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Prof. Al Bovik's VIF Picture Quality Measurement Tool Built as Core of Netflix's Video Quality System

Oct. 10, 2017
Texas ECE Professor Al Bovik’s neuroscience-based Visual Information Fidelity (VIF) picture quality measurement tool has been built into the core of Netflix’s quality system which controls the quality of every video streamed by Netflix to all customers world-wide. VIF is a full reference image quality assessment index that is based on natural scene statistics, and on a model of the type of image information that is extracted by the human visual system. It was developed by Prof.
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Prof. Al Bovik and Alum Rajiv Soundararajan Win IEEE Circuits and Systems for Video Technology Best Paper Award

May 2, 2016
Prof. Al Bovik and his former student Rajiv Soundararajan have been named recipients of the IEEE Circuits and Systems for Video Technology Best Paper Award for 2016. The award recognizes their 2013 paper “Video Quality Assessment by Reduced Reference Spatio-Temporal Entropic Differencing,”  which appeared in the IEEE Transactions on Circuits and Systems for Video Technology in April 2013.