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Arabian Journal for Science and Engineering

, Volume 44, Issue 3, pp 2427–2444 | Cite as

A Comprehensive Study and Performance Evaluation of HDR Video Coding

  • Junaid MirEmail author
  • Dumidu S. Talagala
  • Anil Fernando
  • Hemantha K. Arachchi
Research Article - Electrical Engineering
  • 25 Downloads

Abstract

With production side for the HDR video being standardized, the distribution phase is still in its infancy. Although a number of promising HDR video coding methods exist, the standardization efforts for HDR video distribution are hampered due to limited performance evaluations. This paper addresses this shortcoming by first reviewing the existing HDR video coding methods categorically. A comprehensive performance evaluation is then presented of five state-of-the-art HDR video coding methods, namely HDR-MPEG, HDR10 (PQ), HLG HDR-TV, AdaptRes and SHVC-based coding method. The evaluation was performed on a HDR video dataset considering two HDR display configurations with four objective quality measures including HDR-VDP-2.2 and HDR-VQM quality metrics. The results reveal novel observations regarding two-layer backward-compatible HDR video coding methods indicating that these methods can provide better or similar HDR quality as in single-layer backward-compatible HDR video coding method HLG HDR-TV. Furthermore, HDR10 (PQ), the single-layer method designed for only HDR content delivery, outperforms the other evaluated methods in this work, demonstrating that best HDR quality can be achieved only without the constraint of backward compatibility. Finally, a discrepancy revealed in the performance, in terms of the HDR-VQM metric when compared to the other quality measures, is presented and its implications are discussed.

Keywords

Backward compatibility HDR video coding methods HDR video compression HDR Video distribution Layered coding 

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Notes

Acknowledgements

The authors would like to thank British Broadcast Corporation (BBC) for the insightful, detailed discussions regarding HLG transfer function.

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Copyright information

© King Fahd University of Petroleum & Minerals 2018

Authors and Affiliations

  1. 1.Electrical Engineering DepartmentUniversity of Engineering and Technology TaxilaTaxilaPakistan
  2. 2.Center for Vision Speech and Signal Processing (CVSSP)University of SurreyGuildfordUK

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