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. 1
Based on the hypothesis that HVS is highly adapted for extracting structural information from images, structural similarity (SSIM) index is quite attractive, in which the luminance, contrast, and structure information are involved for perceptual quality estimation REF .
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Computer Science Mathematics Medicine