Image quality assessment: from error visibility to structural similarity¶
Authors: Zhou Wang, A.C. Bovik, H.R. Sheikh, E.P. Simoncelli
Published: 2004 (Journal Paper)
Source: IEEE Transactions on Image Processing
Algorithm: SSIM
DOI: 10.1109/TIP.2003.819861
Summary¶
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.