areas.

  6. 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.

  7. 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.

  8. Image Processing Software

    Science.gov (United States)

    Bosio, M. A.

    1990-11-01

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

  9. 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 ...

  10. Image processing and products for the Magellan mission to Venus

    Science.gov (United States)

    Clark, Jerry; Alexander, Doug; Andres, Paul; Lewicki, Scott; Mcauley, Myche

    1992-01-01

    The Magellan mission to Venus is providing planetary scientists with massive amounts of new data about the surface geology of Venus. Digital image processing is an integral part of the ground data system that provides data products to the investigators. The mosaicking of synthetic aperture radar (SAR) image data from the spacecraft is being performed at JPL's Multimission Image Processing Laboratory (MIPL). MIPL hosts and supports the Image Data Processing Subsystem (IDPS), which was developed in a VAXcluster environment of hardware and software that includes optical disk jukeboxes and the TAE-VICAR (Transportable Applications Executive-Video Image Communication and Retrieval) system. The IDPS is being used by processing analysts of the Image Data Processing Team to produce the Magellan image data products. Various aspects of the image processing procedure are discussed.

  11. 基于CS的SAR图像自动目标分割算法%Automatic Target Segmentation in SAR Images Using CS

    Institute of Scientific and Technical Information of China (English)

    杨萌; 张弓

    2011-01-01

    Object segmentation is an important step in SAR super-resolution processing and automatic target recognition. Considering image inherent sparse structures, an automatic target segmentation algorithm is proposed in this paper. First, a transformation matrix of dictionary is constructed to project the SAR image into a high dimensional space, and a sparse representation set of image local features is achieved. Second, a random sampling matrix is used to obtain its compression sampling and a mean-shift algorithm is applied to parallel process multiple sets of sample data. Finally, by using the sign test method, the SAR images data are classified as target pixels and background pixels classification. Experimental results demonstrate that the proposed algorithm has a good target segmentation results for hard target in synthetic aperture radar (SAR) images.%图像目标分割是SAR图像目标超分辨处理和自动目标识别的重要步骤.针对图像固有的稀疏结构,提出了一种SAR图像自动目标分割算法.通过构造变换字典将SAR图像数据投影到高维空间,实现了图像局部特征的稀疏表示,然后利用随机矩阵获得稀疏域局部特征的压缩采样,并对多组采样数据运用Mean-shift算法并行处理,最后通过符号检验法,实现了对目标像素与背景像素的分类.试验表明,该算法对硬目标具有较好的目标分割性能.

  12. Medical image processing

    CERN Document Server

    Dougherty, Geoff

    2011-01-01

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

  13. 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.

  14. 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.

  15. Biomedical Image Processing

    CERN Document Server

    Deserno, Thomas Martin

    2011-01-01

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

  16. 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.

  17. 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.

  18. 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.

  19. 基于线性最小均方误差估计的 SAR 图像降噪%SAR image denoising via linear minimum meansquare error estimation

    Institute of Scientific and Technical Information of China (English)

    刘书君; 吴国庆; 张新征; 沈晓东; 李勇明

    2016-01-01

    针对合成孔径雷达(synthetic aperture radar,SAR)图像降噪过程中容易引起细节纹理信息损失的问题,该文结合 SAR 图像相干斑噪声的统计特性,提出了一种基于变换域系数线性最小均方误差(linear mini-mum mean-square error,LMMSE)估计的 SAR 图像降噪方法。首先通过 SAR 场景下的 Kmeans 聚类算法将相似图像块聚类;然后针对每一类相似图像块集合进行奇异值分解(singular value decomposition,SVD),得到同时包含图像块集合行列相关信息的含噪奇异值系数;为从含噪奇异值系数中更准确地估计出真实图像奇异值的系数,先通过加性独立信号噪声(additive signal-dependent noise,ASDN)模型将乘性噪声转化为加性噪声,再利用LMMSE 准则对奇异值系数进行估计,最后将估计结果重构得到降噪后的图像块集合。实验结果表明,该方法充分利用相似图像块集合奇异值系数稀疏的特性,采用 LMMSE 准则估计奇异值系数,既保证了系数中噪声分量的去除又避免了图像纹理细节对应小系数的丢失,不仅去噪效果明显,同时能有效地保持图像纹理细节,具有良好的图像视觉效果。%In order to solve the problem that many detail texture information is lost during the synthetic ap-erture radar (SAR)image denoising process,SAR image denoising approach based on the estimated transform domain coefficients by the means of linear minimum mean square error (LMMSE)is proposed,which combines the statistical characteristics of the speckle noise in the SAR image.Firstly,cluster image blocks into disjoint sets of similar blocks through Kmeans corresponding to the SAR scene.Secondly,perform singular value de-composition (SVD)for each set of similar blocks,and the noisy singular value coefficients containing the corre-lation of rows and columns of the set of similar blocks can be obtained.In order to estimate the noise

  20. Methods in Astronomical Image Processing

    Science.gov (United States)

    Jörsäter, S.

