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Association for Computing Machinery (ACM), ACM Transactions on Applied Perception, 3(3), p. 286-308, 2006

DOI: 10.1145/1166087.1166095

Proceedings of the 2nd symposium on Appied perception in graphics and visualization - APGV '05

DOI: 10.1145/1080402.1080418

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A Perceptual Framework for Contrast Processing of High Dynamic Range Images

Journal article published in 2005 by Rafał Mantiuk ORCID, Karol Myszkowski, Jitendra Malik, Hans-Peter Seidel, Jan J. Koenderink
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This paper is available in a repository.

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Abstract

Image processing often involves an image transformation into a domain that is better correlated with visual perception, such as the wavelet domain, image pyramids, multiscale-contrast representations, contrast in retinex algorithms, and chroma, lightness, and colorfulness predictors in color-appearance models. Many of these transformations are not ideally suited for image processing that significantly modifies an image. For example, the modification of a single band in a multiscale model leads to an unrealistic image with severe halo artifacts. Inspired by gradient domain methods, we derive a framework that imposes constraints on the entire set of contrasts in an image for a full range of spatial frequencies. This way, even severe image modifications do not reverse the polarity of contrast. The strengths of the framework are demonstrated by aggressive contrast enhancement and a visually appealing tone mapping, which does not introduce artifacts. In addition, we perceptually linearize contrast magnitudes using a custom transducer function. The transducer function has been derived especially for the purpose of HDR images, based on the contrast-discrimination measurements for high-contrast stimuli.