May 1, 2000
Engineer Peyman Milanfar wins major award from National Science Foundation
By Tim Stephens
Milanfar's work in the area of image and signal processing has applications in a broad range of fields, including astronomy, geophysics, medical imaging and nondestructive testing of materials. Indirect measurements, as opposed to direct observations, play an increasingly important role in gathering information about the world around us. Through technologies that extend and complement human sensory faculties, people are able to probe across great distances and through natural barriers.
At the heart of this ability to make and interpret indirect measurements are practical computational techniques for processing the measured data and distilling the information of interest from the data. These techniques must bring together tools from multidimensional signal processing, statistics, and applied mathematics to solve what are known as "inverse problems." An inverse problem basically involves measuring an effect and working backward to determine its cause.
"These kinds of problems are ubiquitous--they arise in a wide range of situations," Milanfar said.
Milanfar's program will integrate engineering, statistical, and numerical techniques for the solution of inverse problems in imaging. The educational component will involve designing a comprehensive graduate and undergraduate curriculum in statistical signal and image processing in the Department of Electrical Engineering.
The research component of the program will address problems in image reconstruction from indirectly measured information that may be incomplete or noisy. Examples include extracting information from blurred images of a detailed scene or two-dimensional silhouettes of three-dimensional objects.
Additional information about Milanfar's projects is available on his Web site at http://www.cse.ucsc.edu/~milanfar.