@Article{NMTMA-6-262,
author = {M. K. Khan, S. Morigi, L. Reichel and F. Sgallari},
title = {Iterative Methods of Richardson-Lucy-Type for Image Deblurring},
journal = {Numerical Mathematics: Theory, Methods and Applications},
year = {2013},
volume = {6},
number = {1},
pages = {262--275},
abstract = {<p style="text-align: justify;">Image deconvolution problems with a symmetric point-spread function arise in
many areas of science and engineering. These problems often are solved by
the Richardson-Lucy method, a nonlinear iterative method. We first show a
convergence result for the Richardson-Lucy method. The proof sheds light on
why the method may converge slowly. Subsequently, we describe an iterative
active set method that imposes the same constraints on the computed solution
as the Richardson-Lucy method. Computed examples show the latter method to
yield better restorations than the Richardson-Lucy method and typically
require less computational effort.</p>},
issn = {2079-7338},
doi = {https://doi.org/10.4208/nmtma.2013.mssvm14},
url = {http://global-sci.org/intro/article_detail/nmtma/5903.html}
}