Title :
Another stopping rule for linear iterative signal restoration
Author :
Walsh, David O. ; Marcellin, Michael W.
Author_Institution :
Vista Clara Inc., Tucson, AZ, USA
fDate :
11/1/1999 12:00:00 AM
Abstract :
A new stopping rule is proposed for linear, iterative signal restoration using the gradient descent and conjugate gradient algorithms. The stopping rule attempts to minimize MSE under the assumption that the signal arises from a white noise process. This assumption is appropriate for many coherent imaging applications. The stopping rule is trivial to compute and, for fixed relaxation parameters, can be computed prior to starting the iteration. The utility of the stopping rule is demonstrated through the restoration of MR imagery
Keywords :
biomedical MRI; conjugate gradient methods; image restoration; least mean squares methods; medical image processing; white noise; MR imagery; MRI; MSE; coherent imaging; conjugate gradient algorithm; gradient descent; linear iterative signal restoration; relaxation parameter; stopping rule; white noise; Cost function; Degradation; Image restoration; Iterative algorithms; Least squares methods; Minimax techniques; Signal processing; Signal restoration; Vectors; White noise;
Journal_Title :
Signal Processing, IEEE Transactions on