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Trellis-based scalar-vector quantizer for memoryless sources

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2 Author(s)
R. Laroia ; AT&T Bell Labs., Murray Hill, NJ, USA ; N. Farvardin

The paper describes a structured vector quantization approach for stationary memoryless sources that combines the scalar-vector quantizer (SVQ) ideas (Laroia and Farvardin, 1993) with trellis coded quantization (Marcellin and Fischer, 1990). The resulting quantizer is called the trellis-based scalar-vector quantizer (TB-SVQ). The SVQ structure allows the TB-SVQ 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 codes the TB-SVQ can, in principle, achieve the rate-distortion bound. As indicated by the results obtained, even for reasonable block-lengths and relatively simple trellis codes, the TB-SVQ outperforms all other fixed-rate quantizers at reasonable complexity

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IEEE Transactions on Information Theory  (Volume:40 ,  Issue: 3 )