Cite Details
Youzuo Lin and Brendt Wohlberg, "Application of the UPRE Method to Optimal Parameter
Selection for Large Scale Regularization Problems", in
IEEE Southwest Symposium on Image Analysis and Interpretation, (Santa Fe, NM, USA), doi:
10.1109/SSIAI.2008.4512292, pp. 89--92, Mar 2008
Abstract
Regularization is an important method for solving a wide
variety of inverse problems in image processing. In order to
optimize the reconstructed image, it is important to choose the
optimal regularization parameter. The Unbiased Predictive Risk
Estimator (UPRE) has been shown to give a very good estimate of
this parameter. Applying the traditional UPRE is impractical,
however, in the case of inverse problems such as deblurring, due
to the large scale of the associated linear problem. We propose
an approach to reducing the large scale problem to a small
problem, significantly reducing computational requirements while
providing a good approximation to the original problem.
BibTeX Entry
@inproceedings{lin-2008-application,
author = {Youzuo Lin and Brendt Wohlberg},
title = {Application of the {UPRE} Method to Optimal Parameter
Selection for Large Scale Regularization Problems},
year = {2008},
month = Mar,
urlpdf = {http://brendt.wohlberg.net/publications/pdf/lin-2008-application.pdf},
booktitle = {IEEE Southwest Symposium on Image Analysis and Interpretation},
address = {Santa Fe, NM, USA},
doi = {10.1109/SSIAI.2008.4512292},
pages = {89--92}
}
