News

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Team LIVE Wins Computer Vision for Public Safety Challenge

June 8, 2021
WNCG students Marius Facktor and Abhinau Venkataramanan and WNCG alumnus Praful Gupta from Prof. Al Bovik’s Laboratory for Image & Video Engineering (LIVE) have been named Phase 2 winners in the Enhancing Computer Vision for Public Safety Challenge. The challenge is hosted by the Public Safety Communications Research Division of the National Institute of Standards and Technology. The competition aims to support public safety missions by advancing computer vision algorithms and no-reference (NR) metrics that assess image or video quality.
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WNCG Student Joshua Ebenezer Wins Nilanjan Ganguly Memorial Award

Nov. 15, 2019
First-year graduate student Joshua Ebenezer has received the Nilanjan Ganguly Memorial Award for his undergraduate thesis on haze- and fog-affected images and videos. The award designates the “best B.Tech thesis in the Electronics & Electrical Communication Engineering Department” at IIT Khargapur and is given annually to a single student. The award also includes a cash prize for the recipient from the Ganguly family. 
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WNCG Alumnus Leads Teams to Top Spots at International Competition

June 12, 2019
WNCG Alumnus Vishal Monga has led two teams of researchers to success at the New Trends in Image Restoration and Enhancement (NTIRE) worldwide competition. Monga received his Ph.D.EE from Texas ECE in 2005, advised by Prof. Brian L. Evans at WNCG. He now runs the Information Processing & Algorithms Laboratory at Penn State’s College of Engineering and holds the title of Associate Professor in the Department of Electrical Engineering and Computer Science.
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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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Improving Infrared Image Quality

Sept. 2, 2014
While much work has been done to further image quality for cameras and smart phones in the visible light spectrum, WNCG student Todd Goodall and his advisor Prof. Bovik have expanded their research to include the quality of infrared images. “As far as Prof. Bovik and I know, no one has thoroughly studied the natural scene statistics of infrared images,” Goodall states. “Other general image statistics have been studied, but no one has considered the perceptually-relevant natural statistics..”