Title :
Entropy-Coded Lattice Vector Quantization Dedicated to the Block Mixture Densities
Author :
Guillemot, Ludovic ; Gaudeau, Yann ; Moussaoui, Saïd ; Moureaux, Jean-Marie
Author_Institution :
Technoport Schlassgoart, Esch Sur Alzette
Abstract :
Entropy-coded lattice vector quantization (ECLVQ) with codebooks dedicated to independent identically distributed (i.i.d.) generalized Gaussian sources have proven their high coding performances in the wavelet domain. It is well known that wavelet coefficients with high magnitude (corresponding to edges and textures) tend to be clustered in a few amount of vectors. In this paper, we first show that this property has a major influence on the performances of ECLVQ schemes. Since this clustering property cannot be taken into account by the classical i.i.d. assumption, our first proposal is to model the joint distribution of vectors by a multidimensional mixture of generalized Gaussian (MMGG) densities. The main outcome of this MMGG model is to provide a theoretical framework to simply derive from i.i.d. - models, the corresponding MMGG - models. In a second part, a new codebook better suited to wavelet coding is proposed: the so-called dead zone lattice vector quantizers (DZLVQ). It consists of generalizing the scalar dead zone to vector quantization by thresholding vectors according to their energy. We show that DZLVQ improves the rate-distortion tradeoff. Experimental results are provided for the pyramidal LVQ scheme under the assumption of a multidimensional mixture of Laplacian (MML) densities. Results performed on a set of real life images show the precision of the analytical - curves and the efficiency of the DZLVQ scheme.
Keywords :
Gaussian processes; data compression; edge detection; entropy codes; image coding; image segmentation; image texture; pattern clustering; rate distortion theory; vector quantisation; wavelet transforms; block mixture density; codebook; dead zone lattice vector quantizers; entropy-coded lattice vector quantization; image compression; image edge; image texture; independent identically distributed generalized Gaussian source; joint vector distribution; multidimensional mixture of generalized Gaussian density; rate-distortion tradeoff; thresholding vector; vector clustering; wavelet coding; wavelet domain; Analytical rate-distortion model; lattice vector quantization (LVQ); mixture of gamma densities; mixture of generalized Gaussian densities (MGGD); sparsity; vector dead zone; Algorithms; Computer Simulation; Data Compression; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Statistical; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2008.2001044