Novel speckle filtering based on heterogeneity measurement and non-local mean
Chen Shao-b · Jisuanji yingyong yanjiu · 2014
Conventional Euclidean distance can not measure the similarity of SAR image patches robustly. In order to solve this problem,the Euclidean distance was combined with SAR image heterogeneity measurement. Then,this paper proposed a novel similarity measure of SAR image. Further,it designed a new speckle reducing algorithm based on the novel similarity measure. First,it calculated the Euclidean distance of similarity windows and CV( coefficient variation) of search window.Secondly,it adjusted the decay parameter h to CV. Then,it calculated the novel similarity based on the Euclidean distance and the adjusted decay parameter. Last,it performed a weighted average of the values of similar pixels based on the new similarity. The deal with synthetic and real SAR images contaminated by speckle would be filtered by this proposed algorithm. The visual quality and the quantification estimation show that the proposed approach can suppress speckle effectively and keep features of edge,texture,and details simultaneously. In addition,comparing to other NLM methods for speckle filtering,the computational complexity of the proposed is greatly reduced.