Towards high efficiency video coding: Subjective evaluation of potential coding technologies

Francesca De Simone, Lutz Goldmann, Jong Seok Lee, Touradj Ebrahimi

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)

Abstract

This paper describes the details and the results of the subjective quality evaluation performed at EPFL, as a contribution to the effort of the joint collaborative team on video coding (JCT-VC) for the definition of the high efficiency video coding (HEVC) standard. The performance of twenty-seven coding technologies has been evaluated with respect to two H.264/MPEG-4 AVC anchors, for high definition (HD) test material. The test campaign involved a total of 494 naive observers and took place over a period of four weeks. While similar tests have been conducted as part of the standardization process of previous video coding technologies, the test campaign described in this paper is by far the most extensive in the history of video coding standardization. A detailed statistical analysis of the subjective results is provided. The results show high consistency and support an accurate comparison of the performance of the different coding technologies.

Original languageEnglish
Pages (from-to)734-748
Number of pages15
JournalJournal of Visual Communication and Image Representation
Volume22
Issue number8
DOIs
Publication statusPublished - 2011 Nov

Bibliographical note

Funding Information:
The work presented here was partially supported by the European Network of Excellence PetaMedia ( FP7/2007-2011 ) and the Swiss National Foundation for Scientific Research in the framework of NCCR Interactive Multimodal Information Management (IM2). The authors thank Dr. Vittorio Baroncini and the proponents who provided the test material and made this subjective test campaign possible. Also, a special thank goes to Dr. Ulrich Engelke, Dr. Ulrich Reiter, Dr. Junyong You, Mrs. Liyuan Xing, Mrs. Fitri N. Rahayu, and Mr. Christoph Steindl who helped in assisting the test sessions and the subjects who participated with high dedication to the subjective tests.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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