A distortion measure for image artifacts based on human visual sensitivity

A visual model which gives a distortion measure for coding artifacts in images is presented. Given the original and the reproduced image as inputs, the model output is a numerical value, which quantifies the visibility of error in a region of the reproduced image. The model aims to predict accurately the visibility of the common types of coding artifacts blocking, ringing and blurring. Visual sensitivity to these artifacts is measured using psyche-visual experiments. The sensitivity measures thus obtained are used to derive the visual model which predicts the visibility of error. The final model is tested on real images, and the results show that the error visibility predicted by the model correlates well with the subjective ranking