Pyramid non-local mean filter for interferometric phase denoising

Abstract

Interferometric phase denoising is a crucial step of interferometric SAR processing flow. Its performance has great effect on the following steps. Traditional interferometric phase denoising algorithms have a similar drawback that they will wipe off some texture details in the phase image at the same time of filtering noise out. Non local mean filter, in contrast, can find a balance between denoising and texture preserving because it utilizes the recursive structures from the whole image. Taking the features of interferometric phase image into consideration, this paper proposes a modified Non-local mean filter algorithm to solve this problem. Moreover, in order to preserve texture to the biggest extend, an iterative algorithm is invented. In the end, experiments on synthetic and real data validate that this algorithm outperforms other traditional denoising methods.