Jointly optimized trellis-coded residual vector quantization

The union of residual vector quantization (RVQ) and trellis-coded vector quantization (TCVQ) was considered by various authors where the emphasis was on the sequential design. We consider a new jointly optimized combination of RVQ and TCVQ with advantages in all categories. Necessary conditions for optimality of the jointly optimized trellis-coded residual vector quantizers (TCRVQ) are derived. A constrained direct sum tree structure is introduced that facilitates RVQ codebook partitioning. Simulation results for jointly optimized TCRVQ are presented for memoryless Gaussian, Laplacian, and uniform sources. The rate-distortion performance is shown to be better than RVQ and sequentially designed TCRVQ