%0 Journal Article %1 2004-wang %A Wang, Zhou %A Bovik, A.C. %A Sheikh, H.R. %A Simoncelli, E.P. %D 2004 %J IEEE Transactions on Image Processing %K SSIM loss similarity structural %N 4 %P 600-612 %R 10.1109/TIP.2003.819861 %T Image quality assessment: from error visibility to structural similarity %U https://ieeexplore.ieee.org/document/1284395/ %V 13 %X 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. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.

@article{2004-wang, 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. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.}, added-at = {2021-07-06T20:42:49.000+0200}, author = {Wang, Zhou and Bovik, A.C. and Sheikh, H.R. and Simoncelli, E.P.}, biburl = {https://www.bibsonomy.org/bibtex/2a4513384c4da673333b646442d56f07a/pkoch}, doi = {10.1109/TIP.2003.819861}, interhash = {a9295a0c832f5872ef7509f19af0c2da}, intrahash = {a4513384c4da673333b646442d56f07a}, issn = {1941-0042}, journal = {IEEE Transactions on Image Processing}, keywords = {SSIM loss similarity structural}, month = {April}, number = 4, pages = {600-612}, timestamp = {2021-07-06T20:55:30.000+0200}, title = {Image quality assessment: from error visibility to structural similarity}, url = {https://ieeexplore.ieee.org/document/1284395/}, volume = 13, year = 2004 }