Mutual Information Based Subbband Selection for Wavelet Packet Based Image Classification
Ke Huang, Selin Aviyente · 2006
In wavelet packet based image processing and classification, the proper selection of a subset of subbands can achieve a good representation of the image with a small number of subbands. Various algorithms have been proposed to address the subband selection problem. However, these algorithms evaluate the representation power of each subband separately and subsequently choose a set of subbands based on this representation power. Such a process implicitly assumes the independence between different subbands, which seldom holds and thus degrades performance. To address the limit of the existing algorithms, we propose a mutual information based subband selection algorithm for image classification. We also introduce a practical method for computing mutual information in high dimensional space. Our experiments show that the proposed subband selection algorithm effectively improves the accuracy of wavelet packet based image classification.