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

  1. 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

  2. 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

  3. Using SAR and GPS for Hazard Management and Response: Progress and Examples from the Advanced Rapid Imaging and Analysis (ARIA) Project

    Science.gov (United States)

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

    2014-12-01

    ARIA is a joint JPL/Caltech project to automate synthetic aperture radar (SAR) and GPS imaging capabilities for scientific understanding, hazard response, and societal benefit. We have built a prototype SAR and GPS data system that forms the foundation for hazard monitoring and response capability, as well as providing imaging capabilities important for science studies. Together, InSAR and GPS have the ability to capture surface deformation in high spatial and temporal resolution. For earthquakes, this deformation provides information that is complementary to seismic data on location, geometry and magnitude of earthquakes. Accurate location information is critical for understanding the regions affected by damaging shaking. Regular surface deformation measurements from SAR and GPS are useful for monitoring changes related to many processes that are important for hazard and resource management such as volcanic deformation, groundwater withdrawal, and landsliding. Observations of SAR coherence change have a demonstrated use for damage assessment for hazards such as earthquakes, tsunamis, hurricanes, and volcanic eruptions. These damage assessment maps can be made from imagery taken day or night and are not affected by clouds, making them valuable complements to optical imagery. The coherence change caused by the damage from hazards (building collapse, flooding, ash fall) is also detectable with intelligent algorithms, allowing for rapid generation of damage assessment maps over large areas at fine resolution, down to the spatial scale of single family homes. We will present the progress and results we have made on automating the analysis of SAR data for hazard monitoring and response using data from the Italian Space Agency's (ASI) COSMO-SkyMed constellation of X-band SAR satellites. Since the beginning of our project with ASI, our team has imaged deformation and coherence change caused by many natural hazard events around the world. We will present progress on our

  4. The image processing handbook

    CERN Document Server

    Russ, John C

    2006-01-01

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

  5. The Utility of SAR to Monitor Ocean Processes.

    Science.gov (United States)

    1981-11-01

    procedures should be followed to insure norma - lization in the digitization process? and (3) How would one use the derived relationship to infer wave... isI 1.43 cycles, the other 2 cycles long. The ratio of the frequencies is 1.4, which is closely approximated by the SCM spectrum. One of the

  6. Automated feature extraction by combining polarimetric SAR and object-based image analysis for monitoring of natural resource exploitation

    OpenAIRE

    Plank, Simon; Mager, Alexander; Schöpfer, Elisabeth

    2015-01-01

    An automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR) and an object-based post-classification is presented. High resolution SpotLight dual-polarimetric (HH/VV) TerraSAR-X imagery acquired over the Doba basin, Chad, is used for method development and validation. In an iterative training procedure the best suited polarimetric speckle filter, processing parameters for the following en...

  7. Image processing occupancy sensor

    Science.gov (United States)

    Brackney, Larry J.

    2016-09-27

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

  8. Ice Processes and Growth History on Arctic and Sub-Arctic Lakes Using ERS-1 SAR Data

    Science.gov (United States)

    Morris, K.; Jeffries, M. O.; Weeks, W. F.

    1995-01-01

    A survey of ice growth and decay processes on a selection of shallow and deep sub-Arctic and Arctic lakes was conducted using radiometrically calibrated ERS-1 SAR images. Time series of radar backscatter data were compiled for selected sites on the lakes during the period ot ice cover (September to June) for the years 1991-1992 and 1992-1993. A variety of lake-ice processes could be observed, and significant changes in backscatter occurred from the time of initial ice formation in autumn until the onset of the spring thaw. Backscatter also varied according to the location and depth of the lakes. The spatial and temporal changes in backscatter were most constant and predictable at the shallow lakes on the North Slope of Alaska. As a consequence, they represent the most promising sites for long-term monitoring and the detection of changes related to global warming and its effects on the polar regions.

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

    NARCIS (Netherlands)

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

    2003-01-01

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

  10. 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.

  11. 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.

  12. 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%.

  13. 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.

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

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

  16. 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.

  17. SAR processing with non-linear FM chirp waveforms.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2006-12-01

    Nonlinear FM (NLFM) waveforms offer a radar matched filter output with inherently low range sidelobes. This yields a 1-2 dB advantage in Signal-to-Noise Ratio over the output of a Linear FM (LFM) waveform with equivalent sidelobe filtering. This report presents details of processing NLFM waveforms in both range and Doppler dimensions, with special emphasis on compensating intra-pulse Doppler, often cited as a weakness of NLFM waveforms.

  18. 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.

