Structural similarity index measure

The structural similarity index measure, called SSIM, is a method for predicting the perceived quality of digital video and images, or for measuring the similarity between two images. It is a full reference metric, which means the quality estimate rests on an initial, uncompressed image used as the reference. SSIM is a perception-based model: it treats image degradation as a perceived change in structural information, the strong interdependencies between pixels that are spatially close, and it also accounts for visual masking by luminance and by contrast. This separates it from techniques such as mean squared error and peak signal-to-noise ratio, which estimate absolute errors instead.