PROJECT TITLE :
Separated Component Based Restoration of Speckled SAR Images - 2014
Several coherent imaging modalities like artificial aperture radar suffer from a multiplicative noise, commonly known as speckle, which typically makes the interpretation of information tough. An effective strategy for speckle reduction is to use a dictionary that may sparsely represent the options within the speckled image. However, such approaches fail to capture necessary salient features like texture. During this paper, we tend to present a speckle reduction algorithm that handles this issue by formulating the restoration problem therefore that the structure and texture parts can be separately estimated with different dictionaries. To solve this formulation, an iterative algorithm based on surrogate functionals is proposed. Experiments indicate the proposed methodology performs favorably compared to state-of-the-art speckle reduction methods.
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