Level sets and their role in image/data processing

Stanley Osher (IPAM & UCLA) (S)

Since its development in 1987, the level set method has proven
to be a very valuable tool in a host of applications including image
processing and related fields. Almost simultaneously, useful and
interesting nonlinear PDE based approaches to image processing were
developed. In this talk we will try to give a survey of recent
developments in this field, particularly those that have some hope of
overcoming the curse of dimensionality.


Stanley Osher received his MS (1964) and Phd (1966) degrees from the
Courant institute, New York University. He was at Brookhaven national
Laboratory from 1966-68, U. C. Berkeley from 1968-70, SUNY Stony Brook
from 1970-77, and at UCLA since 1977. He has been a Fulbright, Sloan, SERC
and US-Israel BSF fellow, shared the NASA public service group achievement
award and was an invited speaker at the International Congress of
Mathematicians. He is the coinventor and a prncipal developer of widely
used i)state-of-the-art high resolution schemes for approximating
conservation laws and Hamilton-Jacobi equations, ii)level set and related
methods for computing dynamic fronts, and iii)total variation and other
PDE based image processing techniques. His work has been written up
numerous times in the scientific and international media, e.g, Science
News, Die Zeit (both in 1999). He is now Director of Special Projects at

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