期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 7, 期 1, 页码 63-67出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2009.2024011
关键词
Bayesian inference; regularization methods; speckle reduction; synthetic aperture radar (SAR)
This letter presents the despeckling of single-look complex (SLC) synthetic aperture radar (SAR) images using non-quadratic regularization. The objective function consists of an image model, a gradient, and a prior model. The Huber-Markov random field (HMRF) models the prior. A numerical solution is achieved through extensions of half-quadratic regularization methods using complex-valued SAR data. The proposed method using the HMRF prior together with nonquadratic regularization shows the superior results on SLC synthetic and actual SAR images.
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