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Fast motion estimation algorithm for H.264/AVC based on centered prediction

机译:基于中心预测的H.264 / AVC快速运动估计算法

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H.264/AVC video coding standard can achieve roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality. However, this comes at a cost in considerably increased complexity at the encoder and thus increases the difficulty in hardware implementation. The high redundancy that exists between the successive frames of a video sequence makes it possible to achieve a high data compression ratio. Motion estimation (ME) plays an important role in motion compensated video coding. A fast motion estimation algorithm for H.264/AVC is proposed based on centered prediction, called centered prediction based fast mixed search algorithm (CPFMS). It makes use of the spatial and temporal correlation in motion vector (MV) fields and feature of all-zero blocks to accelerate the searching process. With the initialized searching point prediction, adaptive search window changing and searching direction decision, CPFMS is provided to reduce computation in block-matching process. The experimental results show that the speed of CPFMS is nearly 12 times of FS with a negligible peak signal-noise ratio (PSNR) loss. Also, the efficiency of CPFMS outperforms some popular fast algorithms such as hybrid unsymmetrical cross multi-hexagongrid search and a novel multidirectional gradient descent search evidently.
机译:对于给定的质量,H.264 / AVC视频编码标准可以实现比MPEG2和MPEG4大约一半的位节省。但是,这以在编码器处的复杂性显着增加为代价,并因此增加了硬件实现的难度。视频序列的连续帧之间存在的高冗余度使得可以实现高数据压缩率。运动估计(ME)在运动补偿视频编码中起着重要作用。提出了一种基于中心预测的H.264 / AVC快速运动估计算法,称为基于中心预测的快速混合搜索算法(CPFMS)。它利用运动矢量(MV)字段中的空间和时间相关性以及全零块的特征来加快搜索过程。通过初始化搜索点预测,自适应搜索窗口更改和搜索方向决策,提供了CPFMS以减少块匹配过程中的计算。实验结果表明,CPFMS的速度是FS的近12倍,峰值信噪比(PSNR)损失可忽略不计。而且,CPFMS的效率明显优于一些流行的快速算法,例如混合非对称交叉六边形搜索和新颖的多方向梯度下降搜索。

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