PERCEPTUAL VIDEO CODING WITH BLOCK-LEVEL STAIRCASE JUST NOTICEABLE DISTORTION

被引：0
|
作者：
Zhang, Xinyu [1 ,2 ]
Wang, Hanli [1 ,2 ]
Tian, Tao [1 ,2 ]
机构：
[1] Tongji Univ, Dept Comp Sci & Technol, Shanghai, Peoples R China
[2] Tongji Univ, Minist Educ, Key Lab Embedded Syst & Serv Comp, Shanghai, Peoples R China
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2019年
基金：
中国国家自然科学基金; 国家重点研发计划;
关键词：
Perceptual video coding; staircase just noticeable distortion; block-level just noticeable distortion; video compression;
D O I：
10.1109/icip.2019.8803454
中图分类号：
TB8 [摄影技术];
学科分类号：
0804 ;
摘要：
Perceptual video coding (PVC) is able to improve video compression efficiency by employing just noticeable distortion (JND) models. However, there are limitations of conventional JND models on simulating complex human visual system. To address this issue, a novel PVC framework is proposed in this work, in which a JND model based on staircase perceptual characteristics is designed to calculate block-level JND (BLJND) levels and a convolutional neural network based predictive model is developed to predict BLJND levels for video coding. Experimental results demonstrate that the proposed PVC framework is effective and robust in terms of video compression efficiency and subjective video quality.
引用
收藏
页码：4140 / 4144
页数：5
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