TRELLIS-BASED SCALAR-VECTOR QUANTIZER FOR MEMORYLESS SOURCES

This paper describes a structured vector quantization approach for sta tionary memoryless sources that combines the scalar-vector quantizer ( SVQ) ideas (Laroia and Farvardin) with trellis coded quantization (Mar cellin and Fischer). The resulting quantizer is called the trellis-bas ed scalar-vector quantizer (TB-SVQ). The SVQ structure allows the TB-S VQ to realize a large boundary gain while the underlying trellis code enables it to achieve a significant portion of the total granular gain . For large block-lengths and powerful (possibly complex) trellis code s the TB-SVQ can, in principle, achieve the rate-distortion bound. As indicated by the results obtained here, even for reasonable block-leng ths and relatively simple trellis codes, the TB-SVQ outperforms all ot her fixed-rate quantizers at reasonable complexity.