Multi-Band Texture Modeling Using Finite Mixtures of Multivariate Generalized Gaussian Distributions

We present a unified statistical model for multivariate and multi-modal texture representation. This model is based on the formalism of finite mixtures of multivariate generalized Gaussians (MoMGG) which enables a compact and accurate representation of joint statistics of different sub-bands of multireslotion texture transform. This representation expresses correlation between sub-bands at different scales and orientations, and also between adjacent locations within the same subbands, providing a precise description of the texture layout. It enables also to combine different multi-scale transforms to build a richer and more representative texture signature. We successfully tested the model on traditional texture transforms such as wavelets and contourlets. Experiments on color-texture image retrieval have demonstrated the performance of our approach comparatively to state-of-art methods.