Texture analysis and classification with tree-structured wavelet transform

Authors:
T. Chang;C. -C.J. Kuo
Affiliations:
Dept. of Electr. Eng.-Syst., Univ. of Southern California, Los Angeles, CA;-
Venue:
IEEE Transactions on Image Processing
Year:
1993

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Abstract

A multiresolution approach based on a modified wavelet transform called the tree-structured wavelet transform or wavelet packets is proposed. The development of this transform is motivated by the observation that a large class of natural textures can be modeled as quasi-periodic signals whose dominant frequencies are located in the middle frequency channels. With the transform, it is possible to zoom into any desired frequency channels for further decomposition. In contrast, the conventional pyramid-structured wavelet transform performs further decomposition in low-frequency channels. A progressive texture classification algorithm which is not only computationally attractive but also has excellent performance is developed. The performance of the present method is compared with that of several other methods