GF-3 SAR image despeckling based on non-subsampled shearlet transform
Zengguo Sun, Rui Shi · 2017
More and more attentions have been paid to GF-3 due to its diversified imaging mode, high resolution and extensive application. However, due to the coherent imaging system, speckle appears in GF-3 synthetic aperture radar (SAR) images and it hinders the understanding and interpretation of images seriously. As a new multi-resolution analysis tool, Shearlet has the best sparse representation and it can effectively deal with the high-resolution SAR images that have the obvious sparse features. In this paper, non-subsampled Shearlet transform is used to deal with GF-3 SAR images. Firstly, the logarithmic operation is applied to the GF-3 SAR image, and the Shearlet-transformed coefficients are obtained for different subbands and different directions. The hard-threshold algorithm is used for the transformed high frequency coefficients, and the Shearlet reconstruction is carried out. The despeckled image is obtained by making an exponential operation. The experimental results demonstrate that compared with other despeckling methods, the non-subsampled Shearlet transform can effectively suppress the speckle in homogeneous region and it has the highest capability of edge feature and strong point target preservation.