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.