Improved Fisher MAP Filter for Despeckling of High-Resolution SAR Images Based on Structural Information Detection

Abstract

Fisher distribution is a popular model for high-resolution (HR) synthetic aperture radar (SAR) images due to its high-peaked and heavy-tailed characteristics as well as its theoretical justification and mathematical tractability. Based on the Fisher modeling of SAR images, the maximum a posteriori (MAP) filter is suggested. In the Fisher model, the parameter of image looks is thought to be fixed to correspond to the formation mechanism of multi-look intensity images, and the other two parameters are accur ately assessed from the SAR image based on second-kind statistics. To improve the Fisher MAP filter especially in the aspect of speckle suppression, the Fisher MAP filter based on recognition of structural information is created using point target detection, the adaptive windowing method, homogeneous region detection, and selection of most homogeneous sub-window. The experiments on despeckling of HR SAR images demonstrate that the improved Fisher MAP filter based on structural information detection can suppress speckle in homogenous and edge regions, and effectively preserve fine details, edges, and point targets.