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.
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.
Ensuring the security of public transportation portals, company facilities, and government installations has become a topic of increased concern over the past 15 years. Thus, it becomes important to develop new and diverse imaging modes capable of conducting screening and inspection processes under increasingly difficult and busy conditions, as well as to test and verify the efficacy of the new and developing imaging devices that use these diverse and various modes.
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..”
This project aims at investigating the interaction of perceptual image quality on computer vision tasks. WNCG Profs. Alan Bovik and Joydeep Ghosh, with student Suriya Gunasekar currently work on images with facial content and developed algorithms for face detection under commonly observed distortions in image transmission and storage including additive white noise, Gaussian blur, and JPEG compression.