Another stopping rule for linear iterative signal restoration

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 i...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on signal processing 1999-11, Vol.47 (11), p.3156-3159
Main Authors: Walsh, D.O., Marcellin, M.W.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Coherence
Cost function
Degradation
Descent
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Image restoration
Imagery
Information, signal and communications theory
Iterative algorithms
Iterative methods
Least squares methods
Minimax techniques
Restoration
Signal and communications theory
Signal processing
Signal restoration
Signal, noise
Telecommunications and information theory
Utilities
Vectors
White noise
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1053-587X
1941-0476
DOI:10.1109/78.796454