PROJECT TITLE :

Scattering-Based Nonlocal Means SAR Despeckling

ABSTRACT:

Speckle noise greatly limits each artificial aperture radar (SAR) data human readability, especially for non-SAR-professional users, and performance of automatic processing and data retrieval procedures by computer programs. So, despeckling of SAR images is a vital preprocessing step in SAR information analysis, processing, and modeling, also in data retrieval and inversion procedures. Up to now, one of the most accurate and promising despeckling approaches—among those based on one SAR image—is that the one wishing on the nonlocal means ideas. But, at the most effective of our knowledge, most of the cutting-edge considers the despeckling drawback only within a statistical framework, completely discarding the electromagnetic phenomena behind SAR imagery formation. In this paper, we have a tendency to introduce the novel plan of a physical-based despeckling, taking into account meaningful physical characteristics of the imaged scenes. This idea is realized via the implementation of a physical-oriented probabilistic patch-based (PPB) filter based on a priori information of the underlying topography and analytical scattering models. This filter is appropriate for SAR images of natural scenes presenting a significant topography. An adaptive version of the proposed scattering-based mostly PPB filter for denoising of SAR pictures including each mountainous and flat areas is also developed. The performances of the proposed filter and its adaptive version are evaluated both qualitatively and quantitatively in numerical experiments using both simulated and actual SAR images. The proposed technique exhibits performance superior w.r.t. the quality PPB filter and comparable or, in some cases, superior to the state of the art, each in terms of speckle reduction and texture and detail preservation.