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Quantization as Histogram Segmentation: Optimal Scalar Quantizer Design in Network Systems

机译:量化作为直方图分段:网络系统中的最佳标量量化器设计

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摘要

An algorithm for scalar quantizer design on discrete-alphabet sources is proposed. The proposed algorithm can be used to design fixed-rate and entropy-constrained conventional scalar quantizers, multiresolution scalar quantizers, multiple description scalar quantizers, and Wyner–Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for conventional fixed-rate scalar quantizers and entropy-constrained scalar quantizers. For the other coding scenarios, the algorithm yields the best code among all codes that meet a given convexity constraint. In all cases, the algorithm run-time is polynomial in the size of the source alphabet. The algorithm derivation arises from a demonstration of the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph.
机译:提出了一种在离散字母源上进行标量量化器设计的算法。所提出的算法可用于设计固定速率和受熵约束的常规标量量化器,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。该算法保证了常规固定速率标量量化器和熵约束标量量化器的全局最优解。对于其他编码方案,该算法在满足给定凸度约束的所有代码中产生最佳代码。在所有情况下,算法运行时都是源字母大小的多项式。该算法的推导来自对标量量化,直方图分割和某个有向无环图中的最短路径问题之间的联系的证明。

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  • 作者

    Muresan Dan; Effros Michelle;

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  • 年度 2008
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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