通用可细化网格编码量化

S. Steger, T. Richter
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引用次数: 7

摘要

提出了一种适用于多重构阶段位平面编码的通用可细化网格量化方案(URTCQ)。现有的可细化网格量化器要么需要过多的码本训练,并且在两个以上的阶段(MS-TCQ, E-TCQ)上被标量量化所优于,要么需要巨大的计算负担(SR-TCQ),要么仅在最后阶段(UTCQ)获得良好的率失真性能。所提出的量化技术是标量量化器和E-TCQ改进版本的混合。对于所有支持的源,只需要一次训练到i.i.d统一源,并且每个阶段的增量比特率不超过1bps。复杂度与阶段的数量和格子状态的数量成正比。我们比较了我们在广义高斯i.i.d源上的工作与在JPEG2000 (USDZQ, UTCQ)中部署的量化器的速率失真性能。事实证明,它在任何阶段都不比标量量化器差,并且通常优于UTCQ,除了最后阶段。
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Universal Refinable Trellis Coded Quantization
We introduce a novel universal refinable trellis quantization scheme (URTCQ) that is suitable for bitplane coding with many reconstruction stages. Existing refinable trellis quantizers either require excessive codebook training and are outperformed by scalar quantization for more than two stages (MS-TCQ, E-TCQ), require a huge computational burden (SR-TCQ) or achieve a good rate distortion performance in the last stage only (UTCQ). The presented quantization technique is a mixture of a scalar quantizer and an improved version of the E-TCQ. For all supported sources only one time training to an i.i.d. uniform source is required and its incremental bitrate is not more than 1 bps for each stage. The complexity is proportional to the number of stages and the number of trellis states. We compare the rate distortion performance of our work on generalized Gaussian i.i.d. sources with the quantizers deployed in JPEG2000 (USDZQ, UTCQ). It turns out that it is in no stage worse than the scalar quantizer and usually outperforms the UTCQ except for the last stage.
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