A transformation-aware perceptual image metric

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

doi:10.1117/12.2076754

17 March 2015 A transformation-aware perceptual image metric

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

Proceedings Volume 9394, Human Vision and Electronic Imaging XX; 939408 (2015) https://doi.org/10.1117/12.2076754
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

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 indeed 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. 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 novel measure of complexity in a flow field. This representation is then used for applications, such as comparison of non-aligned images, where transformations cause threshold elevation, and detection of salient transformations.

Citation Download Citation

Petr Kellnhofer, Tobias Ritschel, Karol Myszkowski, and Hans-Peter Seidel "A transformation-aware perceptual image metric", Proc. SPIE 9394, Human Vision and Electronic Imaging XX, 939408 (17 March 2015); https://doi.org/10.1117/12.2076754

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