Blind image quality assessment without training on human opinion scores

Anish Mittal; Rajiv Soundararajan; Gautam S. Muralidhar; Alan C. Bovik; Joydeep Ghosh

doi:10.1117/12.981761

14 March 2013 Blind image quality assessment without training on human opinion scores

Anish Mittal, Rajiv Soundararajan, Gautam S. Muralidhar, Alan C. Bovik, Joydeep Ghosh

Proceedings Volume 8651, Human Vision and Electronic Imaging XVIII; 86510T (2013) https://doi.org/10.1117/12.981761
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

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.

Citation Download Citation

Anish Mittal, Rajiv Soundararajan, Gautam S. Muralidhar, Alan C. Bovik, and Joydeep Ghosh "Blind image quality assessment without training on human opinion scores", Proc. SPIE 8651, Human Vision and Electronic Imaging XVIII, 86510T (14 March 2013); https://doi.org/10.1117/12.981761

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