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Unifying analysis of full reference image quality assessment
K. Seshadrinathan and A. C. Bovik
IEEE International Conference on Image Processing
Abstract
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.
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