  19. Quantum image processing?

    Science.gov (United States)

    Mastriani, Mario

    2017-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2006-09-01

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

  1. Image processing of 2D crystal images.

    Science.gov (United States)

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

    2013-01-01

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

  2. An Algorithm for Repeated Trajectory Bistatic Spotlight SAR Widefield Imaging%同航线双基聚束式SAR宽场景成像算法

    Institute of Scientific and Technical Information of China (English)

    张磊; 井伟; 邢孟道; 保铮

    2009-01-01

    该文在现有双基SAR成像研究的基础上,提出了同航线双基聚束式SAR成像的算法.该算法首先对回波信号进行方位预处理实现信号支撑区的不模糊,然后利用传统波数域的成像算法聚焦.该算法较双基极坐标算法有更高的聚焦精度并且没有几何形变.它不仅适用于平行航线的双基成像,其思路也完全适用于其它聚束模式的成像处理.最后通过仿真验证了算法的正确性.%Based on the current research on bistatic SAR image, a new algorithm to process data of repeated trajectory bistatic spotlight SAR system is proposed. The algorithm first suppress azimuth aliasing with an azimuth preprocess step, and focus image with traditional wavenumber domain algorithm. It is with high focusing accuracy without distortion involved, by which well focused image over large scene can be obtained. The principal of the azimuth preprocess is also suited to deal with other spotlight SAR mode. And a numeric simulation confirms the validity of the algorithm.

  3. 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.

  4. 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.

  5. 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....

  6. Collection and processing data for high quality CCD images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2007-03-01

    Coherent Change Detection (CCD) with Synthetic Aperture Radar (SAR) images is a technique whereby very subtle temporal changes can be discerned in a target scene. However, optimal performance requires carefully matching data collection geometries and adjusting the processing to compensate for imprecision in the collection geometries. Tolerances in the precision of the data collection are discussed, and anecdotal advice is presented for optimum CCD performance. Processing considerations are also discussed.

  7. 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

  8. 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.

  9. A learning tool for optical and microwave satellite image processing and analysis

    Science.gov (United States)

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

    2016-04-01

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

  10. Forest Height Inversion Using Dual-pol Polarimetric SAR Interferometry

    Science.gov (United States)

    Fu, W. X.; Guo, H. D.; Xie, C.; Lu, Y. C.; Li, X. W.

    2014-03-01

    Polarimetric Synthetic Aperture Radar Interferometry (PolInSAR) has been extensively applied for forest parameter inversion over different frequencies and polarimetric conditions. So far, most research was based on full-pol SAR images with relatively small coverage. A spaceborne SAR system will have the potential for PolInSAR applications used for global forest monitoring. Spaceborne dual-pol SAR images usually have higher resolution and larger swath than full-pol mode. In this paper, forest height retrieval was attempted by PolInSAR from a L-band spaceborne dual-pol SAR pairs using HH and HV channels. The random volume over ground (RVoG) model was used to retrieve the height and the coherence optimization method was extended to the dual-pol PolInSAR, which makes use of polarimetry to enhance the quality of SAR interferograms. The three-stage process is also used in the dual-pol PolInSAR technique. Finally, the experimental test was performed for forest height estimation on the dual-pol L-band SAR data of the Saihanba forest acquired by the ALOS PALSAR sensor in 2009.

  11. A Fast Back Projection Algorithm for Spotlight Mode Bi-SAR Imaging

    Directory of Open Access Journals (Sweden)

    Zhang Wen-bin

    2013-09-01

    Full Text Available A Fast Back Projection (FBP algorithm for spotlight mode Bistatic Synthetic Aperture Radar (Bi-SAR was presented. Sync channel signal from land receiver was taken as matched filter for echo signal in the phase of range compression, and the secondary phase calibration decreased the approximation error effects for FBP algorithm in the phase of azimuth compression. Computational complexity of this algorithm was O(N2.5 . In addition, this algorithm was validated on Graphic Processing Unit (GPU by simulation data and measured data.

  12. Image Processing for Teaching.

    Science.gov (United States)

    Greenberg, R.; And Others

    1993-01-01

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

  13. Image-Processing Program

    Science.gov (United States)

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

    1994-01-01

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

  14. 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.

  15. 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.

  16. Real-time optical processor prototype for remote SAR applications

    Science.gov (United States)

    Marchese, Linda; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Bourqui, Pascal; Legros, Mathieu; Desnoyers, Nichola; Guillot, Ludovic; Mercier, Luc; Savard, Maxime; Martel, Anne; Châteauneuf, François; Bergeron, Alain

    2009-09-01

    A Compact Real-Time Optical SAR Processor has been successfully developed and tested. SAR, or Synthetic Aperture Radar, is a powerful tool providing enhanced day and night imaging capabilities. SAR systems typically generate large amounts of information generally in the form of complex data that are difficult to compress. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Indeed, the first SAR images have been optically processed. The optical processor architecture provides inherent parallel computing capabilities that can be used advantageously for the SAR data processing. Onboard SAR image generation would provide local access to processed information paving the way for real-time decision-making. This could eventually benefit navigation strategy and instrument orientation decisions. Moreover, for interplanetary missions, onboard analysis of images could provide important feature identification clues and could help select the appropriate images to be transmitted to Earth, consequently helping bandwidth management. This could ultimately reduce the data throughput requirements and related transmission bandwidth. This paper reviews the design of a compact optical SAR processor prototype that would reduce power, weight, and size requirements and reviews the analysis of SAR image generation using the table-top optical processor. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and size are reviewed. Results of image generation from simulated point targets as well as real satellite-acquired raw data are presented.

