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A general formulation of constrained iterative restoration algorithms

Published 23 March 2005
Aggelos K. Katsaggelos, J. Biemond, R. Mersereau, Ronald W. Schafer
Citations45

TL;DR

This paper introduces a general formulation of constrained iterative restoration algorithms in which deterministic and/or statistical information about the undistorted signal and statistical Information about the noise are directly incorporated into the iterative procedure.

Abstract

This paper introduces a general formulation of constrained iterative restoration algorithms in which deterministic and/or statistical information about the undistorted signal and statistical information about the noise are directly incorporated into the iterative procedure. This a priori information is incorporated into the restoration algorithm by what we call "soft" or statistical constraints. Their effect on the solution depends on the amount of noise on the data; that is, the constraint operator is "turned off" for noiseless data. The development of the new iterative algorithm is based on results from regularization techniques for stabilizing ill-posed problems.

Keywords

Computer ScienceEarth and Planetary SciencesEngineering