A new paradigm for designing compressed image quality metric is proposed in this paper, of which the most significant characteristic is the use of mutual information, a key concept in information theory which measures statistical dependence between two random variables, to exploring the degree of similarity of spatial visual information distribution across different frequency bands in image. Visual information used in the calculation of mutual information is extracted by contrast sensitivity function (CSF) and local band-limited contrast definition proposed by E. Peli. Our paradigm is more consistent with human perceptual mechanism comparing with the traditional error-summation based ones. The effectiveness of our image quality assessment paradigm is validated by JPEG & JPEG2000 compressed images at different bit rates and images with various types of noises.