Spatial Constant Quantization in JPEG XR is Nearly Optimal

T. Richter
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引用次数: 6

Abstract

The JPEG XR image compression standard, originally developed under the name HD-Photo by Microsoft, offers the feature of spatial variably quantization; its codestream syntax allows to select one out of a limited set of possible quantizers per macro block and per frequency band. In this paper, an algorithm is presented that finds the rate-distortion optimal set of quantizers, and the optimal quantizer choice for each macro block. Even though it seems plausible that this feature may provide a huge improvement for images whose statistics is non-stationary, e.g. compound images, it is demonstrated that the PSNR improvement is not larger than 0.3dB for a two-step heuristics of feasible complexity, but improvements of up to 0.8dB for compound images are possible by a much more complex optimization strategy.
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空间常数量化在JPEG XR中几乎是最优的
JPEG XR图像压缩标准最初由微软以HD-Photo的名义开发,提供了空间可变量化的特性;它的码流语法允许从每个宏块和每个频带的有限可能量化器集中选择一个。本文提出了一种寻找率失真最优量化器集的算法,并给出了每个宏块的最优量化器选择。尽管对于统计数据是非平稳的图像(如复合图像),该特征似乎可以提供巨大的改进,但事实证明,对于可行复杂度的两步启发式算法,PSNR的改进不大于0.3dB,但对于复合图像,通过更复杂的优化策略,PSNR的改进可能高达0.8dB。
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