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Perceived dynamic range of HDR images with no semantic information

Abstract : Computing dynamic range of high dynamic range (HDR) content is an important procedure when selecting the test material , designing and validating algorithms, or analyzing aesthetic attributes of HDR content. It can be computed on a pixel-based level, measured through subjective tests or predicted using a mathematical model. However, all these methods have certain limitations. This paper investigates whether dynamic range of modeled images with no semantic information, but with the same first order statistics as the original, natural content, is perceived the same as for the corresponding natural images. If so, it would be possible to improve the perceived dynamic range (PDR) pre-dictor model by using additional objective metrics, more suitable for such synthetic content. Within the subjective study, three experiments were conducted with 43 participants. The results show significant correlation between the mean opinion scores for the two image groups. Nevertheless, natural images still seem to provide better cues for evaluation of PDR.
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Contributor : Frédéric Dufaux <>
Submitted on : Friday, January 10, 2020 - 11:48:06 AM
Last modification on : Saturday, May 1, 2021 - 3:50:26 AM
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  • HAL Id : hal-01654136, version 1


Vedad Hulusic, Giuseppe Valenzise, Frederic Dufaux. Perceived dynamic range of HDR images with no semantic information. Human Vision and Electronic Imaging Conference, IS&T International Symposium on Electronic Imaging (EI 2018), Jan 2018, Burlingame, United States. ⟨hal-01654136⟩



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