A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Some computer applications for tissue characterization in medicine operate with tissue samples taken from small area of interest so that only few methods can be used. These methods should be insensitive to noise and image distortions and yet reliable enough. Here, the authors propose a new approach for texture analysis, based on the wavelet transform. The idea of this method is to decompose analyzed image with the filter bank derived from an orthonormal wavelet basis and to form image approximations with higher resolution. Energies calculated at the outputs of the filter bank are used as texture features in an unsupervised classification procedure based on a modification of the statistical T-test. The method is tested clinically, for characterization of infarcted myocardium and reported classification results are very promising.