On the selection of an optimal wavelet basis for texture characterization

Although most of the theoretical and implementation aspects of wavelet based algorithms in texture characterization are well studied and understood, many issues related to the choice of filter bank in texture processing remain unresolved. The impact of the wavelet basis has been mentioned in a few p...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 9; no. 12; pp. 2043 - 2050
Main Authors:	Mojsilovic, A., Popovic, M.V., Rackov, D.M.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01-12-2000 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Analysis of variance Applied sciences Computers in experimental physics Decomposition Discrete transforms Discrete wavelet transforms Exact sciences and technology Filter bank Filter banks Finite impulse response filter Image analysis Image coding Image processing Image texture analysis Information, signal and communications theory Instruments, apparatus, components and techniques common to several branches of physics and astronomy Nonlinear filters Optimization Physics Signal processing Surface layer Telecommunications and information theory Texture Wavelet Wavelet transforms Characterization Texture analysis Optimal filter Image processing Wavelet transformation Coding Wavelet base Classification Decomposition method Filter bank Experimental study Algorithm
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Summary:	Although most of the theoretical and implementation aspects of wavelet based algorithms in texture characterization are well studied and understood, many issues related to the choice of filter bank in texture processing remain unresolved. The impact of the wavelet basis has been mentioned in a few papers, whereas other more detailed investigations have considered only the choice of the wavelet basis in image coding. For example, regularity, number of vanishing moments and a shift variance degree have been used for the filter evaluation in image coding, but the utility of all these metrics in texture analysis has not yet been established. Therefore, the scope of this paper was to investigate whether the properties of decomposition filters play an important role in texture description, and which feature is dominant in the selection of an optimal filter bank. We performed classification experiments with 23 Brodatz textures. Our investigation shows that the selection of the decomposition filters has a significant influence on the result of texture characterization. Finally, the paper ranks 19 orthogonal and biorthogonal filters, and establishes the most relevant criteria for choice of decomposition filters in wavelet-based texture characterization algorithms.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1
ISSN:	1057-7149 1941-0042
DOI:	10.1109/83.887972