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Efficient Probability Based Macroblock Mode Selection In H.264/AVC

机译:H.264 / AVC中基于有效概率的宏块模式选择

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摘要

To get high compress efficiency, the latest H.264/AVC international video coding standard introduced many more advanced tools than previously used standards, such as using sophisticated prediction and rate-distortion (RD) mode selection. Although these new coding tools can significantly improve video coding efficiency, the improvement in performance comes at substantially higher computational complexity as a result of more complicated mode decision. To reduce the complexity of H.264 encoding, various fast mode decision algorithms have been proposed. Many of these algorithms take advantage of motion and video content classification so as to reduce the number of modes tried during mode decision. When used for video sequences with high motion or detailed visual information, video coding efficiency can be significantly compromised as a result of imperfect classification. In this paper, an efficient Probability Based Macroblock Mode Selection (PBMMS) algorithm is proposed. Each MB is predicted to different probability MB based on spatial and special correlation, which then leads to 50-60% computation savings and some compression performance improvements over existing H.264 fast mode decision algorithms.
机译:为了获得较高的压缩效率,最新的H.264 / AVC国际视频编码标准引入了比以前使用的标准更高级的工具,例如使用复杂的预测和速率失真(RD)模式选择。尽管这些新的编码工具可以显着提高视频编码效率,但由于模式决策更加复杂,因此性能的提高显着提高了计算复杂度。为了降低H.264编码的复杂性,已经提出了各种快速模式决策算法。这些算法中的许多算法都利用了运动和视频内容分类的优势,以减少在模式决策过程中尝试的模式数量。当用于具有高运动或详细视觉信息的视频序列时,由于分类不完善,视频编码效率可能会大大降低。本文提出了一种有效的基于概率的宏块模式选择(PBMMS)算法。根据空间和特殊相关性,将每个MB预测为具有不同概率的MB,从而可以节省50-60%的计算量,并且与现有的H.264快速模式决策算法相比,压缩性能有所提高。

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