An evaluation of quality metrics for compressed images based on human visual sensitivity

It is generally believed that the performance of current image coding techniques is not close enough to the fundamental limit on the bit rate at which high reception quality is maintained. For supporting the future applications that demand high image quality at very low bit rates, more efficient coding algorithms are expected. Among numerous approaches to reach this optimality, perceptual coding that matches the compression algorithm to the human perception mechanism has been considered as the most promising solution, and has recently become an important area of research. In addition to the investigation on perceptual coding, the need for a distortion metric for predicting the distortion has long been recognized in the image processing community. For still image evaluation, several distortion measures tied to some psycho-visual properties have been proposed. Examples of such measures are to be found in the literature. One significant problem associated with these metrics is that there is little information on how these measures perform in comparison to one another. The purpose of this paper is to provide a rigorous evaluation of four metrics which are designed for the evaluation of coded achromatic still images