Multispectral image indexing based on Vector Lifting Schemes

In this work, we are interested in extracting salient signatures from multiscale representations of multispectral images for retrieval applications. The contribution of this paper consists in focusing on a special multiresolution decomposition based on the concept of Vector Lifting Scheme (VLS) which offers the advantage of simultaneously capturing the spatial and the cross-spectral redundancies of any multicomponent image. Within each subband, the joint distribution of the resulting coefficients stacked through the spectral components is modeled by a multivariate function driven by an appropriately chosen copula function. The parameters of such distribution model are chosen as relevant signatures of the image. Experimental results indicate an improvement in the retrieval performances when using the VLS instead of the conventional wavelet transform.