华南理工大学学报(自然科学版) ›› 2009, Vol. 37 ›› Issue (10): 44-48,65.

• 电子、通信与自动控制 • 上一篇    下一篇

基于率失真优化的AVS-M关键参考帧选择算法

张庆明 彭强 代志刚   

  1. 西南交通大学 信息科学与技术学院, 四川 成都 610031
  • 收稿日期:2008-12-16 修回日期:2009-03-20 出版日期:2009-10-25 发布日期:2009-10-25
  • 通信作者: 张庆明(1975-),男,博士生,主要从事视频压缩编码及传输控制、图像处理等方面研究. E-mail:zh.qingming@163.com
  • 作者简介:张庆明(1975-),男,博士生,主要从事视频压缩编码及传输控制、图像处理等方面研究.
  • 基金资助:

    国家自然科学基金资助项目(60672099);

Selection Algorithms of Key Reference Pictures for AVS-M Based on Rate-Distortion Optimization

Zhang Qing-ming  Peng Qiang  Dai Zhi-gang   

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
  • Received:2008-12-16 Revised:2009-03-20 Online:2009-10-25 Published:2009-10-25
  • Contact: 张庆明(1975-),男,博士生,主要从事视频压缩编码及传输控制、图像处理等方面研究. E-mail:zh.qingming@163.com
  • About author:张庆明(1975-),男,博士生,主要从事视频压缩编码及传输控制、图像处理等方面研究.
  • Supported by:

    国家自然科学基金资助项目(60672099);

摘要: AVS—M标准的差错控制技术简单,差错恢复效果不理想.文中从像素级对AVS—M视频编码传输过程中的端到端失真进行了分析,将一种传输失真度估算模型和传统率失真优化准则相结合,形成一种率失真优化模型.利用此模型实现了一种无反馈关键参考帧选择算法,提出一种在有反馈信道条件下的有反馈关键参考帧选择算法.实验结果表明:采用的失真度估计模型能够较精确地估计出端到端的失真度;在3%-20%丢包率下,无反馈和有反馈关键参考帧选择方法较AVS-M标准的Y-PSNR值分别提高了1.9—6.4dB和2.7—10.9dB,有效提高了AVS-M视频传输的抗差错性能.

关键词: 视频编码, 差错恢复, 率失真优化, 端到端失真, 参考帧选择

Abstract:

The error resilience of AVS-M can not achieve desirable results because the adopted error control technology is too simple. In order to solve this problem, the end-to-end error propagation distortion in AVS-M video encoding and transmission is investigated at a precision level of pixel, and a non-feedback key reference picture selection (KRPS) algorithm is realized, based on the rate-distortion optimization model which combines the general transmission distortion estimation model with the rate-distortion optimization (RDO) rule. Then, a feedback KRPS algorithm is proposed based on the non-feedback KRPS. Experimental results indicate that the adopted distortion estimation model can accurately estimate the end-to-end distortion, and that, as compared with the algorithm of AVS-M, the non-feedback and the feedback KRPS algorithms respectively result in the Y-PSNR gains of 1.9 -6. 4dB and 2. 7 ~ 10. 9dB, at a packet loss rate varying from 3% to 20%. It is thus concluded that the two proposed algorithms effectively improve the performance of error resilience in AVS-M video encoding.

Key words: video coding, error resilience, rate-distortion optimization, end-to-end distortion, reference picture selection