Land use classification of SAR images using a type II local discriminant basis for preprocessing

We present the application of the Type II local discriminant basis (LDB) technique to feature extraction for land use classification in synthetic aperture radar (SAR) images. Our classification algorithm incorporates spatial information into the decision process by classifying small image blocks, instead of single pixels. A feature vector composed of all the values in the image blocks is large for even small image blocks and, therefore, degrades the performance of many classifiers. The LDB technique greatly compresses the dimensionality of the feature vector, by indicating the most discriminant coordinates within the wavelet packet decomposition of an image block.