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Optimal entropy coding in image subband coders

机译:图像子带编码器中的最佳熵编码

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The paper argues that the JPEG coder is based on a non-optimal entropy coding method. It is shown that for frequency domain coders using uniform quantization it is optimal to use entropy coders optimized for the entropy in each frequency component. A subband coder model with uniform quantization followed by optimal entropy coding is presented, where each subband is allocated an entropy coder based on its entropy. The theoretical coding gain limit for this model is shown to be the same as for frequency domain coders employing explicit bit allocation. However, the new model exploits the advantage associated with variable length coding. In addition, it is possible to efficiently use midtread quantizers, which have higher mean square error performance and, more important, better visual performance than midrise quantizers. Advantages for practical subband image coders are discussed in the paper.
机译:本文认为JPEG编码器基于非最优熵编码方法。结果表明,对于使用均匀量化的频域编码器,它是最佳使用针对每个频率分量中的熵优化的熵编码器。提出了具有均匀量化之后的子带编码器模型,然后是最佳熵编码,其中基于其熵分配每个子带。该模型的理论编码增益限制显示为与采用显式比特分配的频域编码器相同。然而,新模型利用了与可变长度编码相关的优势。此外,可以有效地使用中继量化器,其具有更高的均方误差性能,而且比中型量化器更重要,更良好的视觉性能。本文讨论了实用子带图像编码器的优点。

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