New gage for measuring image quality

Image quality measurement is a major challenge in digital image processing field. All image quality methods compare two images by providing a quantitative score that describes the degree of similarity, or in other words, the level of distortion between them. In this work, we propose a new full reference image quality measure using some statistical functions called Copulas. To our knowledge, this is the first time that copulas are used for image quality measurement. Our algorithms use the steerable pyramid technique to decompose the original and the distorted images. Then we exploit some of copula functions properties to calculate the image quality of the distorted image (such as a forged image) with respect to its original. The experimental results of our method show that the effectiveness of our method is comparable or better than the state of the current state of the art methods. In addition, our method is simple and fast.