Maximum entropy image processing using transform domain constraints
Date
1989
Authors
Zala, C A
Barrodale, I
Lucas, C E
MacKinnon, R F
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
A formulation of the maximum entropy (ME) method is described,
where the data constraints are expressed in the form of fixed bounds on
the elements of an orthogonal transform of the model. The bounds are set
on the basis of both the observed data and an estimate of the noise
statistics in the transform domain; prior knowledge, if available, can
also be incorporated. Using a special-purpose conjugate gradient
algorithm developed for this problem, one-dimensional examples are
presented that illustrate substantial SNR enhancement using the new
formulation with both Fourier and Walsh transforms. A simple strategy
for selecting an initial feasible solution for the algorithm is
presented.
Description
©1989 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords
conjugate gradient algorithm, data constraints, Fourier transforms, image processing, maximum entropy method, noise statistics, observed data, orthogonal transform, picture processing, SNR enhancement, transform domain constraints, Walsh transforms
Citation
Zala, C., et al, PACRIM.1989, p. 87-90