Transformation-aware perceptual image metric

Petr Kellnhofer; Tobias Ritschel; Karol Myszkowski; Hans-Peter Seidel

doi:10.1117/1.JEI.25.5.053014

21 September 2016 Transformation-aware perceptual image metric

Petr Kellnhofer, Tobias Ritschel, Karol Myszkowski, Hans-Peter Seidel

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Journal of Electronic Imaging, Vol. 25, Issue 5, 053014 (September 2016). https://doi.org/10.1117/1.JEI.25.5.053014

Abstract

Predicting human visual perception has several applications such as compression, rendering, editing, and retargeting. Current approaches, however, ignore the fact that the human visual system compensates for geometric transformations, e.g., we see that an image and a rotated copy are identical. Instead, they will report a large, false-positive difference. At the same time, if the transformations become too strong or too spatially incoherent, comparing two images gets increasingly difficult. Between these two extrema, we propose a system to quantify the effect of transformations, not only on the perception of image differences but also on saliency and motion parallax. To this end, we first fit local homographies to a given optical flow field, and then convert this field into a field of elementary transformations, such as translation, rotation, scaling, and perspective. We conduct a perceptual experiment quantifying the increase of difficulty when compensating for elementary transformations. Transformation entropy is proposed as a measure of complexity in a flow field. This representation is then used for applications, such as comparison of nonaligned images, where transformations cause threshold elevation, detection of salient transformations, and a model of perceived motion parallax. Applications of our approach are a perceptual level-of-detail for real-time rendering and viewpoint selection based on perceived motion parallax.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Petr Kellnhofer, Tobias Ritschel, Karol Myszkowski, and Hans-Peter Seidel "Transformation-aware perceptual image metric," Journal of Electronic Imaging 25(5), 053014 (21 September 2016). https://doi.org/10.1117/1.JEI.25.5.053014

Published: 21 September 2016

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