Data-rate constrained lattice vector quantization: a new quantizing algorithm in a rate-distortion sense

This paper describes an image coding scheme using lattice vector quantizers where the emphasis is put on a new lattice vector quantization approach. The adaptive signal decomposition uses wavelet packets which allow to best match the decomposition to the signal non-stationary characteristics. The quantizers used here are data rate constrained lattice vector quantizers. A classical rate-distortion algorithm [Ramchandran and Vetterli, 1993] based on two nested optimization processes allows to jointly optimize transformation and quantization and is used as a first step in the quantization procedure described here. It allows to define in each subband the lattice spacing (or scaling factor) minimizing the overall distortion for a given bit rate and to choose by a pruning algorithm the best structure of decomposition. An additional procedure developed here allows (by exploiting the lattice properties) to project a vector on a lattice point providing a better rate-distortion tradeoff. In addition, a new partitioning of the vector space allowing to divide the source of vectors into three sub-sources is introduced in order to improve the coding efficiency. In the rate distortion plane, this new quantization procedure brings a significant improvement of about 0.5-0.6 dB with respect to the classical rate-distortion algorithm