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J4  2014, Vol. 48 Issue (4): 734-741    DOI: 10.3785/j.issn.1008-973X.2014.04.025
电信技术、自动化技术     
基于自适应预选的快速帧间模式选择算法
殷海兵, 徐宁
中国计量学院 信息工程学院,浙江 杭州 310018
Fast inter mode decision algorithm based on intelligent mode preselection with adaptive offset
YIN Hai-bing, XU Ning
College of Information Engineering, China Jiliang University, Hangzhou 310018, China
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摘要:

针对率失真性能和算法复杂度约束,提出基于偏移量自适应模式预选的高效帧间模式选择算法.计算所有可能模式率失真优化关闭判据下的编码代价,对代价进行自适应偏移量调整.基于调整后的代价进行模式预选,选择几种性能可能较优的候选模式,对这些模式进行率失真优化模式选择.由于该算法采用统计分析建模方法,自适应地确定偏移量参数,显著提高了模式预选准确率,较好地平衡了复杂度和算法性能.针对典型视频测试序列进行算法验证.实验表明,与完全率失真优化模式选择算法相比,该算法的复杂度大大降低,视频质量仅存在轻微退化.

Abstract:

An efficient inter mode decision algorithm based on intelligent mode preselection with adaptive offset was proposed under the constraint of complexity and performance trade off. All candidate modes were checked using the RDO-off criterion for mode selection, and some coding modes were preselected with adaptive offset adjustment. Then the preselected modes were checked with the RDO-on mode selection criterion to select the final coding mode. The offset parameters were determined using the adaptive selection mechanism based on the statistics analysis. The adaptive offset parameters improved the accuracy probability of mode preselection. The proposed algorithm was verified with typical test video sequences. Experimental results demonstrate that computation complexity is drastically reduced with little PSNR loss in the proposed algorithm, compared to optimal RDO-on mode decision.

出版日期: 2014-09-03
:  TN 919  
基金资助:

浙江省自然科学基金资助项目(Y1110114, LY12F05007, LY12F01011, LY13H180011);国家“十二五”科技支撑计划资助项目(2013BAH54F04).

作者简介: 殷海兵(1974—),男,教授,从事数字视频压缩算法的研究.E-mail: haibingyin@163.com
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引用本文:

殷海兵, 徐宁. 基于自适应预选的快速帧间模式选择算法[J]. J4, 2014, 48(4): 734-741.

YIN Hai-bing, XU Ning. Fast inter mode decision algorithm based on intelligent mode preselection with adaptive offset. J4, 2014, 48(4): 734-741.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2014.04.025        http://www.zjujournals.com/eng/CN/Y2014/V48/I4/734

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