Advertisement

High Dynamic Range Visual Quality of Experience Measurement: Challenges and Perspectives

  • Manish Narwaria
  • Matthieu Perreira Da SilvaEmail author
  • Patrick Le Callet
Chapter

Abstract

Traditional capture and display devices can only support a limited dynamic range (contrast) and color gamut given the hardware limitations. As a result, the real physical luminance present in a natural scene cannot be captured by these. However, with the recent advancements in the related software and hardware technologies, it is now possible to capture or reproduce higher contrast and luminance ranges. Such scene-referred visual signals are known as high dynamic range (HDR) signals. They are visually more appealing because they can represent the dynamic range of the visual stimuli present in the real world more accurately. Not surprisingly, the emergence of HDR is seen as an important step towards improving the visual quality of experience (QoE) of the end users. However, HDR comes with its own set of challenges including capture, storage, processing, display, and so on. This chapter focuses on some of those issues from a QoE viewpoint.

Keywords

Visual Quality Human Visual System High Dynamic Range Tone Mapping Tone Mapping Operator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Yoshida A., Blanz V., Myszkowski K., and Seidel H. Perceptual evaluation of tone mapping operators with real-world scenes. In Proceedings of SPIE Human Vision & Electronic Imaging X, pages 192–203, San Jose, CA, USA, 2005.Google Scholar
  2. 2.
    Industrial Light & Magic (2008) OpenEXR. Available at: http://www.openexr.com.
  3. 3.
    SIM2 MULTIMEDIA Available at: http://www.sim2.com/HDR/.
  4. 4.
    Spheron HDR VR. Available at: http://www.spheron.com/home.html.
  5. 5.
    Guthier B. Real-time algorithms for high dynamic range video. PhD. Thesis, 2012.Google Scholar
  6. 6.
    Reinhard E., Stark M., Shirley P., and Ferwerda J. Photographic tone reproduction for digital images. ACM Transactions on Graphics (TOG), 21(3):267–276, July 2002.CrossRefGoogle Scholar
  7. 7.
    Banterle F., Artusi A., Debattista K., and Chalmers A. Advanced High Dynamic Range Imaging: Theory and Practice. AK Peters (CRC Press), Natrick, MA, USA, 2011.Google Scholar
  8. 8.
    Banterle F., Debattista K., Artusi A., Pattanaik S., Myszkowski K., Ledda P., and Chalmers A. High dynamic range imaging and low dynamic range expansion for generating HDR content. Computer Graphics Forum, 28(8):3243–2367, December 2009.CrossRefGoogle Scholar
  9. 9.
    Drago F., Myszkowski K., Annen T., and Chiba N. Adaptive logarithmic mapping for displaying high contrast scenes. Computer Graphics Forum, 22(3):419–426, September 2003.CrossRefGoogle Scholar
  10. 10.
    Drago F., Martens W., Myszkowski K., and Seidel H. Perceptual evaluation of tone mapping operators. In Procedings of ACM SIGGRAPH 2003 Sketches & Applications, pages 1–1. ACM Press, 2003.Google Scholar
  11. 11.
    Durand F. and Dorsey J. Fast bilateral filtering for the display of high-dynamic-range images. ACM Transactions on Graphics (TOG), 21(3):257–266, July 2002.CrossRefGoogle Scholar
  12. 12.
    Eilertsen G., Wanat R., Mantiuk R., and Unger J. Evaluation of tone mapping operators for HDR-video. Computer Graphics Forum, 32(7):275–284, October 2013.CrossRefGoogle Scholar
  13. 13.
    Mather G. Foundations of Perception. Psychology Press, Hove, East Sussex, 2006.Google Scholar
  14. 14.
    Ward G. Real pixels. In Graphic Gems II, pages 80–83. Academic Press, 1991.Google Scholar
  15. 15.
    Ward G. A contrast-based scalefactor for luminance display. In Graphic Gems IV, pages 415–421. Academic Press, 1994.Google Scholar
  16. 16.
    Ward G. The LogLuv encoding for full gamut, high dynamic range images. Journal of Graphics Tools, 3(1):15–31, March 1998.CrossRefGoogle Scholar
  17. 17.
    Ward G. and Simmons M. JPEG-HDR: A backwards-compatible high dynamic range extension to jpeg. In ACM SIGGRAPH 2006 Courses, 2006.Google Scholar
  18. 18.
    Seetzen H., Heidrich W., Stuerzlinger W., Ward G., Whitehead L., Trentacoste M., Ghosh A., and Vorozcovs A. High dynamic range display systems. ACM Transactions on Graphics (TOG), 23(3):760–768, August 2004.CrossRefGoogle Scholar
  19. 19.
    Kuang J., Johnson G., and Fairchild M. iCAM06: A refined image appearance model for hdr image rendering. J. Visual Communication and Image Representation (JVCI), 18(5):406–414, October 2007.Google Scholar
