Bit allocation for dependent quantization with applications to multiresolution and MPEG video coders
Bit allocation for dependent quantization with applications to multiresolution and MPEG video coders
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DOI：
10.1109/83.334987
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发表时间：
1994-09
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影响因子：
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通讯作者：
K. Ramchandran;Antonio Ortega;M. Vetterli
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文献类型：
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作者：
K. Ramchandran;Antonio Ortega;M. Vetterli
我们解决了相关编码环境中有效位分配的问题。虽然文献中已经研究了独立编码信号块的最佳比特分配，但我们将这些技术扩展到更一般的时间和空间相关的编码场景。特别令人感兴趣的是热门的 MPEG 视频编码器和多分辨率编码器。我们的方法对任意量化器集使用操作率失真（R-D）框架。我们展示了如何利用相关 R-D 曲线的某些单调性特性来制定快速方法来获得最佳和接近最佳的解决方案。我们说明了该属性在指定智能修剪条件中的应用，以消除 MPEG 分配问题的次优操作点，为此我们还指出了快速近最优启发法。此外，我们以空间金字塔编码器为例，为多分辨率编码器制定了有效的分配策略。然后，我们将此分析扩展到时空 3D 金字塔编码方案。我们解决了优化全分辨率质量的兼容性问题，同时满足次分辨率比特率或质量限制。我们展示了如何获得快速解决方案，提供近乎最佳（通常在 0.3 dB 以内）全分辨率质量，同时为次分辨率层提供更好的性能（通常比全分辨率最佳解决方案好 2-3 dB）。
We address the problem of efficient bit allocation in a dependent coding environment. While optimal bit allocation for independently coded signal blocks has been studied in the literature, we extend these techniques to the more general temporally and spatially dependent coding scenarios. Of particular interest are the topical MPEG video coder and multiresolution coders. Our approach uses an operational rate-distortion (R-D) framework for arbitrary quantizer sets. We show how a certain monotonicity property of the dependent R-D curves can be exploited in formulating fast ways to obtain optimal and near-optimal solutions. We illustrate the application of this property in specifying intelligent pruning conditions to eliminate suboptimal operating points for the MPEG allocation problem, for which we also point out fast nearly-optimal heuristics. Additionally, we formulate an efficient allocation strategy for multiresolution coders, using the spatial pyramid coder as an example. We then extend this analysis to a spatio-temporal 3-D pyramidal coding scheme. We tackle the compatibility problem of optimizing full-resolution quality while simultaneously catering to subresolution bit rate or quality constraints. We show how to obtain fast solutions that provide nearly optimal (typically within 0.3 dB) full resolution quality while providing much better performance for the subresolution layer (typically 2-3 dB better than the full-resolution optimal solution).