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Robust texture classification using wavelet frames

Acharyya M., Kundu M.

Image Processing & Communications

1999

Vol. 5, no 2

19-37

In this paper we present an approach to characterize textures at multiple scales using wavelet transforms and discuss the issues of translational and rotational invariance and noise immunity of a texture analysis system. We employ the non-separable discrete wavelet frames analysis which gives an overcomplete wavelet decomposition. Discrete Wavelet Frame (DWF) decompose the textures into a set of frequency channels. A texture is characterized by a set of these channel variances in this work. Classification experiments using twenty Brodazt textures indicate that texture signatures based on wavelet frame analysis are beneficial for accomplishing subtle discrimination of textures and robust classification against rotation translation and noise.