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IEEE Trans Image Process. 2004 Apr;13(4):600-12.

Image quality assessment: from error visibility to structural similarity.

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1
Howard Hughes Medical Institute, the Center for Neural Science and the Courant Institute for Mathematical Sciences, New York University, New York, NY 10012, USA. zhouwang@ieee.org

Abstract

Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a Structural Similarity Index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000.

PMID:
15376593
[Indexed for MEDLINE]
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