Combined Wavelet and Contourlet Denoising of SAR Images

The nonsubsampled contourlet transform (NSCT) is a new image representation approach that has sparser representation at both spatial and directional resolution and thus captures smooth contours in images On the other hand, wavelet transform has sparser representation of homogeneous areas. In this paper, three combinations of undecimated wavelet and nonsubsampled contourlet transforms will be used for denoising of SAR images. Two of the methods use the wavelet transform to denoise homogeneous areas and the nonsubsampled contourlet transform to denoise areas with edges. The segmentation between homogeneous areas and areas with edges is done by using total variation segmentation. The third method is a linear averaging of the two denoising methods. A thresholding in the wavelet and contourlet domain is done by non-linear functions which are adapted for each selected subband. The non-linear functions are based on sigmoid functions. Simulation results suggested that these denoising schemes achieve good and clean images.