A Statistical Texture Feature for Building Collapse Information Extraction of Sar Image

Abstract

ABSTRACT:Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G 0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual-or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

Performance Analysis of Optical Flow Techniques for Airborne SAR Image Registration

“…Coherence is a standard measure in SAR to evaluate the quality of registration [19]. It is evaluated on complex resampled images.…”

“…NCC can be applied to complex valued SAR images or to real-valued amplitude images [18]. In case of good SNR, the phase information can be helpful for registration, however in case of low SNR it is usually leading to more noisy results [18], [19]. Since our application scenario, Sect.…”

Joint Exploitation of Coherent Change Detection and Global-Context Capturing Network for Subtle Changed Track Detection With Airborne SAR

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