*3.2. Visual Difference Predictor*

HDR-VDP is a visual metric that compares a pair of images and predicts their visibility (the probability of the differences between the images) and quality (the quality degradation with the respect to the reference image). In this paper, Mantiuk et al.'s HDR-VDP-2 [23] is adopted to evaluate our re-coloring technique and Kuhn's method. HDR-VDP-2 is a major revision which improves the accuracy of the prediction and changes the metric to predict the visibility (detection/discrimination) and image quality (mean-opinion-score). The new metric also models Long-, Middle-, Short-cone and rod sensitivities for different spectral characteristics of the incoming light. As shown in Figure 16, the first and fourth rows are two test images and their CVD simulation. The images from the left to the right are the original images, CVD simulation results using our re-coloring technique and the results obtained from Kuhn's method. The second and fifth rows are the RMS values with *k* = 11. The higher value of RMS is displayed in a deeper blue color, and the low value is displayed in a white color. The third and sixth rows are the visibility test results using HDR-VDP-2. The probability of detection map tells us how likely we will notice the difference between two images. Red color denotes the high probability and green color indicates a low probability. Finally, as shown in the second and fifth rows, the distribution of our results and Kuhn's are almost the same. However, the third and sixth rows indicate that our re-coloring technique is able to provide more distinguishable colors on the CVD simulation results.
