Professor Lucier's recent research concentrates on mathematical
analysis of and computational methods for wavelet techniques in
image processing. He has written papers on image compression,
surface compression, application to compression of mammographic
images, noise removal, and variational problems, in each case using
nonlinear wavelet techniques to derive or analyze algorithms that
are near the top of the performance range for each problem. This
work is continuing, with new results in tomographic reconstruction
from noisy data (with applications to Positron Emission Tomography,
an important method of brain imaging), image smoothing scale
spaces, etc., soon to be finished. This work is supported by the
Office of Naval Research.
Very recently, Lucier has begun collaborating with Jens Palsberg on
applying programming language transformation techniques to speed
Genetic Programming systems applied to problems with large data
sets, as arise, for example in image processing. This work, which
has resulted in speedups up to 30 times in serial code, is
supported by British Telecom.