Entropy-constrained finite-state residual vector quantization: a new scheme for low-bit-rate coding

Syed A. Rizvi; Nasser M. Nasrabadi

doi:10.1117/12.233242

27 February 1996 Entropy-constrained finite-state residual vector quantization: a new scheme for low-bit-rate coding

Syed A. Rizvi, Nasser M. Nasrabadi

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233242
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

Abstract

Finite-state vector quantization (FSVQ) is known to give a better performance than a memoryless vector quantization (VQ). Recently, a new scheme that incorporates a finite memory into a residual vector quantizer (RVQ) has been developed. This scheme is referred to as finite-state RVQ (FSRVQ). FSRVQ gives better performance than the conventional FSVQ with a substantial reduction in the memory requirement. The codebook search complexity of an FSRVQ is also reduced in comparison with that of the conventional FSVQ scheme. This paper presents a new variable-rate VQ scheme called entropy-constrained finite state residual vector quantization (EC-FSRVQ). EC-FSRVQ is designed by incorporating a constraint on the output entropy of an FSRVQ during the design process. This scheme is intended for low bit rate applications due to its low codebook search complexity and memory requirements. Experimental results show that the EC-FSRVQ outperforms JPEG at low bit rates.

Citation Download Citation

Syed A. Rizvi and Nasser M. Nasrabadi "Entropy-constrained finite-state residual vector quantization: a new scheme for low-bit-rate coding", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233242

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KEYWORDS

Quantization

Neural networks

Neurons

Computer programming

Distortion

Tin

Computer engineering

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