Wavelet energy signature: comparison and analysis

Authors:
Xiaobin Li;Zheng Tian
Affiliations:
Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an, China;Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an, China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Year:
2006

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Abstract

Though wavelet transform based methods have recently raised increasing interests in texture analysis due to their good space and frequency localization, many issues related to the choice of the wavelet basis and texture feature remain unresolved. In this paper, we evaluate the performance of seven wavelet energy signatures and eight wavelet basis for texture discrimination. Experimental results on 111 Brodatz textures show that the feature extracted from high and middle frequency channels is more suitable for texture analysis and the choice of wavelet basis has some influence on texture discrimination.