Back to articles
Articles
Volume: 29 | Article ID: art00010
Image
Perceptual Evaluation of Psychovisual Rate-Distortion Enhancement in Video Coding
  DOI :  10.2352/ISSN.2470-1173.2017.14.HVEI-121  Published OnlineJanuary 2017
Abstract

Psychovisual rate-distortion optimization (Psy-RD) has been used in the industrial video coding practice as a tool to improve perceptual video quality. It has earned significant popularity through the wide spread of the open source x264 video encoders, where the Psy-RD option is employed by default. Nevertheless, little work has been dedicated to validate the impact of Psy-RD optimization on perceptual quality, so as to provide meaningful guidance on the practical usage and future development of the idea. In this work, we build a database that contains Psy-RD encoded video sequences at different strength and bitrates. A subjective user study is then conducted to evaluate and compare the quality of the Psy-RD encoded videos. We observe that there is considerable agreement between subjects' opinions on the test video sequences. Unfortunately, the impact of Psy-RD optimization on video quality does not appear to be encouraging. Somewhat surprisingly, the perceptual quality gain of Psy-RD ON versus Psy-RD OFF cases is negative on average. Our results suggest that Psy-RD optimization should be used with caution. Further investigations show that most state-of-the-art full-reference objective quality models correlate well with the subjective experiment results overall. But in terms of the paired comparison between Psy-RD ON and OFF cases, the false alarm rates are moderately high.

Subject Areas :
Views 15
Downloads 2
 articleview.views 15
 articleview.downloads 2
  Cite this article 

Zhengfang Duanmu, Kai Zeng, Zhou Wang, Mahzar Eisapour, "Perceptual Evaluation of Psychovisual Rate-Distortion Enhancement in Video Codingin Proc. IS&T Int’l. Symp. on Electronic Imaging: Human Vision and Electronic Imaging,  2017,  pp 85 - 90,  https://doi.org/10.2352/ISSN.2470-1173.2017.14.HVEI-121

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2017
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology