Color channels decorrelation by ICA transformation in the wavelet domain for color texture analysis and synthesis

Yufeng Liang, Eero P. Simoncelli, Zhibin Lei

Research output: Contribution to journalArticle

Abstract

In this paper, we developed a color model to cancel the dependency between color channels, which enables us to separate spectral processing from spatial processing. We introduced Independent Component Analysis (ICA) transformation in the wavelet domain to decorrelate the subband color joint statistics. The decorrelated joint color conditional histograms display scaling of variance. Gaussian Scale Mixture (GSM) was used to model the subband color statistics and a normalization scheme was adapted to cancel the pair-wise color subband statistical dependency. This color model was combined with the Portilla/Simoncelli texture model to construct the color texture model. Based on this model, features were extracted and the corresponding color texture synthesis scheme was developed.

Original languageEnglish (US)
Pages (from-to)608-611
Number of pages4
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume1
DOIs
StatePublished - Jan 1 2000

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ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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