Spatial and temporal models for texturebased video coding In this paper, we investigate spatial and temporal models for texture analysis and synthesis. The goal is to use these models to increase the coding efficiency for video sequences containing textures. The models are used to segment texture regions in a frame at the encoder and synthesize the textures at the decoder. These methods can be incorporated into a conventional video coder (e.g. H.264) where the regions to be modeled by the textures are not coded in a usual manner but texture model parameters are sent to the decoder as side information. We showed that this approach can reduce the data rate by as much as 15%.

Video coding with fully separable wavelet and wavelet packet transforms Threedimensional (t2D) wavelet coding schemes have been demonstrated to be efficient techniques for video compression applications. However, the separable wavelet transform used for removing the spatial redundancy allows a limited representation of the 2D texture because of spatial isotropy of the wavelet basis functions. In this case, anisotropic transforms, such as fully separable wavelet transforms (FSWT), can represent a solution for spatial decorrelation. FSWT inherits the separability, the computational simplicity and the filter bank characteristics of the standard 2D wavelet transform, but it improves the representation of directional textures, as the ones which can be found in temporal detail frames of t  2D decompositions. The extension of both classical wavelet and waveletpacket transforms to fully separable decompositions preserve at the same time the lowcomplexity and bestbases selection algorithms of these ones. We apply these transforms in t  2D video coding schemes and compare them with classical decompositions.