The goal of this work is to present and review two new image difference metrics, named SDOG – CIELAB and SDOG – DEE. These metrics are along the same lines as the standard SCIELAB metric (Zhang and Wandell, 1997), modified to include a pyramidal subsampling, the Difference of Gaussians receptivefield model (DOG) (Tadmor and Tolhurst, 2000), and the ΔEE color-difference formula (Oleari et al., 2009). The DOG model and the ΔEE formula have been shown to improve respectively contrast measures and image quality metrics (Simone et al., 2009). Extensive testing using 29 state-of-the-art metrics and six image databases has been performed. Although this new approach is promising, we only find weak evidence of effectiveness. Analysis of the results indicates that the metrics show fairly good correlations over particular test images, yet they do not outperform the most common objective quality measures.
Sebastien A. Ajagamelle, Marius Pedersen, Gabriele Simone, "Analysis of the Difference of Gaussians Model in Image Difference Metrics" in Proc. IS&T CGIV 2010/MCS'10 5th European Conf. on Colour in Graphics, Imaging, and Vision 12th Int'l Symp. on Multispectral Colour Science, 2010, pp 489 - 496, https://doi.org/10.2352/CGIV.2010.5.1.art00076