Wavelet-based texture analysis for SAR image classification
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A novel method for SAR image classification based on the stationary wavelet transform is described. First, a SAR image is decomposed into 4 subbands using the stationary wavelet transform. Each pixel is then represented by a 4-dimension vector those 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.
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