Lattice vector quantization of generalized Gaussian sources

Many important sources of data including subband image and speech coefficients are highly peaked and can be well-modeled by the family of generalized Gaussian (GG) PDF's parameterized by a shape parameter nu. We present here algorithms for defining and quantizing to a Z lattice in which the boundary is optimized to the characteristics of GG sources, and show that these techniques lead to high performance and low complexity for bit rates and dimensions that are of interest in a number of practical coding applications. We derive an analytical description of the granular and overload distortion valid for low and moderate bit rates, and also provide a description of quantizer performance in the limit of high rate and dimension.