Wavelet shrinkage and compression for SAR images

Abstract

The paper presents the wavelet shrinkage and the image compression for SAR images, based on discrete wavelet transform (DWT). It is very efficient to integrate these two procedures in a single process. First, a speckled SAR image is transformed by using multiple level wavelet decomposition. The variance of noise is estimated from wavelet coefficients to determine the threshold, which is used for soft thresholding in all high frequency subbands. The well-known threshold estimation includes SimpleShrink, NormalShrink, VisuShrink, SureShrink, and BayesShrink. The obtained wavelet coefficients are then encoded by using embedded zero-tree wavelet (EZW) to produce the output bit stream of the despeckled image. By means of an evaluating technique include S/MSE, MSE, and PSNR. Experimental results on JERS-1/SAR images are also given.