ABSTRACT
This chapter presents structural similarity as an alternative design philosophy for objective image quality assessment methods. It discusses the motivation, the general idea, and a specific structural similarity (SSIM) index algorithm of the structural similarity-based image quality assessment method. Many image quality assessment algorithms have been shown to behave consistently when applied to distorted images created from the same original image, using the same type of distortions. The SSIM indexing algorithm is quite encouraging not only because it achieves good quality prediction accuracy in the current tests, but also because of its simple formulation and low complexity implementation. The principal hypothesis of structural similarity based image quality assessment is that the human visual system is highly adapted to extract structural information from the visual field, and therefore a measurement of structural similarity should provide a good approximation to perceived image quality.
