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Huber–Markov Model for Complex SAR Image Restoration

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3 Author(s)
Soccorsi, M. ; Inst. fur Methodik der Fernerkundung, Deutsches Zentrum fur Luftund Raumfahrt (DLR), Wessling, Germany ; Gleich, D. ; Datcu, M.

This letter presents the despeckling of single-look complex (SLC) synthetic aperture radar (SAR) images using nonquadratic 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.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:7 ,  Issue: 1 )