Wavelet-based colour texture retrieval using the Kullback-Leibler divergence between bivariate generalized Gaussian models

Authors:
Geert Verdoolaege;Yves Rosseel;Michiel Lambrechts;Paul Scheunders
Affiliations:
Department of Data Analysis, Ghent University, Gent, Belgium;Department of Data Analysis, Ghent University, Gent, Belgium;IBBT, Vision Lab, Department of Physics, University of Antwerp, Wilrijk, Belgium;IBBT, Vision Lab, Department of Physics, University of Antwerp, Wilrijk, Belgium
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

We study the retrieval of coloured textures from a database. In a statistical framework we model the heavy-tailed wavelet histograms through a generalized Gaussian distribution (GGD). We choose the Kullback-Leibler divergence (KLD) as a similarity measure and we obtain a closed-form expression for the KLD between two zero-mean bivariate GGDs. This allows us to take into account the rich correlation structure between the colour bands two by two. We show that this results in a considerably improved retrieval rate and, in addition, we demonstrate the superior performance of the bivariate GGD, in comparison with the bivariate Gaussian.