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Proceedings Paper

Crowdsourcing evaluation of high dynamic range image compression
Author(s): Philippe Hanhart; Pavel Korshunov; Touradj Ebrahimi
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Paper Abstract

Crowdsourcing is becoming a popular cost effective alternative to lab-based evaluations for subjective quality assessment. However, crowd-based evaluations are constrained by the limited availability of display devices used by typical online workers, which makes the evaluation of high dynamic range (HDR) content a challenging task. In this paper, we investigate the feasibility of using low dynamic range versions of original HDR content obtained with tone mapping operators (TMOs) in crowdsourcing evaluations. We conducted two crowdsourcing experiments by employing workers from Microworkers platform. In the first experiment, we evaluate five HDR images encoded at different bit rates with the upcoming JPEG XT coding standard. To find best suitable TMO, we create eleven tone-mapped versions of these five HDR images by using eleven different TMOs. The crowdsourcing results are compared to a reference ground truth obtained via a subjective assessment of the same HDR images on a Dolby `Pulsar' HDR monitor in a laboratory environment. The second crowdsourcing evaluation uses semantic differentiators to better understand the characteristics of eleven different TMOs. The crowdsourcing evaluations show that some TMOs are more suitable for evaluation of HDR image compression.

Paper Details

Date Published: 23 September 2014
PDF: 12 pages
Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 92170D (23 September 2014); doi: 10.1117/12.2065560
Show Author Affiliations
Philippe Hanhart, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Pavel Korshunov, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Touradj Ebrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)


Published in SPIE Proceedings Vol. 9217:
Applications of Digital Image Processing XXXVII
Andrew G. Tescher, Editor(s)

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