A NEW JOINT RATE-DISTORTION OPTIMIZATION MODEL BASED ON TEXTURE AND MEAN-ERROR FACTORS

摘要：

In this paper, a new joint Rate-distortion Optimization model based on texture and mean-error factors (TMJRDM) is proposed. Texture factor implies the subjective factor, giving the texture similarity measure between the original image and the target image. At the same time, mean-error factor gives the objective measure. The joint weighted value of texture and mean-error factors is calculated as the distortion metric, which balances the subjective and objective quality. Experimental results show that our proposed algorithm improves the subjective quality of the reconstructed images without obvious degradation of the objective quality.

关键词： mode decision motion estimation Ratedistortion Optimization (RDO) tezture factor

作者: Qingqing Meng Bojin Zhuang Fei Su

作者单位: School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Network Infrastructure and Digital Content(2009年IEEE网络基础设施与数字内容国际会议 IEEE IC-NIDC2009)

会议地点: 北京

会议语种:英文

页码: 661-665

在线出版日期: 2009-11-06（万方平台首次上网日期，不代表论文的发表时间）