Perceptual similarity between color images using fuzzy metrics

“NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Visual Communication and Image Representation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Visual Communication and Image Representation, [Volume 34, January 2016, Pages 230–235] https://doi.org/10.1016/j.jvcir.2015.04.003 In many applications of the computer vision field measuring the similarity between (color) images is of paramount importance. However, the commonly used pixelwise similarity measures such as Mean Absolute Error, Peak Signal to Noise Ratio, Mean Squared Error or Normalized Color Difference do not match well with perceptual similarity. Recently, it has been proposed a method for gray-scale image similarity that correlates quite well with the perceptual similarity and it has been extended to color images. In this paper we use the basic ideas in this recent work to propose an alternative method based on fuzzy metrics for perceptual color image similarity. Experimental results employing a survey of observations show that the global performance of our proposal is competitive with best state of the art methods and that it shows some advantages in performance for images with low correlation among some image channels. (C) 2015 Elsevier Inc. All rights reserved. Grecova, S.; Morillas Gómez, S. (2016). Perceptual similarity between color images using fuzzy metrics. Journal of Visual Communication and Image Representation. 34:230-235. doi:10.1016/j.jvcir.2015.04.003