Current state-of-the-art algorithms that process visual information for end use by humans treat images and video as traditional signals and employ sophisticated signal processing strategies to achieve their excellent performance. These algorithms also incorporate characteristics of the human visual system (HVS), but typically in a relatively simplistic manner, and achievable performance is reaching an asymptote. However, large gains are still realizable with current techniques by aggressively incorporating HVS characteristics to a much greater extent than is presently done, combined with a good dose of clever signal processing. Achieving these gains requires HVS characterizations which better model natural image perception ranging from sub-threshold perception (where distortions are not visible) to suprathreshold perception (where distortions are clearly visible).
In this talk, I will review results from our lab characterizing the responses of the HVS to natural images, and contrast these results with ‘classical’ psychophysical results. I will also present several examples of signal processing algorithms which have been designed to fully exploit these results. Lastly, I will discuss our current research in developing a structurally-based model for visual masking.
Prof. Sheila S. Hemami received the B.S.E.E. degree from the University of Michigan in 1990, the M.S.E.E. degree from Stanford University in 1992, and the Ph.D. degree from Stanford University in 1994. She was with Hewlett-Packard Laboratories in Palo Alto, California in 1994. In 1995 she joined the School of Electrical Engineering at Cornell University, where she is a Professor and directs the Visual Communications Laboratory. Dr. Hemami received a National Science Foundation Early Career Development Award in 1997 and has received numerous college and national teaching awards. She held the Kodak Term Professorship of Electrical Engineering at Cornell University from 1996-1999, and she was a Fulbright Distinguished Lecturer in 2001. She is a Senior Member of the IEEE. She is currently Chair of the IEEE Image and Multidimensional Signal Processing Technical Committee and has served as the Associate Editor for Source Coding for the IEEE Transactions on Signal Processing. Prof. Hemami is also the Programming Director for the CU-ADVANCE Center at Cornell University.