Abstract: A framework for learning multiscale sparse representations of color images and video with overcomplete dictionaries is presented in this talk. The dictionary learning is formulated as an optimization problem, efficiently solved by combining quad-tree structures with orthogonal matching pursuit (OMP) and one-rank approximations. The proposed framework provides an alternative to pre-defined dictionaries such as wavelets, and shown to lead to state-of-the-art results in a number of image and video enhancement and restoration applications. We conclude the talk with discussion of learning sparse representations beyond the task of restoration.

The core of this talk is based on joint work with J. Mairal and M. Elad. Additional material presented briefly is the result of work with J. Mairal, F. Rodriguez, F. Bach, J. Ponce, and A. Zisserman.

Biography: Guillermo Sapiro was born in Montevideo, Uruguay, on April 3, 1966. He received his B.Sc. (summa cum laude), M.Sc., and Ph.D. from the Department of Electrical Engineering at the Technion, Israel Institute of Technology, in 1989, 1991, and 1993 respectively. After post-doctoral research at MIT, Dr. Sapiro became a Member of the Technical Staff at the research facilities of HP Labs in Palo Alto, California.

Dr. Sapiro works on differential geometry and geometric partial differential equations, both in theory and applications in computer vision, computer graphics, medical imaging, and image analysis. He co-edited a special issue of IEEE Image Processing on this topic and a second one in the Journal of Visual Communication and Image Representation. He has authored and co-authored numerous papers in this area and has written a monograph published by Cambridge University Press, January 2001.

Dr. Sapiro was awarded the Gutwirth Scholarship for Special Excellence in Graduate Studies in 1991, the Ollendorff Fellowship for Excellence in Vision and Image Understanding Work in 1992, the Rothschild Fellowship for Post-Doctoral Studies in 1993, the Office of Naval Research Young Investigator Award in 1998, the Presidential Early Career Awards for Scientist and Engineers (PECASE) in 1998, the National Science Foundation Career Award in 1999, and the George Taylor Research Award in 2006. G. Sapiro is the founding Editor-in-Chief of the SIAM Journal on Imaging Sciences.