基于虚拟视图和低秩矩阵恢复的视点间预测OACSTPCD
Inter-view Prediction Based on Virtual-view and Low-rank Matrix Recovery
新一代的多视点视频格式引入了深度图用于虚拟视图的合成.为了能充分利用深度信息,进一步提高多视点视频的压缩效率,本文提出一种基于虚拟视图和低秩矩阵恢复的视点间预测方法.首先利用深度图和相邻视点合成虚拟视图,当编码一个宏块时,利用虚拟视图中的对应块作为参考到相邻视图中寻找若干相似块,最后利用低秩矩阵恢复进行处理,以降低噪声.实验结果表明,该方法比JMVC(Joint Multi-view Video Coding)原有的视点间预测方法节省大约2％的码率.
The new generation of multi-view video introduced depth map for virtual view synthesis.In order to make full use of the depth information and improve the compression efficiency,this paper presents a prediction method based on the virtual view and low-rank matrix recovery.First,the paper generates the virtual view by the adjacent views and depth maps,and then searches for several matching blocks from adjacent views using the corresponding block of virtual vie…查看全部>>
刘如意
北京工业大学计算机学院,北京100124
信息技术与安全科学
视频编码多视点视频虚拟视图合成低秩矩阵恢复
video coding multi-view video virtual view synthesis low-rank matrix recovery
《计算机与现代化》 2013 (8)
19-22,4
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