Evaluating Preference for Images Enhanced with Simple Tone Curves

Bennett, James and Finlayson, Graham D. (2025) Evaluating Preference for Images Enhanced with Simple Tone Curves. In: The 16th Congress of International Colour Association, 2025-10-19 - 2025-10-24. (In Press)

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Abstract

Tone curves are central to camera pipelines and image editing workflows, describing how tonal values are mapped to produce visually appealing images. While tone curves can be arbitrarily complex, recent work has suggested that simple tone curves – defined as monotonic functions with at most one inflexion point – are sufficient to approximate expert adjustments. This raises an important perceptual question of whether human observers prefer images enhanced with simple tone curves. We address this by conducting a psychophysical study on the MIT-Adobe FiveK dataset. Expert tone curves were approximated using a constrained optimisation method from the prior art to derive the best simple curve in the primal domain, and additionally in a logarithmic domain. For each of 24 selected images (drawn from well-, less-well- and poorest-fitted simple curves), we compared four renditions: the unenhanced input, the expert output, the primal-domain simple rendition, and the log-domain simple rendition. Eight naïve observers completed pairwise preference tests under controlled viewing conditions. Our results show that both primal and log-domain simple tone curves produce images with perceptual quality comparable to expert renditions. Observers did not show a significant preference between expert and simple renditions, indicating that simplified curves provide a suitable approximation, with the log-domain simple renditions being marginally favoured. These findings demonstrate that simple tone curves are not only objectively similar but also perceptually competitive to expert renderings, offering a practical alternative to complex expert adjustments in image enhancement.

Item Type:	Conference or Workshop Item (Paper)
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Colour and Imaging Lab
Depositing User:	LivePure Connector
Date Deposited:	03 Oct 2025 16:30
Last Modified:	03 Oct 2025 16:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/100622
DOI:

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