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Fast Mode Decision for Coarse Granular Scalability via Switched Candidate Mode Set

机译:通过切换候选模式集的快速模式判定粗粒缩放性

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This paper presents an improved fast mode decision algorithm for coarse grain scalability (CGS). The modified fast mode decision algorithm extends previous work to provide better encoder complexity reduction with insignificant degradation in picture quality. The candidate mode set is adaptive to the quantization parameter difference between a layer and its "base layer". Furthermore, the proposed scheme fully utilizes the statistics of mode transition between a layer and its "base layer" when the quantization parameter difference between these two layers is small. Simulation results demonstrate that the proposed scheme provides up to 64% of time saving compared with the original SVC encoder.
机译:本文介绍了一种改进的粗粒可伸缩性的快速模式决策算法(CGS)。修改的快速模式决策算法扩展了以前的工作,以提供更好的图像质量下降的编码器复杂性降低。候选模式集适用于层和其“基层”之间的量化参数差。此外,当这两层之间的量化参数差小时,所提出的方案充分利用层和“基层”之间的模式转换统计。仿真结果表明,与原始SVC编码器相比,所提出的方案可提供高达64%的节省时间。

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