UNIFYING ANALYSIS OF FULL REFERENCE IMAGE QUALITY ASSESSMENT

This paper studies two increasingly popular paradigms for image quality assessment - Structural SIMilarity (SSIM) metrics and Information Fidelity metrics. The relation of the SSIM metric to Mean Squared Error and Human Visual System (HVS) based models of quality assessment are studied. The SSIM model is shown to be equivalent to models of contrast gain control of the HVS. We study the information theoretic metrics and show that the Information Fidelity Criterion (IFC) is a monotonic function of the structure term of the SSIM index applied in the sub-band filtered domain. Our analysis of the Visual Information Fidelity (VIF) criterion shows that improvements in VIF include incorporation of a contrast comparison, in addition to the structure comparison in IFC. Our analysis attempts to unify quality metrics derived from different first principles and characterize the relative performance of different QA systems.