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Proceedings Paper

Modeling amplitude SAR image with the Cauchy-Rayleigh mixture
Author(s): Qiangqiang Peng; Qingyu Du; Yinwei Yao; Huang Huang
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Paper Abstract

In this paper, we introduce a novel mixture model of the SAR amplitude image, which is proposed as an approximation to the heavy-tailed Rayleigh model. The limitation of the heavy-tailed Rayleigh model in SAR image application is discussed. We also present an expectation-maximization (EM) algorithm based parameter estimation method for the Cauchy-Rayleigh mixture. We test the new model on some simulated data in order to confirm that is appropriate to the heavy-tailed Rayleigh model. The performance is evaluated by some statistic values (cumulative square errors (CSE) < 0.013, correlation coefficient (CC) > 0.99 and Kolmogorov-Smirnov distance (K-S) < 0.03). Finally, the performance of the proposed mixture model is tested on some real SAR images and compared with other models, including the heavy-tailed Rayleigh and Nakagami mixture models. The result indicates that the proposed model can be an optional statistical model for amplitude SAR images.

Paper Details

Date Published: 24 October 2017
PDF: 7 pages
Proc. SPIE 10463, AOPC 2017: Space Optics and Earth Imaging and Space Navigation, 104630J (24 October 2017); doi: 10.1117/12.2282781
Show Author Affiliations
Qiangqiang Peng, Beijing Aerospace Automatic Control Institute (China)
Qingyu Du, Beijing Aerospace Automatic Control Institute (China)
Yinwei Yao, Beijing Aerospace Automatic Control Institute (China)
Huang Huang, Beijing Materials Handling Research Institute (China)


Published in SPIE Proceedings Vol. 10463:
AOPC 2017: Space Optics and Earth Imaging and Space Navigation
Carl Nardell; Suijian Xue; Huaidong Yang, Editor(s)

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