## Speaker:

Professor Tony Chan

## Institution:

UCLA

## Time:

Thursday, April 7, 2005 - 4:00pm

## Location:

MSTB 254

The total variation based image denoising model of Rudin, Osher,

and Fatemi

has been generalized and modified in many ways in the literature; one of

these modifications is to use the L1 norm as the fidelity term. We study the

interesting consequences of this modification, especially from the point of

view of geometric properties of its solutions. It turns out to have

interesting

new implications for data driven scale selection and multiscale image

decomposition.

(joint work with Selim Esedgolu).