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In this paper, a multiscale Markov random field method for segmentation of the synthetic aperture radar (SAR) images is proposed. A classifier which inherits the strongpoint of the Markov random field (MRF) and the multiscale autoregressive (MAR) model is designed. The MAR models are utilized to extract the multiscale feature of SAR image, which is used to train the MRF with the proposed algorithm,...
This paper presents efficient non-parameter and multiscale approach to segmentation of natural clutter in synthetic aperture radar (SAR) imagery. The method we propose not only exploit the coherent nature of SAR sensor, and take of advantage of the characteristic statistical difference in imagery of different terrain types, but also do not require distribution of pixels due to using bootstrap method...
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