TY  - JOUR
TI  - Image quality assessment: from error visibility to structural similarity
AU  - Zhou Wang
AU  - Alan C. Bovik
AU  - Hamid R. Sheikh
AU  - Eero P. Simoncelli
PY  - 2004
JO  - IEEE Transactions on Image Processing
DO  - 10.1109/tip.2003.819861
UR  - https://doi.org/10.1109/tip.2003.819861
AB  - 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.
ER  -