Physics

Image compression

Pattern recognition (psychology)

Neuroscience

JPEG

Discrete cosine transform

Perception

JPEG 2000

Biology

Image (mathematics)

Similarity (geometry)

Optics

Visibility

Structural similarity

Transform coding

Artificial intelligence

Human visual system model

Set (abstract data type)

Programming language

Visualization

Computer science

Computer vision

Image quality

Image processing

IEEE Transactions on Image Processing

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/.

Image Quality Assessment: From Error Visibility to Structural Similarity