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 language||English (US)|
|Number of pages||4|
|Journal||Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
|State||Published - 2000|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition