作为直方图分割的量化:网络系统中全局最优标量量化器设计

D. Muresan, M. Effros
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引用次数: 42

摘要

我们提出了一种多项式时间算法,用于离散字母源的最优标量量化器设计。该方法的特殊情况产生了固定速率和熵约束标量量化器、多分辨率标量量化器、多描述标量量化器和Wyner-Ziv标量量化器的最佳设计算法。该算法保证了固定速率和熵约束标量量化器的全局最优解和其他编码场景的约束最优解。我们通过证明标量量化、直方图分割和某有向无环图的最短路径问题之间的联系,推导出该算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantization as histogram segmentation: globally optimal scalar quantizer design in network systems
We propose a polynomial-time algorithm for optimal scalar quantizer design on discrete-alphabet sources. Special cases of the proposed approach yield optimal design algorithms for fixed-rate and entropy-constrained scalar quantizers, multi-resolution scalar quantizers, multiple description scalar quantizers, and Wyner-Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for fixed-rate and entropy-constrained scalar quantizers and constrained optima for the other coding scenarios. We derive the algorithm by demonstrating the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph.
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