  17. Geodetic Imaging of the Coseismic and Postseismic deformation from the 2015 Mw 7.8 Gorkha Earthquake and Mw 7.3 Aftershock in Nepal with SAR and GPS

    Science.gov (United States)

    Fielding, E. J.; Liang, C.; Agram, P. S.; Sangha, S. S.; Huang, M. H.; Samsonov, S. V.; Owen, S. E.; Moore, A. W.; Rodriguez-Gonzalez, F.; Minchew, B. M.

    2015-12-01

    The 25th of April 2015 Mw 7.8 Gorkha Earthquake in Nepal affected a large area of central Nepal and adjacent parts of India and Tibet. It was followed by a number of large aftershocks, with the largest so far an Mw 7.3 aftershock on the 12th of May 2015. We integrate geodetic measurements from Global Positioning System (GPS) data and synthetic aperture radar (SAR) satellite images to image the three-dimensional vector field of coseismic surface deformation for these two large events. We analyze SAR data from the Copernicus Sentinel-1A satellite operated by the European Space Agency; the RADARSAT-2 satellite operated by MacDonald, Dettwiler and Associates (MDA); and the Advanced Land Observation Satellite-2 (ALOS-2) satellite operated by the Japanese Aerospace Exploration Agency. We combine less precise analysis of large scale displacements from the SAR images of the three satellites by pixel offset tracking or sub-pixel correlation, including the along-track component of surface motion, with the more precise SAR interferometry (InSAR) measurements in the radar line-of-sight direction to estimate all three components of the surface displacement for the mainshock and large aftershock. A large area of central Nepal was pushed southward, due to thrust slip on the Main Himalayan Thrust (MHT) at depth extending about 170 km along-strike. The InSAR measurements show that there was no detectable slip on the shallower part of the MHT up-dip from the large coseismic slip or on other thrust faults in the Himalayas, except for one area of very shallow triggered slip of up to 5 cm on a thrust to the north of the Himalayan Frontal Thrust, during the two event. We also image postseismic deformation after these earthquakes with ongoing continuous GPS measurements and InSAR analysis of the SAR satellite data. Initial analysis of the GPS measurements indicates the most likely process in the first months is afterslip down-dip from the main coseismic slip. Large atmospheric effects in

  18. 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.

  19. Basics of Polar-Format algorithm for processing Synthetic Aperture Radar images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2012-05-01

    The purpose of this report is to provide a background to Synthetic Aperture Radar (SAR) image formation using the Polar Format (PFA) processing algorithm. This is meant to be an aid to those tasked to implement real-time image formation using the Polar Format processing algorithm.

  20. Hyperspectral image processing

    CERN Document Server

    Wang, Liguo

    2016-01-01

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

  1. 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

  2. Image processing techniques for acoustic images

    Science.gov (United States)

    Murphy, Brian P.

    1991-06-01

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

  3. 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

  4. Retinomorphic image processing.

    Science.gov (United States)

    Ghosh, Kuntal; Bhaumik, Kamales; Sarkar, Sandip

    2008-01-01

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

  5. 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.

  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. Recent advances and plans in processing and geocoding of SAR data at the DFD

    Science.gov (United States)

    Noack, W.

    1993-01-01

    Because of the needs of future projects like ENVISAT and the experiences made with the current operational ERS-1 facilities, a radical change in the synthetic aperture radar (SAR) processing scenarios can be predicted for the next years. At the German PAF several new developments were initialized which are driven mainly either by user needs or by system and operational constraints ('lessons learned'). At the end there will be a major simplification and uniformation of all used computer systems. Especially the following changes are likely to be implemented at the German PAF: transcription before archiving, processing of all standard products with high throughput directly at the receiving stations, processing of special 'high-valued' products at the PAF, usage of a single type of processor hardware, implementation of a large and fast on-line data archive, and improved and unified fast data network between the processing and archiving facilities. A short description of the current operational SAR facilities as well as the future implementations are given.

