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Fast view prediction for stereo images based on Delaunay triangular mesh model
【摘要】 The view prediction is an important step in stereo/multiview video coding, wherein, disparity estimation (DE) is a key and diffcult operation. DE algorithms usually require enormous computing power. A fast DE algorithm based on Delaunay triangulation (DT) is proposed. First, a flexible and content adaptive DT mesh is established on a target frame by an iterative split-merge algorithm. Second, DE on DT nodes are performed in a three-stage algorithm, which gives the majority of nodes a good estimate of the disparity vectors (DV), by removing unreliable nodes due to occlusion, and forcing the minority of ’problematic nodes’ to be searched again, within their umbrella-shaped polygon, to the best. Finally, the target view is predicted by using affne transformation Experimental results show that the proposed algorithm can give a satisfactory DE with less computational cost.
【Abstract】 The view prediction is an important step in stereo/multiview video coding, wherein, disparity estimation (DE) is a key and diffcult operation. DE algorithms usually require enormous computing power. A fast DE algorithm based on Delaunay triangulation (DT) is proposed. First, a flexible and content adaptive DT mesh is established on a target frame by an iterative split-merge algorithm. Second, DE on DT nodes are performed in a three-stage algorithm, which gives the majority of nodes a good estimate of the disparity vectors (DV), by removing unreliable nodes due to occlusion, and forcing the minority of ‘problematic nodes’ to be searched again, within their umbrella-shaped polygon, to the best. Finally, the target view is predicted by using affne transformation Experimental results show that the proposed algorithm can give a satisfactory DE with less computational cost.
【Key words】 image reconstruction; disparity estimation; view prediction; triangular mesh.;
- 【文献出处】 Journal of Systems Engineering and Electronics ,系统工程与电子技术(英文版) , 编辑部邮箱 ,2009年01期
- 【分类号】TP391.41
- 【下载频次】57