Thursday,
April 24, 2008, 12:15 p.m. PSA 206
Wolfgang Stefan
Dept. Math. & Stats.
Improved total variation-type regularization using higher-order edge detectors
Abstract
We present a novel deconvolution approach that simultaneously deblurs
and detects edges in piecewise smooth signals. Both edges and smooth
regions, separated by jump discontinuities, are preserved. The method
uses a two step procedure: The polynomial annihilation method combined
with total variation (TV) deconvolution obtains an estimate of the
location of jump discontinuities in blurred noisy data. This
information is used to determine the order for a higher-order TV
regularization which is then utilized in the signal restoration. As
compared to those obtained with standard TV, signal restorations are
more accurate representations of the true signals, as measured in a
relative $l^2$ norm, and can also be used to obtain a more accurate
estimation of the locations and sizes of the true jump
discontinuities.
For further information please contact:
mittelmann@asu.edu