Blind image quality assessment without training on human opinion scores
Anish Mittal, Rajiv Soundararajan, Gautam S. Muralidhar, Alan Conrad Bovik, Joydeep Ghosh · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
We propose a family of image quality assessment (IQA) models based on natural scene statistics (NSS), that can predict the subjective quality of a distorted image without reference to a corresponding distortionless image, and without any training results on human opinion scores of distorted images. These `completely blind' models compete well with standard non-blind image quality indices in terms of subjective predictive performance when tested on the large publicly available `LIVE' Image Quality database.