Code of reference methods
SCN: Wang et al., 2015, Deep Networks for Image Super-Resolution with Sparse Prior, ICCV 2015.
SRCNN: Dong et al., 2014, Learning a Deep Convolutional Network for Image Super-Resolution, ECCV 2014.
SelfExSR: Huang et al., 2015, Single Image Super-Resolution from Transformed Self-Exemplars, CVPR 2015.
A+: Timofte et al., 2014, A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution, ACCV 2014.
Quantitative evaluation
PSNR, SSIM, and IFC criteria can be found in the SelfExSR method's website.
This function computes the three above criteria (only for luminance).
This function illustrates how to use these criteria to evaluate the results of various SR methods.