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A weighted low-rank matrix approximation based template matching scheme for inter-frame prediction

机译:帧间预测的基于加权低秩矩阵近似的模板匹配方案

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In the field of video coding, inter-frame prediction plays an important role in improving compression efficiency. This task is achieved by finding a predictor for each block such that the residual data can be close to zero as much as possible. For recent video coding standards, motion vectors are required for a decoder to locate the predictors during video reconstruction. Block matching algorithms are usually utilized in the stage of motion estimation to find such motion vectors. For decoderside inter-frame predictive coding, proper templates are defined and template matching algorithms are used to produce a predictor for each block such that the overhead information to transmit motion vectors can be avoided. However, the conventional criteria of either block matching or template matching algorithms may lead to the generation of worse predictors. To enhance coding efficiency, a weighted low-rank matrix approximation approach for decoder-side inter-frame prediction is proposed in this paper. By finding dominating block candidates as well as their corresponding importance factors, a predictor for each block is formed. Together with mode decision, the coder can switch to a better mode between the motion compensation by block matching and the proposed template matching scheme which can operate at decoder side.
机译:在视频编码领域,帧间预测在提高压缩效率方面起着重要作用。通过为每个块找到一个预测变量来实现此任务,以使残差数据尽可能接近零。对于最新的视频编码标准,解码器在视频重建期间需要运动矢量来定位预测变量。在运动估计阶段通常利用块匹配算法来找到这样的运动矢量。对于解码器侧帧间预测编码,定义了适当的模板,并且使用模板匹配算法为每个块生成预测器,从而可以避免传输运动矢量的开销信息。但是,块匹配算法或模板匹配算法的常规标准可能会导致产生较差的预测变量。为了提高编码效率,提出了一种用于解码器侧帧间预测的加权低秩矩阵逼近方法。通过找到主要的区块候选者及其对应的重要性因子,可以形成每个区块的预测变量。与模式决定一起,编码器可以在通过块匹配的运动补偿和可以在解码器侧操作的所提出的模板匹配方案之间切换到更好的模式。

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