A fast adaptive algorithm for image restoration

Guo Fang Xu; Tamal Bose; Wolfgang Kober; John Thomas

doi:10.1109/81.739269

A fast adaptive algorithm for image restoration

Guo Fang Xu, Tamal Bose, Wolfgang Kober, John Thomas

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

17 Scopus citations

Abstract

An adaptive filtering algorithm based on an Euclidean direction search (EDS) method is presented for image restoration. It is a fast algorithm and has a computational complexity of O(N) for least squares optimization. Computer simulations illustrate that this algorithm is very effective in image restoration. The figures for signal-to-noise ratio improvement (SNRI) produced by this algorithm are comparable to those obtained by using the recently reported sample-based conjugate gradient (SCG) algorithm, which has a computational complexity of O(N²). This algorithm can also be extended to other applications in adaptive signal processing.

Original language	English (US)
Pages (from-to)	216-220
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume	46
Issue number	1
DOIs	https://doi.org/10.1109/81.739269
State	Published - 1999
Externally published	Yes

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/81.739269

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title = "A fast adaptive algorithm for image restoration",

abstract = "An adaptive filtering algorithm based on an Euclidean direction search (EDS) method is presented for image restoration. It is a fast algorithm and has a computational complexity of O(N) for least squares optimization. Computer simulations illustrate that this algorithm is very effective in image restoration. The figures for signal-to-noise ratio improvement (SNRI) produced by this algorithm are comparable to those obtained by using the recently reported sample-based conjugate gradient (SCG) algorithm, which has a computational complexity of O(N2). This algorithm can also be extended to other applications in adaptive signal processing.",

author = "Xu, \{Guo Fang\} and Tamal Bose and Wolfgang Kober and John Thomas",

note = "Funding Information: Manuscript received May 1, 1998; revised August 17, 1998. This work was supported in part by a grant from the Colorado Advanced Software Institute. G.-F. Xu and T. Bose are with the Department of Electrical Engineering, University of Colorado, Denver, CO 80217-3364 USA. W. Kober and J. Thomas are with the Data Fusion Corporation, Westminster, CO 80021 USA. Publisher Item Identifier S 1057-7122(99)00553-X.",

year = "1999",

doi = "10.1109/81.739269",

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T1 - A fast adaptive algorithm for image restoration

AU - Xu, Guo Fang

AU - Bose, Tamal

AU - Kober, Wolfgang

AU - Thomas, John

N1 - Funding Information: Manuscript received May 1, 1998; revised August 17, 1998. This work was supported in part by a grant from the Colorado Advanced Software Institute. G.-F. Xu and T. Bose are with the Department of Electrical Engineering, University of Colorado, Denver, CO 80217-3364 USA. W. Kober and J. Thomas are with the Data Fusion Corporation, Westminster, CO 80021 USA. Publisher Item Identifier S 1057-7122(99)00553-X.

PY - 1999

Y1 - 1999

N2 - An adaptive filtering algorithm based on an Euclidean direction search (EDS) method is presented for image restoration. It is a fast algorithm and has a computational complexity of O(N) for least squares optimization. Computer simulations illustrate that this algorithm is very effective in image restoration. The figures for signal-to-noise ratio improvement (SNRI) produced by this algorithm are comparable to those obtained by using the recently reported sample-based conjugate gradient (SCG) algorithm, which has a computational complexity of O(N2). This algorithm can also be extended to other applications in adaptive signal processing.

AB - An adaptive filtering algorithm based on an Euclidean direction search (EDS) method is presented for image restoration. It is a fast algorithm and has a computational complexity of O(N) for least squares optimization. Computer simulations illustrate that this algorithm is very effective in image restoration. The figures for signal-to-noise ratio improvement (SNRI) produced by this algorithm are comparable to those obtained by using the recently reported sample-based conjugate gradient (SCG) algorithm, which has a computational complexity of O(N2). This algorithm can also be extended to other applications in adaptive signal processing.

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A fast adaptive algorithm for image restoration

Abstract

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