A fixed-rate quantizer using block-based entropy-constrained quantization and run-length coding

Dongchang Yu, M. Marcellin
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引用次数: 6

Abstract

A fast and efficient quantization technique is described. It is fixed-length, robust to bit errors, and compatible with most current compression standards. It is based on entropy-constrained quantization and uses the well-known and efficient Viterbi algorithm to force the coded sequence to be fixed-rate. Run-length coding techniques are used to improve the performance at low encoding rates. Simulation results show that it can achieve performance comparable to that of Huffman coded entropy-constrained scalar quantization with computational complexity increasing only linearly in block length.
使用基于块的熵约束量化和运行长度编码的固定速率量化器
描述了一种快速有效的量化技术。它是固定长度的,对比特错误具有鲁棒性,并且与大多数当前的压缩标准兼容。它基于熵约束量化,并使用众所周知的高效Viterbi算法强制编码序列固定速率。运行长度编码技术用于提高低编码率下的性能。仿真结果表明,该方法可以达到与霍夫曼编码熵约束标量量化相当的性能,且计算复杂度仅随数据块长度线性增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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