北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2016, Vol. 39 ›› Issue (5): 110-115.doi: 10.13190/j.jbupt.2016.05.022

• 研究报告 • 上一篇    下一篇

基于结构分析的感知视频信号压缩方法

叶锋1,2,3, 李承欣1, 许力1, 陈家祯1, 门爱东3   

  1. 1. 福建师范大学 数学与计算机科学学院, 福州 350007;
    2. 福建星网锐捷通讯股份有限公司 通讯产品研究院, 福州 350002;
    3. 北京邮电大学 多媒体中心, 北京 100876
  • 收稿日期:2016-04-16 出版日期:2016-10-28 发布日期:2016-12-02
  • 作者简介:叶锋(1978-),男,博士,硕士生导师,E-mail:yefeng@fjnu.edu.cn.
  • 基金资助:
    国家自然科学基金项目(61271190,U1405255,61671077);福建省教育厅项目(JA15136)

Perceptual Video Signal Compression Method Based on Structure Analysis

YE Feng1,2,3, LI Cheng-xin1, XU Li1, CHEN Jia-zhen1, MEN Ai-dong3   

  1. 1. School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China;
    2. Fujian STAR-NET Communications Company, Ltd, Fuzhou 350007, China;
    3. Multimedia Center, Beijing University of Posts and Telecommunication, Beijing 100876, China
  • Received:2016-04-16 Online:2016-10-28 Published:2016-12-02

摘要: 针对视频中的视觉感知冗余,提出一种面向视频编码的基于结构分析的感知信号处理模型——结构显著性最小可觉察失真模型.先分策略获取视频帧的有序/无序结构分量和纹理分量进行最小可觉察失真(JND)建模;使用无序结构分量的结构不确定性调节视频帧的显著性区域和JND的对比度掩蔽效应;最后,基于该模型的感知滤波模块被嵌入HEVC中.实验结果表明,在主观视觉感知没有明显损失的情况下,所提出方法的平均码率比HEVC的编码软件HM16.0减少了10.3%.

关键词: 最小可觉察失真, 显著性, 信号处理, 感知冗余

Abstract: In order to remove the visual perceptual redundancy, a new perceptual video signal processing model based on structure analysis combined with saliency just noticeable distortion (SSJ) was proposed. First, the order structure component, disorderly structure component and texture component can be estimated by some method, which are used to just noticeable distortion (JND) model. Then the disorderly structure uncertainty of disorderly structure component is available to adjust saliency regions of frames and contrast masking. Finally, The SSJ model is incorporated into HEVC software HM 16.0 via the adaptive perception signal process. Experiments show that 10.3% bitrate reduction is achieved in the proposed system compared with HM 16.0 without jeopardizing the perceptual quality.

Key words: just noticeable distortion, saliency, signal processing, perceptual redundancy

中图分类号: