Hulusic, Vedad, Debattista, Kurt, Valenzise, Giuseppe and Dufaux, Frédéric (2017) A model of perceived dynamic range for HDR images. Signal Processing: Image Communication, 51 . pp. 26-39. doi:10.1016/j.image.2016.11.005 ISSN 0923-5965.

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Abstract

For High Dynamic Range (HDR) content, the dynamic range of an image is an important characteristic in algorithm design and validation, analysis of aesthetic attributes and content selection. Traditionally, it has been computed as the ratio between the maximum and minimum pixel luminance, a purely objective measure; however, the human visual system's perception of dynamic range is more complex and has been largely neglected in the literature. In this paper, a new methodology for measuring perceived dynamic range (PDR) of chromatic and achromatic HDR images is proposed. PDR can benefit HDR in a number of ways: for evaluating inverse tone mapping operators and HDR compression methods; aesthetically; or as a parameter for content selection in perceptual studies. A subjective study was conducted on a data set of 36 chromatic and achromatic HDR images. Results showed a strong agreement across participants' allocated scores. In addition, a high correlation between ratings of the chromatic and achromatic stimuli was found. Based on the results from a pilot study, five objective measures (pixel-based dynamic range, image key, area of bright regions, contrast and colorfulness) were selected as candidates for a PDR predictor model; two of which have been found to be significant contributors to the model. Our analyses show that this model performs better than individual metrics for both achromatic and chromatic stimuli.

Item Type:	Journal Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH):	Image analysis, High dynamic range imaging
Journal or Publication Title:	Signal Processing: Image Communication
Publisher:	Elsevier
ISSN:	0923-5965
Official Date:	February 2017
Dates:	Date Event February 2017 Published 27 November 2016 Available 25 November 2016 Accepted 12 August 2016 Submitted
Volume:	51
Page Range:	pp. 26-39
DOI:	10.1016/j.image.2016.11.005
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Date of first compliant deposit:	30 November 2016
Date of first compliant Open Access:	7 December 2016
Funder:	Region Ile de France, Royal Society (Great Britain). University Research Fellowship
Grant number:	FUI 4EVER2;

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