Veeraraghavan wins NSF CAREER Award

Computational imaging project will lead to more sophisticated cameras 

Rice University engineer Ashok Veeraraghavan and his research group have a vision clear enough to earn a prestigious National Science Foundation (NSF) CAREER Award.

The NSF awards CAREER grants to young scientists who show the potential for leadership in their fields. The five-year grant to Veeraraghavan is for $549,000.

Veeraraghavan

Veeraraghavan specializes in the use of computer technology, statistics and sophisticated algorithms to see both farther and deeper, and at increasingly sharper resolution.

An assistant professor of electrical and computer engineering who joined Rice in 2010, Veeraraghavan has already made his mark at the university through his lab’s development of mobileVision, a simple device to monitor eye health, and FlatCam, a project with engineering colleague Richard Baraniuk that is developing a lens-less camera platform.

The new grant will help his lab build a signal processing framework that should improve existing imaging systems for standard cameras and help design new ones to see deeper into nature with enhanced microscopes and farther out through consumer cameras, remote sensing, machine vision and surveillance applications.

“Apart from the theoretical and algorithmic improvements, we’re looking at applications like obtaining high-resolution images from long distances,” Veeraraghavan said. “In particular, we’re building applications to answer questions like, can you do face recognition from a kilometer distance?

“When you are taking images at long range, the resolution is fundamentally limited by the size of your lens. That’s why, when you buy a telephoto lens, it’s both huge and expensive.

“What we are trying to do is create systems that, through computation, can take multiple images and give you the benefit of having a huge lens without having to lug one around,” he said.

The lab aims to improve onboard algorithms that combine multiple shots to achieve higher resolution images, but in small, compact systems. “Don’t think of this as an algorithm,” he said. “Think of it as a new camera. We are looking at how to build compact imaging systems that can achieve the functionalities of really large systems.”

He’s also part of the Scalable Health Initiative at Rice that seeks to advance sensing systems that can help diagnose health in remote locations, another area in which small, compact devices are essential.

“Computational imaging has been a field for about 10 years now and there have been quite a few works, but there is no clear understanding of the field because of the fundamental limits of what can be achieved using these approaches,” he said. “One of our main goals with this project is to explore these fundamental limits.”