Combining speckle reduction and data compression for synthetic aperture radar (SAR) images in wavelet domain

The wavelet transform is widely used in both speckle reduction and data compression of SAR images. Thus, it is very efficient to integrate these two procedures in a single process. In this research, an input image is first subject to a logarithmic operation. The image is then transformed by using multiple level wavelet decomposition. The variance of noise is estimated from the data to determine the threshold, which is used for soft-thresholding the wavelet coefficients. For each subband, the obtained wavelet coefficients ate quantized and finally entropy encoded to produce the output bit stream of the image. The advantage of this method is that both speckle reduction and image compression are performed in wavelet domain. Experimental results on JERS-1/SAR images are also given.