Image quality assessment: from error visibility to structural similarity

@article{citeulike:1029271, 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/.}, author = {Wang, Zhou and Bovik, A. C. and Sheikh, H. R. and Simoncelli, E. P. }, citeulike-article-id = {1029271}, doi = {10.1109/TIP.2003.819861}, journal = {Image Processing, IEEE Transactions on}, keywords = {image, quality}, number = {4}, pages = {600--612}, posted-at = {2007-01-08 01:49:33}, priority = {2}, title = {Image quality assessment: from error visibility to structural similarity}, url = {http://dx.doi.org/10.1109/TIP.2003.819861}, volume = {13}, year = {2004} }

TY - JOUR ID - citeulike:1029271 L3 - citeulike-article-id:1029271 TI - Image quality assessment: from error visibility to structural similarity JF - Image Processing, IEEE Transactions on VL - 13 IS - 4 SP - 600 EP - 612 N2 - 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/. KW - image KW - quality AU - Wang, Zhou AU - Bovik, AC AU - Sheikh, HR AU - Simoncelli, EP PY - 2004/// UR - http://dx.doi.org/10.1109/TIP.2003.819861 ER -