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

    Directory of Open Access Journals (Sweden)

    Balandeh Aminzadeh

    2010-11-01

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

  12. Automatic oil slick detection from SAR images: Results and improvements in the framework of the PRIMI pilot project

    Science.gov (United States)

    Trivero, Paolo; Adamo, Maria; Biamino, Walter; Borasi, Maria; Cavagnero, Marco; De Carolis, Giacomo; Di Matteo, Lorenza; Fontebasso, Fabio; Nirchio, Francesco; Tataranni, Francesco

    2016-11-01

    An automatic system capable of discriminating oil spills from other similar sea surface features in Synthetic Aperture Radar images has been developed and tested. This system, called Oil Spill Automatic Detector (OSAD), was originally conceived for C-band SAR images (mostly ERS PRI) and afterward adapted to ENVISAT data. In the framework of the Progetto pilota Rilevamento Inquinamento Marino da Idrocarburi (PRIMI) national project sponsored by the Italian Space Agency, the OSAD system has been greatly improved and is now able to process L- and X-band images from various satellites as well. OSAD performance, confirmed using a different dataset of verified slicks, shows an a priori overall correct classification of 80%. Moreover, new features have been added, such as an enhanced land masking algorithm, a built-in wind and wave extraction module, and oil spill characterization. OSAD has been integrated into a complex hardware and software architecture for operational sea monitoring, alarm generation, and oil slick drift forecasting. The system's detection capabilities have been validated during a measurement campaign in the Mediterranean Sea. The new improved system is described herein, with special attention to latest enhancements.

  13. Measuring the Coseismic Displacements of 2010 Ms7.1 Yushu Earthquake by Using SAR and High Resolution Optical Satellite Images

    Science.gov (United States)

    Zhang, L.; Wu, J.; Shi, F.

    2017-09-01

    After the 2010, Mw7.1, Yushu earthquake, many researchers have conducted detail investigations of the surface rupture zone by optical image interpretation, field surveying and inversion of seismic waves. However, how larger of the crustal deformation area caused by the earthquake and the quantitative co-seismic displacements are still not available. In this paper, we first take advantage of D-InSAR, MAI, and optical image matching methods to determine the whole co-seismic displacement fields. Two PALSAR images and two SPOT5 images before and after the earthquake are processed and the co-seismic displacements at the surface rupture zone and far field are obtained. The results are consistent with the field investigations, which illustrates the rationality of the application of optical image matching technology in the earthquake.

  14. 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.

  15. Design of a 12-bit 2 MS/s 12 mW pipelined SAR ADC in CMOS 0.18 μm technology for CZT-based imaging system

    Science.gov (United States)

    Xue, F.; Gao, W.; Wei, X.; Liu, W.; Hu, Y.

    2016-12-01

    This paper presents a 12-bit 2 MS/s pipelined successive approximation register (SAR) ADC for CZT-based imaging system. The proposed ADC is divided into a first-stage 6-bit SAR-based Multiplying Digital Analog Converter (MDAC) and a second-stage 8-bit SAR ADC. The first-stage MDAC has a gain of 16 instead of the usual gain of 64, which considerably minimizes the power dissipation of residue amplifier. The second-stage 8-bit SAR ADC employs unit bridge capacitor split-capacitor architecture aiming to reduce the load capacitance of residue amplifier so as to minimize the power dissipation of the proposed ADC. Moreover, a code-randomized calibration algorithm is proposed to improve the linearity of the second-stage 8-bit split-capacitor SAR ADC. In addition, several radiation-hardened-by-design techniques are adopted in the layout design against space radiation effects. The prototype chip was fabricated in 0.18 μ m mixed-signal 1.8 V/3.3 V process and occupied a core area of 0.71 mm2. The proposed pipelined SAR ADC achieves a peak signal-to-noise-and-distortion ratio (SNDR) of 63.2 dB at 2 MS/s sampling rate and consumes 12 mW power in total. The figure of merit (FoM) of the proposed ADC is 5.06 pJ/conversion-step.

  16. 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.

  17. IMAGE ENHANCEMENT USING IMAGE FUSION AND IMAGE PROCESSING TECHNIQUES

    OpenAIRE

    Arjun Nelikanti

    2015-01-01

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

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

    Science.gov (United States)

    Xu, Jia; Huang, Zuzhen; Yan, Liang; Zhou, Xu; Zhang, Furu; Long, Teng

    2016-10-12

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

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

    Directory of Open Access Journals (Sweden)

    Jia Xu

    2016-10-01

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

  20. Digital processing considerations for extraction of ocean wave image spectra from raw synthetic aperture radar data

    Science.gov (United States)

    Lahaie, I. J.; Dias, A. R.; Darling, G. D.

    1984-01-01

    The digital processing requirements of several algorithms for extracting the spectrum of a detected synthetic aperture radar (SAR) image from the raw SAR data are described and compared. The most efficient algorithms for image spectrum extraction from raw SAR data appear to be those containing an intermediate image formation step. It is shown that a recently developed compact formulation of the image spectrum in terms of the raw data is computationally inefficient when evaluated directly, in comparison with the classical method where matched-filter image formation is an intermediate result. It is also shown that a proposed indirect procedure for digitally implementing the same compact formulation is somewhat more efficient than the classical matched-filtering approach. However, this indirect procedure includes the image formation process as part of the total algorithm. Indeed, the computational savings afforded by the indirect implementation are identical to those obtained in SAR image formation processing when the matched-filtering algorithm is replaced by the well-known 'dechirp-Fourier transform' technique. Furthermore, corrections to account for slant-to-ground range conversion, spherical earth, etc., are often best implemented in the image domain, making intermediate image formation a valuable processing feature.

