A unified approach to iterative image restoration

Aggelos K. Katsaggelos

doi:10.1117/12.976502

A unified approach to iterative image restoration

Aggelos K. Katsaggelos^*

^*Corresponding author for this work

MRC - Materials Research Center

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

In this paper a class of iterative image restoration algorithms is derived based on a representation theorem for the generalized inverse of a matrix. These algorithms exhibit a first or higher order of convergence and some of them consist of an “on-line” and an “off-line” computational part. The conditions of convergence and the rate of convergence of these algorithms are derived. A faster rate of convergence can be achieved by increasing the computational load. The algorithms can be applied to the restoration of signals of any dimensionality. Iterative restoration algorithms that have appeared in the literature represent special cases of the class of algorithms described here.

Original language	English (US)
Pages (from-to)	176-181
Number of pages	6
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	845
DOIs	https://doi.org/10.1117/12.976502
State	Published - Oct 13 1987

Funding

The author wishes to thank Mr. Serafim Efstratiadis for producing the experimental results. The research work leading to this paper was supported by the National Science Foundation under grant no. MIP-8614217.

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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title = "A unified approach to iterative image restoration",

abstract = "In this paper a class of iterative image restoration algorithms is derived based on a representation theorem for the generalized inverse of a matrix. These algorithms exhibit a first or higher order of convergence and some of them consist of an “on-line” and an “off-line” computational part. The conditions of convergence and the rate of convergence of these algorithms are derived. A faster rate of convergence can be achieved by increasing the computational load. The algorithms can be applied to the restoration of signals of any dimensionality. Iterative restoration algorithms that have appeared in the literature represent special cases of the class of algorithms described here.",

author = "Katsaggelos, {Aggelos K.}",

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N2 - In this paper a class of iterative image restoration algorithms is derived based on a representation theorem for the generalized inverse of a matrix. These algorithms exhibit a first or higher order of convergence and some of them consist of an “on-line” and an “off-line” computational part. The conditions of convergence and the rate of convergence of these algorithms are derived. A faster rate of convergence can be achieved by increasing the computational load. The algorithms can be applied to the restoration of signals of any dimensionality. Iterative restoration algorithms that have appeared in the literature represent special cases of the class of algorithms described here.

AB - In this paper a class of iterative image restoration algorithms is derived based on a representation theorem for the generalized inverse of a matrix. These algorithms exhibit a first or higher order of convergence and some of them consist of an “on-line” and an “off-line” computational part. The conditions of convergence and the rate of convergence of these algorithms are derived. A faster rate of convergence can be achieved by increasing the computational load. The algorithms can be applied to the restoration of signals of any dimensionality. Iterative restoration algorithms that have appeared in the literature represent special cases of the class of algorithms described here.

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A unified approach to iterative image restoration

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