Segmentation of multi-look fully polarimetric SAR images based on Wishart distribution and MRF

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作者
School of Electronics Science and Engineering, National University of Defense Technology, Changsha 410073, China [1 ]
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Tien Tzu Hsueh Pao | 2007年 / 12卷 / 2302-2306期
关键词
Algorithms - Covariance matrix - Estimation - Image segmentation - Markov processes - Mathematical models - Maximum likelihood - Pixels - Polarimeters - Probability distributions - Sensors;
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摘要
A novel method is proposed for segmenting multi-look fully polarimetric SAR images. The Wishart distribution of the covariance matrix is integrated with the Markov random field model, and then the iterative conditional modes (ICM) algorithm is taken to implement the maximum a posteriori estimation of pixel labels. The initial segmentation map for ICM is obtained using the Wishart-based ML. Using multi-look fully polarimetric SAR images, acquired by the NASA/JPL AIRSAR sensor, the new approach is compared with several other common ones, higher accuracy are observed, as well as less isolated pixels and better connectivity.
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