Adaptive vector lifting schemes and applications to stereo image coding. (Schémas de lifting vectoriels adaptatifs et applications à la compression d'images stéréoscopiques)

This thesis addresses the problem of stereo image coding for storage and transmission purposes. In particular, we are interested in lossy-to-lossless coding schemes allowing progressive reconstruction. In the first part, we propose novel coding methods based on Vector Lifting Schemes. Unlike conventional approaches which encode a reference image, a residual one and a disparity map, the proposed methods do not generate a residual image but two compact multiresolution representations of the left and the right images simultaneously. We also show the benefits that can be drawn from integrating a smooth and dense disparity field within such joint stereo image coding schemes. In the second part, we propose optimization techniques which can be used in the design of these lifting schemes. This allows us to build content adaptive methods. More precisely, we focus on the optimization of all the operators (i.e the update and prediction filters) involved in a lifting structure. To this end, we propose and analyze a new criterion for the design of the update filter. Concerning the prediction filters, we investigate techniques for optimizing sparsity criteria. xxiv A. Résumé en français