3 September 2015 Color graph based wavelet transform with perceptual information
Mohamed Malek, David Helbert, Philippe Carré
Author Affiliations +
Abstract
We propose a numerical strategy to define a multiscale analysis for color and multicomponent images based on the representation of data on a graph. Our approach consists of computing the graph of an image using the psychovisual information and analyzing it by using the spectral graph wavelet transform. We suggest introducing color dimension into the computation of the weights of the graph and using the geodesic distance as a mean of distance measurement. We thus have defined a wavelet transform based on a graph with perceptual information by using the CIELab color distance. This new representation is illustrated with denoising and inpainting applications. Overall, by introducing psychovisual information in the graph computation for the graph wavelet transform, we obtain very promising results. Thus, results in image restoration highlight the interest of the appropriate use of color information.
© 2015 SPIE and IS&T 1017-9909/2015/$25.00 © 2015 SPIE and IS&T
Mohamed Malek, David Helbert, and Philippe Carré "Color graph based wavelet transform with perceptual information," Journal of Electronic Imaging 24(5), 053004 (3 September 2015). https://doi.org/10.1117/1.JEI.24.5.053004
Published: 3 September 2015
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Wavelets

Wavelet transforms

Signal to noise ratio

Denoising

Distance measurement

RGB color model

Color difference

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