See the gallery of stimuli.
This data set was measured for comprehensive testing of visual models using actual distortions and complex images. The distortions are white-noise, JPEG compression artifacts, bilinear upsampling (blurring), and sine-gratings. All distortions are restricted to a small image regions to simplify the measurements.
The thresholds were measured in the 4-alternative-forced-choice experiment, in which all four images were shown side-by-side. The measurement procedure was the same as for the "Contrast sensitivity for wide luminance range" data set.
This is the Visual Difference Predictor for High Dynamic Range Images, C++ implementation from http://www.mpi-inf.mpg.de/resources/hdr/vdp/index.html, version 1.7
The metric is an extension of the VDP'93 metric that can better handle high dynamic range images. HDR-VDP includes, in addition to the VDP'93 feature set, a model of glare (intra-occular light scatter), photoreceptor response (single luminance channel) and the CSF that adapts locally to the pixel luminance.
The algorithm is described in: R. Mantiuk, S. Daly, K. Myszkowski, and H.P. Seidel. "Predicting visible differences in high dynamic range images: model and its calibration." In Human Vision and Electronic Imaging, 204-214, 2005.