WAVELET-BASED COLOUR TEXTURE RETRIEVAL USING THE KULLBACK-LEIBLER DIVERGENCE BETWEEN BIVARIATE GENERALIZED GAUSSIAN MODELS

被引：20

作者：

Verdoolaege, Geert ^{[1
]}

Rosseel, Yves ^{[1
]}

Lambrechts, Michiel ^{[2
]}

Scheunders, Paul ^{[2
]}

机构：

[1] Univ Ghent, Dept Data Anal, Henri Dunantlaan 1, B-9000 Ghent, Belgium

[2] Univ Antwerp, Dept Phys, IBBT, Vis Lab, B-2610 Antwerp, Belgium

来源：

2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6 | 2009年

关键词：

colour texture retrieval; Kullback-Leibler divergence; multivariate generalized Gaussian distribution;

D O I：

10.1109/ICIP.2009.5413405

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：265 / +

页数：2

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