Speckle reduction for remote sensing images based on nonsubsampled contourlet

Existing speckle reduction methods for remote sensing images such as SAR cannot capture image edge detail information and reduce noise effectively at the same time. The nonsubsampled contourlet (NSCT) is built upon nonsubsampled pyramids and nonsubsampled directional filter banks and provides a shift-invariant directional multiresolution image representation. Therefore, a speckle reduction model based on NSCT is presented. Firstly original image with speckle noise was transformed into with additive noise by means of homomorphism transform, and then the NSCT was implemented, finally threshold denoising method was adopted to separate the noise and signal. A comparison between the above NSCT denoising method and conventional methods was carried out on remote sensing images contaminated by multiplicative noise and SAR original image. The experimental results show that the performance of the NSCT is superior not only in speckle reduction but also in edge preservation.