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A Fast Mode Decision Algorithm Using Hierarchical and Skip Methods for Intra Prediction in HEVC

机译:HEVC中基于层次和跳过方法的帧内预测快速模式决策算法

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This paper proposes an adaptive fast mode decision (AFMD) algorithm for intra prediction in high efficiency video coding (HEVC) using hierarchical and skip methods. AFMD consists of two phases: an adaptive hierarchical mode decision and an adaptive rate-distortion optimization. The proposed AFMD focuses mainly on reducing the number of prediction modes, and thus it can decrease computation time. For rough mode decision and rate-distortion optimization, AFMD computes candidate modes in a way that includes only those intra modes that are most promising. In our experiments, AFMD shows times saving of 41.5% and 40.58% compared to the HEVC test model (HM) reference software, versions 14.0 and 16.0. In addition, the proposed algorithm increases the Bjontegaard delta bitrate by only about 1.00% and 0.93% compared to HM 14.0 and HM 16.0.
机译:提出了一种使用分层和跳过方法的高效视频编码(HEVC)帧内预测的自适应快速模式决策(AFMD)算法。 AFMD由两个阶段组成:自适应分层模式决策和自适应速率失真优化。提出的AFMD主要集中在减少预测模式的数量上,因此可以减少计算时间。对于粗略模式决策和速率失真优化,AFMD以仅包括最有前途的那些内部模式的方式计算候选模式。在我们的实验中,与14.0和16.0版的HEVC测试模型(HM)参考软件相比,AFMD节省了41.5%和40.58%的时间。此外,与HM 14.0和HM 16.0相比,提出的算法仅将Bjontegaard增量比特率提高了约1.00%和0.93%。

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