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Highly efficient predictive zonal algorithms for fast block-matching motion estimation

机译:高效的预测区域算法,用于快速块匹配运动估计

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摘要

Motion estimation (ME) is an important part of any video encoding system since it could significantly affect the output quality of an encoded sequence. Unfortunately, this feature requires a significant part of the encoding time especially when using the straightforward full search (FS) algorithm. We propose two techniques, the generalized motion vector (MV) predictor and the adaptive threshold calculation, that can be used to significantly improve the performance of many existing fast ME algorithms. In particular, we apply them to create two new algorithms, named advanced predictive diamond zonal search and predictive MV field adaptive search technique, respectively, which can considerably reduce, if not essentially remove, the computational cost of ME at the encoder, while at the same time give similar, and in many cases better, visual quality with the brute force full search algorithm. The proposed algorithms mainly rely upon very robust and reliable predictive techniques and early termination criteria with parameters adapted to the local characteristics combined with the zonal based patterns. Our experiments verify the considerable superiority of the proposed algorithms versus the performance of possibly all other known fast algorithms, and FS.
机译:运动估计(ME)是任何视频编码系统的重要组成部分,因为它可能会严重影响编码序列的输出质量。不幸的是,此功能需要大量的编码时间,尤其是在使用简单的完全搜索(FS)算法时。我们提出了两种技术,广义运动矢量(MV)预测器和自适应阈值计算,可用于显着提高许多现有快速ME算法的性能。特别是,我们将它们应用于创建两个新算法,分别称为高级预测菱形区域搜索和预测MV场自适应搜索技术,它们可以显着降低(如果不是从根本上消除的话)编码器上ME的计算成本,而同时使用蛮力完全搜索算法提供相似且在许多情况下更好的视觉质量。所提出的算法主要依靠非常健壮和可靠的预测技术以及具有适合于局部特征的参数的早期终止标准,并结合基于区域的模式。我们的实验证明了所提出算法的可观优势优于可能的所有其他已知快速算法和FS的性能。

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