In this paper, a novel method for SAR image classification based on stationary wavelet transform will be described. First, a SAR image is decomposed into 4 subbands using stationary wavelet transform. Each pixel is then represented by a 4-dimension vector whose components are taken from the wavelet subbands. The pixels are finally classified into a small set of categories by using a parametric supervised classification algorithm. The classification using this wavelet transform was successfully applied to a JERS-1/SAR image.
"Wavelet-based texture analysis for SAR image classification", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365885; https://doi.org/10.1117/12.365885