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SMPTE Meetings and Conferences ( October 2018)
[ACTIVE]

Visual perceptual entropy measure

Metadata

Publisher
SMPTE — White Plains, NY, USA
Doc Type
Conference Paper
Content Type
Original Research
Volume
2018, No. 10, pp. 1–15
Abstract
This paper is about a theoretical framework on perceptual reproduction quality assessment. — Visual perception is the main theme for two approaches on image metrics, visual performance and image quality. Visual performance looks at the perception of standard elementary images, such as gratings, by different observers or by a single observer in different visual conditions; image quality looks at the perception of variations of the same complex scene by a standard observer. — Visual performance, for which Barten proposed a model in 1999, is studying threshold responses in visual perception. For image quality, on the other hand, indexes are built which must evaluate responses to a variety of suprathreshold visual characteristics, attempting to give results as close as possible to human visual perception. — In audiovisual field, all the configurations approved by the creative team must be reproduced in the final viewing. This cannot be measured by visual performance or image quality indexes. A third approach is needed. This may be called perceptual reproduction quality assessment. Visual perception assessment is not measuring defects, per se; it is built to evaluate the perceptual effectiveness of a given scene coding through a given reproduction technology. — It is only dependent on the number of configurations being reproduced by a given theater system relatively to the various configurations reproduced and approved in the review room. As such, it is a statistical measure. It is in fact similar to the definition of relative entropy. One important fact is that this evaluation must include a model of visual perception. — This paper shows how relative entropy, and entropy loss, can be estimated while taking into account the coding transform, the projector performances, maximum light and the characteristics of human visual system. — This scheme is carried easily for monochromatic content. Color, trichromacy, is quite challenging. The size of configurations goes from 2¹² to 2³⁶, around 6 billion configurations. Calculation and memory requirements are huge. Non-linearities are adding complexity leading to calculation of an upper limit only of entropy loss. — Presentation of results is also a challenge. One way to solve this is to process separately lightness and chromatic information. — In summary the main arguments in this paper are: — • Besides image quality and visual performance there is a need for perceptual reproduction quality assessment — • Entropy is the proper statistical estimator to evaluate the perceptual reproduction quality — • Color reproduction quality estimation requires processing lightness and chromatic attributes separately
Publication Date
2018-10-22
DOI
10.5594/M001837
ISBN
Print: 978-1-61482-960-7
Link
https://doi.org/10.5594/M001837
Author(s)
Francois HeltEclairColor, Ymagis, France
Keyword(s)
Entropy, Perception, Sensation, Quality Metrics, PQ
Copyright
© 2018 Society of Motion Picture and Television Engineers, Inc.

Bibliographic Reference(s)

  • Contrast Sensitivity Experiment to Determine the Bit Depth for Digital Cinema [Active]
  • Quality Assessment Framework for Color Conversions and Perception [Active]
  • ISO/CIE 11664-3 [Active]
  • F. Dretske, Perception Knowledge and Belief, Cambridge, United Kingdom: Cambridge University Press, 2000. EXTERNAL
  • L. Naccache, "Visual phenomenal consciouness: a neurological guided tour," in Progress in Brain Research, Vol. 150, Elsevier B. V., 2005, p. Chapter 13. EXTERNAL
  • P. G. J. Barten, Contrast Sensitivity of the Human Eye and its Effcts on Image Quality, EXTERNAL
  • E. C. Weiss, Collected Papers of Charles Sanders Peirce, Harvard: Harvard University Press. EXTERNAL
  • Academy of Motion Picture Arts and Science, «Specification S-2014-004 ACEScg - A Working Space for CGI Render and Compositing,» March 2016. EXTERNAL
  • J. L. Austin, Sense and Sensibilia (ed. G. J. Warnock), Oxford: Clarendon Press, 1962. EXTERNAL
  • R. W. G. Hunt, Measuring Colour, Kingston-upon-Thames, England: Fountain Press, 1998 (Third Edition). EXTERNAL
  • C. A. B. Peacocke, Sense and Content, Oxford: Clarendon Press, 1983. EXTERNAL
  • G. E. M. Anscombe and L. Wiitgenstein, Remarks on Colour, Oxford, Unted Kingdom: Blackwell Publishing, 2007, First published in 1977. EXTERNAL
  • ITU-R, "Report ITU-R BT.2246-1 - The present state of ultra high definition television," ITU, Geneva, 2012. EXTERNAL
  • C. E. Shannon and W. Weaver, The Mathematical Theory of Communication, Urbana and Chicago: University of Illinois Press, 1949,1998. EXTERNAL
  • W. F. Schreiber, Fundamentals of Electronic Imaging Systems, Thrid Edition, Springer-Verlag, 1992. EXTERNAL
  • E. Reinhard and T. Kunkel, "A Reassessment of the Simultaneous Dynamic Range of the Human Visual System," in APGV '10 Proceedings of the 7th Symposium on Applied Perception in Graphics and Visualization, Los Angeles, 2010. EXTERNAL
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Francois Helt; Visual perceptual entropy measure, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7. Available at https://doi.org/10.5594/M001837
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Francois Helt; Visual perceptual entropy measure, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7. Available at https://doi.org/10.5594/M001837

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Francois Helt; Visual perceptual entropy measure, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7. Available at https://doi.org/10.5594/M001837
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<span class="citation">Francois Helt; <cite>Visual perceptual entropy measure</cite>, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7. Available at <a href="https://doi.org/10.5594/M001837" target="_blank" rel="noopener">https://doi.org/10.5594/M001837</a></span>

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Francois Helt; Visual perceptual entropy measure, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7
doi: 10.5594/M001837
url: https://doi.org/10.5594/M001837
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Francois Helt; <cite id="bib-10-5594-m001837">Visual perceptual entropy measure</cite>, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7
<span class="doi">10.5594/M001837</span>
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