Objective and subjective evaluation of High Dynamic Range video compression

R Mukherjee, K Debattista, T Bashford-Rogers, Peter Vangorp, R Mantiuk, M Bessa, B Waterfield, A Chalmers

Research output: Contribution to journalArticle

24 Citations (Scopus)
119 Downloads (Pure)

Abstract

A number of High Dynamic Range (HDR) video compression algorithms proposed to date have either been developed in isolation or only-partially compared with each other. Previous evaluations were conducted using quality assessment error metrics, which for the most part were developed for qualitative assessment of Low Dynamic Range (LDR) videos. This paper presents a comprehensive objective and subjective evaluation conducted with six published HDR video compression algorithms. The objective evaluation was undertaken on a large set of 39 HDR video sequences using seven numerical error metrics namely: PSNR, logPSNR, puPSNR, puSSIM, Weber MSE, HDR-VDP and HDRVQM. The subjective evaluation involved six short-listed sequences and two ranking-based subjective experiments with hidden reference at two different output bitrates with 32 participants each, who were tasked to rank distorted HDR video footage compared to an uncompressed version of the same footage. Results suggest a strong correlation between the objective and subjective evaluation. Also, non-backward compatible compression algorithms appear to perform better at lower output bit rates than backward compatible algorithms across the settings used in this evaluation.
Original languageEnglish
Pages (from-to)426-437
Number of pages12
JournalSignal Processing: Image Communication
Volume47
Early online date3 Aug 2016
DOIs
Publication statusPublished - 1 Sep 2016

Keywords

  • HDR video
  • Compression algorithm
  • Quality assessment
  • Ranking
  • Ratedistortion

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    Mukherjee, R., Debattista, K., Bashford-Rogers, T., Vangorp, P., Mantiuk, R., Bessa, M., Waterfield, B., & Chalmers, A. (2016). Objective and subjective evaluation of High Dynamic Range video compression. Signal Processing: Image Communication, 47, 426-437. https://doi.org/10.1016/j.image.2016.08.001