An adaptive technique for accuracy enhancement of vector quantizers in nonorthogonal domains

Recently, novel vector quantization techniques in multiple nonorthogonal domains for both waveform and model-based signal characterization that give an improved qualitative and quantitative signal coding performance as compared to vector quantization in single domain have been reported. In these techniques, vectors are formed either directly from the signal waveform or from the model parameters extracted from the signal. Then, the vectors are represented in multiple nonorthogonal domains. The encoder chooses the domain that best represents the vector according to a predetermined criterion. An iterative codebook enhancement algorithm, applicable to both waveform and model-based vector quantization in nonorthogonal domains is developed and presented in this paper. In this algorithm, each set of codebooks in a given domain is retrained by the vectors that were best represented by that particular set of codebooks in the most recent iteration. The algorithm is applied successfully and extensive simulation results yield considerable performance enhancement of the vector quantization in nonorthogonal domains, for a given bit rate. Sample results are provided which demonstrate the improved performance.