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Modern high resolution satellite SAR sensors even allow analysis of building sub-structures like windows and balconies. In the amplitude data man-made objects usually appear either as salient bright lines or points embedded within dark background. The latter features may coincide also with so-called persistent scatterers (PS), whose phase history is exploited by time series analysis for 3D reconstruction...
Presents a new method for segmentation of synthetic aperture radar (SAR) images. A Gaussian autoregressive (GAR) model under a multiresolution pairwise Markov framework can be proposed based on texture feature fusion images from in part gray level co-occurrence probability statistics, we examine the texture segmentation of SAR image suing the multi-resolution maximization of the posterior marginal...
This paper describes detection and interpretation of temporal changes in an area of interest using coherent change detection in repeat-pass Synthetic Aperture Radar imagery, with the main goal of detecting subtle scene changes such as potential human activities. Possibilities of introducing knowledge sources in order to improve the final result are also presented.
One of the major stakeholders of image fusion is being able to process the most complex images at the finest possible integration level and with the most reliable accuracy. The use of support vector machine (SVM) fusion for the classification of multisensors images representing a complex tropical ecosystem is investigated. First, SVM are trained individually on a set of complementary sources: multispectral,...
In this paper, we present a Ground moving target indication (GMTI) method based on the analysis of the two phase difference maps (PDM) of the same target scene obtained by one antenna phase center on a slow moving platform. For small unmanned aerial vehicles (UAVs) only one antenna is available to detect moving targets. Using a single antenna and the two PDMs method, odd numbered spatial samples are...
Forward-Looking Ground Penetrating Synthetic Aperture Radar (FLGPSAR) has the capability of forming two-dimensional high-resolution images of subsurface objects from a standoff distance. This paper addresses the detection of subsurface targets, i.e. landmines, in FLGPSAR images. The conventional Constant False-Alarm Rate (CFAR) algorithm has been widely used in SAR image target detection, but its...
Fuzzy clustering algorithms have been successfully applied to POLSAR classification, but not to POLInSAR. In this paper, a Fuzzy C Means (FCM) clustering algorithm integrating the complementary physical information and statistical property contained in both polarimetric and interferometric data, is used for POLInSAR classification. At first, the area dominated by volume scattering is extracted from...
Recent years, the application of multi-baseline DInSAR was primarily possible in the case of slow ground movements. In this paper, the application of Beijing-Tianjin intercity railway roadbed deformation monitoring based on multi-baselines DInSAR is present. To enable this, the advanced network algorithm is adapted for pixels linking. Our study is based on 15 ALOS PALSAR images during one-year period...
The goal of this work is the generation of an X-Band backscatter map by assembling images acquired by the TerraSAR-X mission. Global backscatter data is required for accurate performance estimation and instrument commanding inside the TerraSAR-X and TanDEM-X missions. Moreover, many scientific applications can be based on the analysis of backscatter behavior and evolution. The complete ground coverage...
Automated segmentation routines may be used to extract scattering features in synthetic aperture radar (SAR) images. The watershed transform segments real-valued images into regions associated with a local minima. Watershed algorithms suffer from over-segmentation which, for SAR image segmentation, results in many more regions than scatterers. We consider an algorithm called Peak Region Segmentation...
Modern SAR systems have high resolution which leads the backscattering clutter to be non-Gaussian. In order to properly classify images from these systems, a non-Gaussian noise model is considered: the SIRV model. A statistical test of equality of covariance matrices is used to classify pixels, taking into account the critical region of the test which rejects the likeliness of a covariance matrix...
For remote sensing data, the testing analysis tools is difficult since the ground-truth data are not available in many cases. To address this issue, a novel method for image synthesis is presented for use as a evaluation test-bed. Given the scale-dependent, non-stationary nature of remotely sensed data, a new modeling approach that combines a resolution-oriented hierarchical method with a regional...
We develop a new SAR processor based on oblique projection. We take into account the scattering properties of the target and the interferences by using subspace models. To detect the target and to reject the interferences, we process images with the oblique projection of the received signal into the target subspace along the interference one. This new SAR processor is applied to realistic simulated...
Image segmentation and unsupervised classification are difficult problems. We propose to combine both. A clustering process is applied over segment mean values. Only large segments are considered. The clustering is composed of a mean-shift step and a hierarchical clustering step. The hierarchical grouping is based upon a powerful segmentation technique previously developed. The approach is applied...
Recently, non-local approaches have proved very powerful for image denoising. Unlike local filters, the non-local (NL) means introduced in decrease the noise while preserving well the resolution. In the proposed paper, we suggest the use of a non-local approach to estimate single-look SAR reflectivity images or to construct SAR interferograms. SAR interferogram construction refers to the joint estimation...
We perform a full exploitation of the Differential SAR Interferometry (DInSAR) algorithm referred to as Small BAseline Subset (SBAS) technique to investigate long term surface deformation occurring in extended, seismogenetic areas. To this aim we benefit of the SBAS technique capability to work in multi-frame and multi-sensor scenarios in order to improve the spatial and temporal coverage, as well...
This paper presents an analysis of the performance of TerraSAR-X for subsidence monitoring in urban areas. The city of Murcia has been selected as a test-site due to its high deformation rate and the set of extensometers deployed along the city that provide validation data. The obtained results have been compared with those obtained from ERS/ENVISAT data belonging to the same period and validated...
Information mining from heavy SAR images is considered from the point of view of the procedure automatization. Two schemes based on Neural Networks are evaluated, one based on the Self Organizing Map method exploiting polarimetric information and oriented to land cover classification, the other based on the Pulse-Coupled Neural Networks aiming at characterizing the imaged buildings.
We develop a new SAR processor based on several orthogonal projections.We take into account the scattering properties of the target and the interferences by using subspace models. To detect the target without detecting the interferences, we process images from the orthogonal projection of the received signal into the target subspace and from the orthogonal projection of the received signal into a...
This paper is about evaluating the interest between studying directs dual images statistical indices and the use of statistical indices build from two SAR multipolarization images. We show an original way of using this kind of images by using two dimensionned statistical calculation in a Markov random field classification. We present results of our segmentation on urban, forest and mangrove areas...
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