  1. 一种基于局部窗口的SAR图像目标检测算法%Algorithm for SAR image target detection based on local window

    Institute of Scientific and Technical Information of China (English)

    梅磊

    2015-01-01

    In terms of the requirements of the target detection accuracy, real-time and robustness for synthetic aperture radar (SAR) , this paper designs an algorithm for SAR image target detection based on local window. On the basis of conducting the denoising and segmentation processing to the acquired SAR image, this algorithm implements the strategy of fast registration for sub-pixel accuracy, based on SIFT. Meanwhile, it also achieves the target detection by the feature description results of SIFT lowering the dimension, and based on the expectation maximization algorithm of local window. Experimental results show that this algorithm has a better adaptation to the complex background and illumination along with rotation change, achieving an ideal effect of target detection.%针对合成孔径雷达(SAR)目标检测精确性、实时性和鲁棒性的要求,设计了一种基于局部窗口的SAR图像目标检测算法。该算法在对获取的SAR图像进行去噪和分割处理的基础上,基于尺度不变特征变换(SIFT)实现了亚像素精度快速配准策略;同时,通过SIFT特征的描述结果降维和基于局部窗口的最大期望算法(EM)实现了目标检测。实验结果表明,该算法对复杂背景和光照、旋转变化有较强的自适应性,获得了理想的目标检测效果。

  2. ISAR Echoes Coherent Processing and Imaging

    Institute of Scientific and Technical Information of China (English)

    XINGMengdao; LANJinqiao; BAOZheng; LIAOGuisheng

    2004-01-01

    The general approach to ISAR imaging is Range-doppler (RD) imaging approach. For this approach,the Translational motion compensation (TMC) is firstly obtained by envelope alignment and autofocus, so the target can be treated as a rotating target for the next processing. But in this method, scatterers' Migration through resolution cells (MTRC) caused by rotational motion is neglected. However in practice, MTRC exists with the improvement of resolution or for big target. For MTRC compensation, the keystone transformation in SAR is used inthis paper. Before the keystone transformation, it is demanded that the rawdata is coherent, while in fact, the ISAR rawdata is usually not. So a coherent processing of rawdata is proposed. In this paper, the coherent processing of rawdata is firstly done and the next step is to correct MTRC. After using multi-component Amplitude modulation and Linear frequency modulation (AM-LFM) parameter estimation method, the Range-Instantaneous Doppler(RID) ISAR image is obtained. The effectiveness of this algorithm is validated by the processing of simulation data.

  3. 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.

  4. scikit-image: image processing in Python.

    Science.gov (United States)

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

    2014-01-01

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

  5. scikit-image: image processing in Python

    Directory of Open Access Journals (Sweden)

    Stéfan van der Walt

    2014-06-01

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

  6. An Imaging Method of MIMO-SAR with Compressed Echo Data%基于回波数据压缩的MIMO-SAR成像方法

    Institute of Scientific and Technical Information of China (English)

    谢矿生

    2015-01-01

    The amount of echo data is huge in multiple input multiple output synthetic aperture radar( MI-MO-SAR) imaging with high resolution. To solve this problem,an imaging method of MIMO-SAR based on compressed echo data is proposed. Firstly,the echo signal model of MIMO-SAR system is analyzed and the phase error induced by MIMO radar is compensated. Secondly,the echo signal is preprocessed by the Range Migration Algorithm( RMA) ,and also the sparsity of the processed data is analyzed. Then the pre-processed data is compressed and transmitted. In the ground receiver,the sparse expression of echo data in Range-Doppler( RD) domain is reconstructed. Finally,the simulation result shows that the amount of the transmitted data by the proposed method is less than that by the conventional MIMO-SAR imaging method.%针对多发多收合成孔径雷达( MIMO-SAR)高分辨成像的回波数据量过大问题,提出了一种基于数据压缩的MIMO-SAR成像方法。通过对MIMO-SAR回波数据的分析,补偿了由于MIMO雷达收发分置导致的相位误差;其次利用距离徙动算法( RMA)对回波数据进行预处理并分析了其稀疏性;然后针对预处理后的回波数据进行压缩传输,在接收端利用压缩感知重构算法获得回波数据在距离多普勒域的稀疏表示并进行成像处理。仿真结果表明,所提方法可以在大幅压缩MIMO-SAR回波数据的基础上实现准确成像。

  7. 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.

