Texture classification with tree-structured wavelet transform

Proposes a multiresolution approach based on a tree-structured wavelet transform for texture classification. The development of tree-structured wavelet transform is motivated by the observation that textures are quasi-periodic signals whose dominant frequencies are located in the middle frequency channels. With the transform, one is able to zoom into desired frequency channels and performs further decomposition. In contrast, the conventional wavelet transform only decomposes subsignals in low frequency channels. A progressive texture classification algorithm which is not only computationally attractive but also has excellent performance is developed