  20. 20.
    Kuang J., Yamaguchi H., Liu C., Johnson G., and Fairchild M. Evaluating hdr rendering algorithms. ACM Transactions on Applied Perception (TAP), 4(2), Article No. 9,July 2007.Google Scholar
  21. 21.
    Tumblin J., Hodgins J., and Guenter B. Two methods for display of high contrast images. ACM Transactions on Graphics (TOG), 18(1):56–94, January 1999.CrossRefGoogle Scholar
  22. 22.
    Chiu K., Herf M., Shirley P., Swamy S., Wang C., and Zimmerman K. Spatially nonuniform scaling functions for high contrast images. In Proceedings of Graphics Interface, pages 245–253, 1993.Google Scholar
  23. 23.
    Ashikhmin M. A tone mapping algorithm for high contrast images. In Proceedings of the 13 th Eurographics workshop on Rendering (EGRW), pages 145–156, 2002.Google Scholar
  24. 24.
    Ashikhmin M. and Goyal J. A reality check for tone-mapping operators. ACM Transactions on Applied Perception (TAP), 3(4):399–411, October 2006.CrossRefGoogle Scholar
  25. 25.
    Cadik M., Wimmer M., Neumann L., and Artusi A. Evaluation of HDR tone mapping methods using essential perceptual attributes. Computers & Graphics, 32(3):330–349, June 2008.CrossRefGoogle Scholar
  26. 26.
    Narwaria M., Silva M., Callet P., and Pepion R. Effect of tone mapping operators on visual attention deployment. In Proceedings of SPIE 8499, Applications of Digital Image Processing XXXV, San Diego, California, USA, 2012.Google Scholar
  27. 27.
    Narwaria M., Silva M., Callet P., and Pepion R. Tone mapping-based high-dynamic-range image compression: study of optimization criterion and perceptual quality. Optical Engineering, 52(10):102008–102008, 2013.CrossRefGoogle Scholar
  28. 28.
    Narwaria M., Silva M., Callet P., and Pepion R. Impact of tone mapping in high dynamic range image compression. In Proceedings of Eighth International Workshop on Video Processing and Quality Metrics for Consumer Electronics (VPQM), Chandler, Arizona, USA, 2014.Google Scholar
  29. 29.
    Narwaria M., Silva M., Callet P., and Pepion R. Tone mapping based hdr compression: Does it affect visual experience? Signal Processing: Image Communication, 29(2):257–273, February 2014.Google Scholar
  30. 30.
    Sugiyama N., Kaida H., Xue X., Jinno T., Adami N., and Okuda M. HDR compression using optimized tone mapping model. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1001–1004, 2009.Google Scholar
  31. 31.
    Ledda P., Chalmers A., Troscianko T., and Seetzen H. Evaluation of tone mapping operators using a high dynamic range display. ACM Transactions on Graphics (TOG), 24(3):640–648, July 2005.CrossRefGoogle Scholar
  32. 32.
    Fattal R., Lischinski D., and Werman M. Gradient domain high dynamic range compression. ACM Transactions on Graphics (TOG), 21(3):249–256, July 2002.CrossRefGoogle Scholar
  33. 33.
    Mantiuk R., Efremov A., Myszkowski K., and Seidel H. Backward compatible high dynamic range MPEG video compression. ACM Transactions on Graphics (TOG), 25(3):713–723, July 2006.CrossRefGoogle Scholar
  34. 34.
    Mantiuk R., Jim K., Rempel A., and Heidrich W. HDR-VDP-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions. ACM Transactions on Graphics (TOG), 30(4), July 2011.Google Scholar
  35. 35.
    Mantiuk R., Myszkowski K., and Seidel H. A perceptual framework for contrast processing of high dynamic range images. ACM Transactions on Applied Perception (TAP), 3(3):267–276, July 2006.Google Scholar
  36. 36.
    Rensink R. Visual attention. In Encyclopedia of Cognitive Science. Nature Publishing Group, London, 2003.Google Scholar
  37. 37.
    Mann S. and Picard R. Being ‘undigitial’ with digital cameras: Extending dynamic range by combining differently exposed pictures. In Proceedings of IS&T 48th Annual Conference, pages 422–428. Society for Imaging Science and Technology, 1995.Google Scholar
  38. 38.
    Aydin T., Mantiuk R., and Seidel H. Extending quality metrics to full luminance range images. In Proceedings of SPIE Human Vision & Electronic Imaging XIII, pages 68060B–68060B–10, San Jose, CA, USA, 2008.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Manish Narwaria
    • 1
  • Matthieu Perreira Da Silva
    • 1
    Email author
  • Patrick Le Callet
    • 1
  1. 1.Lunam University, IRCCyN CNRS UMR 6597, Polytech NantesNantes Cedex 3France

Personalised recommendations