Computational and Applied Math Proseminar

Tuesday, October 14, 12:00 p.m. ECG 317

Youzuo Lin

Dept. Math. & Stats

Application of Regularization Techniques in Image Restoration

Abstract Regularization is a successful approach to a wide variety of image restoration problems, of which Tikhonov and Total Variation (TV) regularization are two of the main regularization techniques. In this talk, I will cover a few topics that I have been working on relating to these methods, including a parallelization algorithm for Tikhonov regularization, and optimal parameter selection for TV regularization. Other than these two approaches, over the past few years, another type of regularization based on learning from examples has received more and more attention. I will also talk about my exploration on this method and its application to Image Super-Resolution.

For further information please contact: mittelmann@asu.edu