Two of Prof. Al Bovik’s research publications have been recognized as 2017 Google Scholar Classic Papers. Google Scholar Classic Papers are highly-cited papers that have stood the test of time, and are among the ten most-cited articles in their area of research published ten years earlier.
One paper, “Image information and visual quality,” IEEE Transactions on Image Processing, vol. 15, no. 2, pp. 430-444, February 2006, co-authored with ECE and WNCG alumnus Hamid Sheikh, was recognized in the area Computer Vision and Pattern Recognition, where it is the fourth most-cited paper from 2006, with 1,965 cites over that period. The main algorithm developed in the paper, called the Visual Information Fidelity (VIF) Index, is a core picture quality prediction engine used to quality-assess all encodes streamed globally by Netflix.
The other paper, “An evaluation of recent full reference image quality assessment algorithms,” IEEE Transactions on Image Processing, vol. 15, no. 11, pp. 3440-3451, November 2006, co-authored with ECE and WNCG alumnae Hamid Sheikh and Farooq Sabir, was recognized in the area Signal Processing, where it is also the fourth most-cited paper from 2006, with 1,454 cites over that period. The picture quality database and human study described in the paper, the LIVE Image Quality Database, has been the standard development tool for picture quality research since its first introduction in 2003.