Generalized adaptive edge-preserving image restoration algorithm

Sung Cheol Park; Moon Gi Kang

doi:10.1109/TENCON.1999.818517

Generalized adaptive edge-preserving image restoration algorithm

Sung Cheol Park, Moon Gi Kang

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Discontinuities present serious difficulties to standard regularization, since standard regularization theory imposes global smoothness constraints on possible solution. We propose a noise-adaptive edge-preserving image restoration algorithm based on the Markov random field image model. Our potential function is controlled by the weighting function for providing the capability of adaptively introducing the discontinuities into the solution. Moreover a new parameter is adopted to prevent the undesirable amplification of strong noise. Extending our previous work, we propose a nonlinear formulation of the regularization functional and derive an iterative algorithm for ensuring the global minimum. The effectiveness of the proposed algorithm is demonstrated experimentally.

Original language	English
Title of host publication	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	726-729
Number of pages	4
ISBN (Electronic)	0780357396, 9780780357396
DOIs	https://doi.org/10.1109/TENCON.1999.818517
Publication status	Published - 1999
Event	1999 IEEE Region 10 Conference, TENCON 1999 - Cheju Island, Korea, Republic of Duration: 1999 Sep 15 → 1999 Sep 17

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume	1
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Other

Other	1999 IEEE Region 10 Conference, TENCON 1999
Country	Korea, Republic of
City	Cheju Island
Period	99/9/15 → 99/9/17

Bibliographical note

Publisher Copyright:
© 1999 IEEE.

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/TENCON.1999.818517

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title = "Generalized adaptive edge-preserving image restoration algorithm",

abstract = "Discontinuities present serious difficulties to standard regularization, since standard regularization theory imposes global smoothness constraints on possible solution. We propose a noise-adaptive edge-preserving image restoration algorithm based on the Markov random field image model. Our potential function is controlled by the weighting function for providing the capability of adaptively introducing the discontinuities into the solution. Moreover a new parameter is adopted to prevent the undesirable amplification of strong noise. Extending our previous work, we propose a nonlinear formulation of the regularization functional and derive an iterative algorithm for ensuring the global minimum. The effectiveness of the proposed algorithm is demonstrated experimentally.",

author = "Park, {Sung Cheol} and Kang, {Moon Gi}",

note = "Publisher Copyright: {\textcopyright} 1999 IEEE.; 1999 IEEE Region 10 Conference, TENCON 1999 ; Conference date: 15-09-1999 Through 17-09-1999",

year = "1999",

doi = "10.1109/TENCON.1999.818517",

language = "English",

series = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Park, SC & Kang, MG 1999, Generalized adaptive edge-preserving image restoration algorithm. in IEEE Region 10 Annual International Conference, Proceedings/TENCON. IEEE Region 10 Annual International Conference, Proceedings/TENCON, vol. 1, Institute of Electrical and Electronics Engineers Inc., pp. 726-729, 1999 IEEE Region 10 Conference, TENCON 1999, Cheju Island, Korea, Republic of, 99/9/15. https://doi.org/10.1109/TENCON.1999.818517

Generalized adaptive edge-preserving image restoration algorithm. / Park, Sung Cheol; Kang, Moon Gi.

IEEE Region 10 Annual International Conference, Proceedings/TENCON. Institute of Electrical and Electronics Engineers Inc., 1999. p. 726-729 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Discontinuities present serious difficulties to standard regularization, since standard regularization theory imposes global smoothness constraints on possible solution. We propose a noise-adaptive edge-preserving image restoration algorithm based on the Markov random field image model. Our potential function is controlled by the weighting function for providing the capability of adaptively introducing the discontinuities into the solution. Moreover a new parameter is adopted to prevent the undesirable amplification of strong noise. Extending our previous work, we propose a nonlinear formulation of the regularization functional and derive an iterative algorithm for ensuring the global minimum. The effectiveness of the proposed algorithm is demonstrated experimentally.

AB - Discontinuities present serious difficulties to standard regularization, since standard regularization theory imposes global smoothness constraints on possible solution. We propose a noise-adaptive edge-preserving image restoration algorithm based on the Markov random field image model. Our potential function is controlled by the weighting function for providing the capability of adaptively introducing the discontinuities into the solution. Moreover a new parameter is adopted to prevent the undesirable amplification of strong noise. Extending our previous work, we propose a nonlinear formulation of the regularization functional and derive an iterative algorithm for ensuring the global minimum. The effectiveness of the proposed algorithm is demonstrated experimentally.

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 1999 IEEE Region 10 Conference, TENCON 1999

Y2 - 15 September 1999 through 17 September 1999

ER -

Generalized adaptive edge-preserving image restoration algorithm

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