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Proceedings Paper

Multiridgelets for texture analysis
Author(s): Hong-Jun Yoon; Ching-Chung Li
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Paper Abstract

The directional wavelet used in image processing has orientation selectivity and can provide a sparse representation of edges in natural images. Multiwavelets offer the possibility of better performance in image processing applications as compared to the scalar wavelet. Applying directionality to multiwavelets may thus gain both advantages. This paper proposes a scheme, named multiridgelets, which is an extension of ridgelets. We consider the application of the balanced multiwavelet transform to the Radon transform of an image. Specifically, we consider its use in the image texture analysis. The regular polar angle method is employed to realize the discrete transform. Three statistical features: standard deviation, median, and entropy are computed based on multiridgelet coefficients. Comparative study was made with the results obtained using 2D wavelets, scalar ridgelets, and curvelets. Classification of the mura defects of the LCD screen is tested to quantify performance of the proposed texture analysis methods. 240 normal images and 240 simulated defected images are supplied to train the support vector machine classifier and another 40 normal and 40 defected images for testing. It concludes that multiridgelets were comparable to or better than curvelets and gave significant performance than 2D wavelets and scalar ridgelets.

Paper Details

Date Published: 27 January 2009
PDF: 8 pages
Proc. SPIE 7248, Wavelet Applications in Industrial Processing VI, 724803 (27 January 2009); doi: 10.1117/12.805626
Show Author Affiliations
Hong-Jun Yoon, Univ. of Pittsburgh (United States)
Ching-Chung Li, Univ. of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 7248:
Wavelet Applications in Industrial Processing VI
Frederic Truchetet; Olivier Laligant, Editor(s)

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