  8. Wavefront curvature limitations and compensation to polar format processing for synthetic aperture radar images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2006-01-01

    Limitations on focused scene size for the Polar Format Algorithm (PFA) for Synthetic Aperture Radar (SAR) image formation are derived. A post processing filtering technique for compensating the spatially variant blurring in the image is examined. Modifications to this technique to enhance its robustness are proposed.

  9. DIGITAL IMAGES PROCESSING IN RADIOGRAPHY

    OpenAIRE

    Pilař, Martin

    2010-01-01

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

  10. 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.

  11. 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.

  12. Bistatic SAR: State of the Art and Development Trend

    Directory of Open Access Journals (Sweden)

    Zeng Tao

    2012-12-01

    Full Text Available Bistatic SAR (BiSAR systems have attracted the interests from global researchers and become a hotspot in the international radar community due to the progress of radar technology and rapidly increased applications nowadays. Based on the BiSAR experiments and breakthrough of the key technology, the paper summarized the general progresses of BiSAR systems, especially in European radar community, from different aspects such as system design, processing idea and topology etc. Different bistatic image formation algorithms have been analyzed and reviewed. Finally, the development trend is discussed in the paper.

  13. Smart Image Enhancement Process

    Science.gov (United States)

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

    2012-01-01

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

  14. Image processing and recognition for biological images.

    Science.gov (United States)

    Uchida, Seiichi

    2013-05-01

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

  15. Polar format algorithm for airborne bistatic SAR imaging%机载平行等速双基SAR的极坐标格式成像算法

    Institute of Scientific and Technical Information of China (English)

    熊涛; 周鹏; 邢孟道

    2012-01-01

    The bistatic synthetic aperture radar (SAR) refers to the SAR system whose transmitter and receiver work in a same orientation and equal velocity. It is called the azimuth-invariant bistatic synthetic aperture radar (SAR). The polar format algorithm (PFA) suitable for single base SAR imaging was improved to make it applied to the bistatic SAR imaging. Because the transmitter and receiver of the system are mounted in two different places, the slope-distance geometrical relation of the echo signal on the transmitting and receiving planes is complicated For the subsequent 2-D interpolation operation, a new geometrical model was established to describe the slope-distance relation on the transmitting and receiving planes. The new algorithm is easy as the conventional PFA to operate and implemente. The proposed approach was verified by the imaging processing of the simulation data.%平行等速双基SAR是指收发平台速度大小和方向均相同的双基SAR系统,该构型具有广阔的应用前景.在此将传统适用于单基地SAR成像的极坐标格式算法(PFA)加以改进,使之适用于平行等速双基SAR成像处理.由于收发异置,回波信号在接收平面和发射平面的斜距几何关系比较复杂.为了便于后续的二维插值操作,用一个新的几何模型来描述收发平面上斜距的关系.该算法具有传统PFA算法的操作简单,易于实现的特点.最后通过仿真数据的成像处理对该方法进行了验证.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Image processing with ImageJ

    CERN Document Server

    Pascau, Javier

    2013-01-01

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

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Fundamentals of electronic image processing

    CERN Document Server

    Weeks, Arthur R

    1996-01-01

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

  8. 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.

  9. Repeat-pass InSAR processing for Vegetation Height Calculation: Theory and a validated example

    Science.gov (United States)

    Siqueira, P.; Lei, Y.

    2014-12-01

    Knowledge of the vegetation height for a forested region is often used as a proxy for stem volume, biomass, and for characterizing habitats of a variety of plant and animal species. For this reason, remote sensing measures available from stereography, lidar, and InSAR have been important tools for airborne and spaceborne platforms. Among these and other candidates for measuring vegetation heights, InSAR has the advantage of achieving wide coverage areas (on the order of 100 km in cross-track swath) over short time periods, thus making it practical for large-scale assessments of the global environment. The determination of forest stand height (FSH), which is an assessment made on the order of one to ten hectares of resolution, InSAR can provide measures that are proportional to FSH. These are: 1.) interferometric phase compared to a known DEM, preferably of the bald earth, 2.) interferometric correlation (polarimetric or otherwise), which is related to the volume scattering nature of the target, and 3.) interferometric correlation which is related to the temporal decorrelation of the target. Of these, while the volumetric aspect of interferometric correlation is of keen interest, because of the dominant error source of temporal decorrelation, it comes at the cost of the need to perform single-pass interferometry. While such satellite systems do exist (notably the TanDEM-X mission), for vegetation applications, lower frequency systems such as ALOS-1 and -2, and the future NASA radar mission at L-band, provides better signal returns from throughout the vegetation canopy. Hence, rather than relying on volumetric correlation to provide the desired FSH signature, repeat-pass observations of temporal decorrelation are coupled with a vegetation model for this decorrelation to determine the vegetation height. In order to demonstrate this technique, the University of Massachusetts has used 46-day repeat-pass ALOS data to estimate FSH over the US State of Maine, nearly a 10

  10. New perspectives and advanced approaches on effectively processing Big InSAR data: from long term ERS archives to new Sentinel-1 massive data flow

