Hybrid denoising algorithm of NSCT and improved NL-means method to SAR images

Abstract

To efficiently preserve tiny details and sharpness information of synthetic aperture radar (SAR) images while clearly remove the speckles, a despeckling method is proposed in this letter. Firstly, the SAR image is creatively separated to two parts: the texture region and flat region by using the decomposition with non-subsampled contourlet transform (NSCT) and mask estimation iteration algorithm. secondly, in the texture region, a new method of integrating the non-local means (NL-means) with block matching is used to preserve the sharpness and tiny details of SAR images; finally, a big searching window is utilized only in the flat region to remove the noise to a great extent. The experimental results show that both the visual quality and evaluation index of the proposed method outperform the traditional three methods: enhance Lee filtering (ELF), the bilateral Filtering (BF) and the improved NL-means.

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Cite this paper

@article{Hongyu2013HybridDA, title={Hybrid denoising algorithm of NSCT and improved NL-means method to SAR images}, author={Zhao Hongyu and Wang Qingping and Wu Weiwei and Yuan Naichang}, journal={Proceedings 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)}, year={2013}, pages={879-882} }