To improve the GMAP for speckle filtering by consideration of the correlation of SAR images

Synthetic aperture radar (SAR) images are corrupted by speckle noise, which degrades the quality and interpretation. One of the most traditional speckle filters, the Gamma Maximum-A-Posteriori (GMAP) speckle filter, is based on the first order texture models in SAR images, i.e. the local mean and local variance, without the consideration of the correlation present in the SAR images. To enhance the speckle filtering effects, this work presents an improved GMAP filter based on a new model which is able to take the correlation present in images into account. The final experimental results show that our proposed algorithm can get better performance in terms of the speckle suppression and the fine details preservation.