基于图像定位的合适匹配单元的运动估计全搜索算法的无损计算缩减

Proceedings International Conference on Information Technology: Coding and Computing Pub Date : 2001-04-02 DOI:10.1109/ITCC.2001.918837

Jong-Nam Kim, Byung-Ha Ahn

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引用次数: 2

摘要

为了减少全搜索(FS)算法在快速运动估计中的计算量，我们提出了一种新的快速匹配算法，该算法不会像传统的FS算法那样降低预测图像的质量。在预测图像中没有任何退化的计算量减少来自于快速去除不可能的运动向量。我们利用图像数据中复杂区域定位的有效匹配单元，更快地去除不适当的运动向量。本文给出了运动估计中块匹配的三个特性。实验结果表明，与传统的快速匹配扫描算法相比，该算法减少了约30%的不必要的计算量。

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Lossless computational reduction of full search algorithm in motion estimation using appropriate matching unit from image localization

To reduce the amount of computation of the full search (FS) algorithm for fast motion estimation, we propose a new and fast matching algorithm without degradation of predicted images as in conventional FS. The computational reduction without any degradation in the predicted image comes from fast removal of impossible motion vectors. We obtain faster removal of inappropriate motion vectors using efficient matching units from the localization of complex area in image data. In this paper, we show three properties in block matching of motion estimation. Experimentally, we reduce unnecessary computations by about 30% with our algorithm compared with the conventional fast matching scan algorithm.

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Proceedings International Conference on Information Technology: Coding and Computing

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