An improved quantitative measure of image restoration quality

The field of image restoration lacks promising comparison vehicle for judging the effectiveness of competing algorithms. By far the most widely adopted quantitative measure of image restoration quality is the SNR improvement. However, we find that the SNR improvement is of low precision, which will adversely hinder it from being a reliable measure. It is also noted that another limitation of the SNR improvement is that it cannot reveal clearly the extent to which the image quality is improved. We devise an alternative measure for quantitative evaluation of image restoration quality. The proposed measure is much more precise than the SNR improvement. Moreover, the proposed measure contains finite and meaningful reference points in its measurements, to provide us with a better insight into the effectiveness of restoration algorithms that under study