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Bistatic Synthetic Aperture Radar Point Spread Function Characteristic Analysis
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作者 胡程 曾涛 曾海彬 《Journal of Beijing Institute of Technology》 EI CAS 2007年第2期193-196,共4页
Based on the point spread function (PSF) theory, the side-lobe extension direction of the impulse response in bistatic synthetic aperture radar (BSAR) is analyzed in detail; in addition, the corresponding autofocu... Based on the point spread function (PSF) theory, the side-lobe extension direction of the impulse response in bistatic synthetic aperture radar (BSAR) is analyzed in detail; in addition, the corresponding autofocus in BSAR should be considered along iso-range direction, not the traditional azimuth resolution (AR) direction. The conclusion is verified by the computer simulation. 展开更多
关键词 bistatic synthetic aperture rader (BSAR) point spread function (PSF) range resolution (RR) azimuth resolution (AR) iso-range iso-Doppler
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Coherence-coefficient-based Markov random field approach for building segmentation from high-resolution SAR images 被引量:3
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作者 QIAN Qian WANG Bing-nan +2 位作者 XIANG Mao-sheng FU Xi-kai JIANG Shuai 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2019年第3期226-235,共10页
Building segmentation from high-resolution synthetic aperture radar (SAR) images has always been one of the important research issues. Due to the existence of speckle noise and multipath effect, the pixel values chang... Building segmentation from high-resolution synthetic aperture radar (SAR) images has always been one of the important research issues. Due to the existence of speckle noise and multipath effect, the pixel values change drastically, causing the large intensity differences in pixels of building areas. Moreover, the geometric structure of buildings can cause strong scattering spots, which brings difficulties to the segmentation and extraction of buildings. To solve of these problems, this paper presents a coherence-coefficient-based Markov random field (CCMRF) approach for building segmentation from high-resolution SAR images. The method introduces the coherence coefficient of interferometric synthetic aperture radar (InSAR) into the neighborhood energy based on traditional Markov random field (MRF), which makes interferometric and spatial contextual information more fully used in SAR image segmentation. According to the Hammersley-Clifford theorem, the problem of maximum a posteriori (MAP) for image segmentation is transformed into the solution of minimizing the sum of likelihood energy and neighborhood energy. Finally, the iterative condition model (ICM) is used to find the optimal solution. The experimental results demonstrate that the proposed method can segment SAR building effectively and obtain more accurate results than the traditional MRF method and K-means clustering. 展开更多
关键词 building segmentation high-resolution synthetic aperture rader (SAR) image Markov random field (MRF) coherence coefficient
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