    Science.gov (United States)

    Casu, Francesco; De Luca, Claudio; Elefante, Stefano; Lanari, Riccardo; Manunta, Michele; Zinno, Ivana

    2015-04-01

    Advanced differential Synthetic Aperture Radar (SAR) Interferometry (InSAR) usually identifies a set of algorithms, tools and methodologies for the generation of Earth's surface deformation maps and time series computed from a sequence of multi-temporal differential SAR interferograms. Such techniques found their success on the large availability of SAR data archives acquired over time by several satellite systems. Indeed, the current radar Earth Observation (EO) scenario takes advantage of the widely diffused long-term C-band ESA (e.g. ERS-1, ERS-2 and ENVISAT) and Canadian (RADARSAT-1/2) SAR data archives, which have been acquired during the last 20 years, as well as of data sequences provided by the X-band generation SAR sensors, such as the COSMO-SkyMed (CSK) and TerraSAR-X (TSX) constellations. Moreover, a massive and ever increasing data flow will be further supplied by the recently launched (April 2014) Copernicus (European Union) SENTINEL-1A SAR satellite, which will also be paired during 2016 with the SENTINEL-1B twin system that will allow halving the constellation revisit time (from 12 to 6 days). In this context, the massive exploitation of these Big InSAR Data archives for the generation of advanced products will open new research perspectives to understand Earth's surface deformation dynamics at global scale. However, to reach this ambitious goal, Big InSAR Data has to be effectively exploited to generate accurate advanced products in short time frames. Therefore the need of new InSAR processing approaches, efficient algorithms and high performance computing facilities represents the basis for fully benefiting from such a Big Data. In this work we first present the recently proposed Parallel Small BAseline Subset (P-SBAS) InSAR algorithm that has been designed to process big volumes of InSAR data in short times and unsupervised manner by exploiting High Performance Computing (HPC) facilities. Then, we show how the P-SBAS approach is well suitable for

  11. 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.

  12. 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.

  13. SArEM: A SPEM extension for software architecture extraction process

    Directory of Open Access Journals (Sweden)

    Mira Abboud

    2016-04-01

    Full Text Available In order to maintain a system, it’s critical to understand its architecture. However even though every system has an architecture, not every system has a reliable representation of its architecture. To deal with this problem many researchers have engaged in software architecture extraction where the system’s architecture is recovered from its source code. While there is a plethora of approaches aiming at extracting software architectures, there is no mean or tool measurement for these approaches; which makes the comparison between the different approaches a hard task. To tackle this lack, we developed a meta-model, based on SPEM meta-model, that specifies the software architecture extraction process. Such meta-model serves as a tool to compare, analyze and evaluate research field approaches. In this paper we detail our meta-model called SArEM (Software Architecture Extraction Meta-model and clarify its concepts.

  14. 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

  15. An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

    Directory of Open Access Journals (Sweden)

    Xiangguang Leng

    2016-08-01

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

  16. 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.

  17. Eye Redness Image Processing Techniques

    Science.gov (United States)

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

    2017-09-01

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

  18. 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.

  19. SAR Altimetry Processing on Demand Service for Cryosat-2 and Sentinel-3 at ESA G-Pod

    Science.gov (United States)

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

    2016-07-01

    The G-POD SARvatore service to users for the exploitation of CryoSat-2 data was designed and developed by the Altimetry Team at ESA-ESRIN EOP-SER (Earth Observation - Exploitation, Research and Development). The G-POD service coined SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research & Exploitation) is a web platform that allows any scientist to process on-line, on-demand and with user-selectable configuration CryoSat-2 SAR/SARIN data, from L1a (FBR) data products up to SAR/SARin Level-2 geophysical data products. The Processor takes advantage of the G-POD (Grid Processing On Demand) distributed computing platform (350 CPUs in ~70 Working Nodes) to timely deliver output data products and to interface with ESA-ESRIN FBR data archive (155'000 SAR passes and 41'000 SARin passes). The output data products are generated in standard NetCDF format (using CF Convention), therefore being compatible with the Multi-Mission Radar Altimetry Toolbox (BRAT) and other NetCDF tools. By using the G-POD graphical interface, it is straightforward to select a geographical area of interest within the time-frame related to the Cryosat-2 SAR/SARin FBR data products availability in the service catalogue. The processor prototype is versatile, allowing users to customize and to adapt the processing according to their specific requirements by setting a list of configurable options. After the task submission, users can follow, in real time, the status of the processing, which can be lengthy due to the required intense number-crunching inherent to SAR processing. From the web interface, users can choose to generate experimental SAR data products as stack data and RIP (Range Integrated Power) waveforms. The processing service, initially developed to support the awarded development contracts by confronting the deliverables to ESA's prototype, is now made available to the worldwide SAR Altimetry Community for research & development experiments, for on-site demonstrations/training in

  20. 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