用抖动量化器进行变换编码

E. Akyol, K. Rose
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引用次数: 1

摘要

本文研究了结合抖动量化的最优变换编码。最优确定性量化器的误差与重建值不相关,而抖动量化器产生的量化误差与重建值相关,但是白色的,与源无关。这些属性提供了潜在的好处,但也对其他编码人员的优化有影响。我们推导了结果抖动量化的最优变换。对于固定速率编码,我们证明了为抖动量化导出的变换是普遍最优的(对所有源),不像传统的量化情况下,Karhunen-Loeve变换的最优性是保证高斯源。此外,我们还建立了高斯源的可变速率编码最优性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Transform Coding with Dithered Quantizers
This paper is concerned with optimal transform coding in conjunction with dithered quantization.While the optimal deterministic quantizer's error is uncorrelated with the reconstructed value, the dithered quantizer yields quantization errors that are correlated with the reconstruction but are white and independent of the source. These properties offer potential benefits, but also have implications on the optimization of the rest of the coder. We derive the optimal transform for consequent dithered quantization. For fixed rate coding, we show that the transform derived for dithered quantization is universally optimal (for all sources), unlike the conventional quantization case where optimality of the Karhunen-Loeve transform is guaranteed for Gaussian sources. Moreover, we establish variable rate coding optimality for Gaussian sources.
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