Globally optimal smoothing functional for multichannel image restoration

Moon G. Kang, Aggelos K. Katsaggelos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

It is expected that a globally optimal restored multichannel image should be superior to a suboptimally restored image without the use of cross-channel information. In this paper, a regularized multichannel image restoration approach is proposed, which is based on the minimum multichannel regularized noise power criterion. Furthermore, no prior knowledge about the variance of the noise at each channel and a bound on the high frequency energy of the image are assumed, but this information is estimated based on the partially restored result at each step. The multichannel smoothing functional to be minimized is formulated to have a global minimizer with the proper choice of the multichannel regularization functionals. With this algorithm, the regularization functional for each channel is determined by incorporating not only within-channel information but also cross-channel information. It is also shown that the proposed multichannel smoothing functional is convex, and therefore, has a global minimizer. The proposed multichannel algorithm not only does not depend on initial conditions but is also shown to be much more computationally efficient than existing algorithms.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Pages232-243
Number of pages12
Volume2308
Editionp 1
Publication statusPublished - 1994 Dec 1
EventVisual Communications and Image Processing '94 - Chicago, IL, USA
Duration: 1994 Sep 251994 Sep 29

Other

OtherVisual Communications and Image Processing '94
CityChicago, IL, USA
Period94/9/2594/9/29

Fingerprint

Image reconstruction
smoothing
restoration
functionals
energy

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Kang, M. G., & Katsaggelos, A. K. (1994). Globally optimal smoothing functional for multichannel image restoration. In Proceedings of SPIE - The International Society for Optical Engineering (p 1 ed., Vol. 2308, pp. 232-243)
Kang, Moon G. ; Katsaggelos, Aggelos K. / Globally optimal smoothing functional for multichannel image restoration. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 2308 p 1. ed. 1994. pp. 232-243
@inproceedings{01e65ad6eab04e889c140bc29f747050,
title = "Globally optimal smoothing functional for multichannel image restoration",
abstract = "It is expected that a globally optimal restored multichannel image should be superior to a suboptimally restored image without the use of cross-channel information. In this paper, a regularized multichannel image restoration approach is proposed, which is based on the minimum multichannel regularized noise power criterion. Furthermore, no prior knowledge about the variance of the noise at each channel and a bound on the high frequency energy of the image are assumed, but this information is estimated based on the partially restored result at each step. The multichannel smoothing functional to be minimized is formulated to have a global minimizer with the proper choice of the multichannel regularization functionals. With this algorithm, the regularization functional for each channel is determined by incorporating not only within-channel information but also cross-channel information. It is also shown that the proposed multichannel smoothing functional is convex, and therefore, has a global minimizer. The proposed multichannel algorithm not only does not depend on initial conditions but is also shown to be much more computationally efficient than existing algorithms.",
author = "Kang, {Moon G.} and Katsaggelos, {Aggelos K.}",
year = "1994",
month = "12",
day = "1",
language = "English",
isbn = "081941638X",
volume = "2308",
pages = "232--243",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",
edition = "p 1",

}

Kang, MG & Katsaggelos, AK 1994, Globally optimal smoothing functional for multichannel image restoration. in Proceedings of SPIE - The International Society for Optical Engineering. p 1 edn, vol. 2308, pp. 232-243, Visual Communications and Image Processing '94, Chicago, IL, USA, 94/9/25.

Globally optimal smoothing functional for multichannel image restoration. / Kang, Moon G.; Katsaggelos, Aggelos K.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 2308 p 1. ed. 1994. p. 232-243.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Globally optimal smoothing functional for multichannel image restoration

AU - Kang, Moon G.

AU - Katsaggelos, Aggelos K.

PY - 1994/12/1

Y1 - 1994/12/1

N2 - It is expected that a globally optimal restored multichannel image should be superior to a suboptimally restored image without the use of cross-channel information. In this paper, a regularized multichannel image restoration approach is proposed, which is based on the minimum multichannel regularized noise power criterion. Furthermore, no prior knowledge about the variance of the noise at each channel and a bound on the high frequency energy of the image are assumed, but this information is estimated based on the partially restored result at each step. The multichannel smoothing functional to be minimized is formulated to have a global minimizer with the proper choice of the multichannel regularization functionals. With this algorithm, the regularization functional for each channel is determined by incorporating not only within-channel information but also cross-channel information. It is also shown that the proposed multichannel smoothing functional is convex, and therefore, has a global minimizer. The proposed multichannel algorithm not only does not depend on initial conditions but is also shown to be much more computationally efficient than existing algorithms.

AB - It is expected that a globally optimal restored multichannel image should be superior to a suboptimally restored image without the use of cross-channel information. In this paper, a regularized multichannel image restoration approach is proposed, which is based on the minimum multichannel regularized noise power criterion. Furthermore, no prior knowledge about the variance of the noise at each channel and a bound on the high frequency energy of the image are assumed, but this information is estimated based on the partially restored result at each step. The multichannel smoothing functional to be minimized is formulated to have a global minimizer with the proper choice of the multichannel regularization functionals. With this algorithm, the regularization functional for each channel is determined by incorporating not only within-channel information but also cross-channel information. It is also shown that the proposed multichannel smoothing functional is convex, and therefore, has a global minimizer. The proposed multichannel algorithm not only does not depend on initial conditions but is also shown to be much more computationally efficient than existing algorithms.

UR - http://www.scopus.com/inward/record.url?scp=0028747611&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028747611&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0028747611

SN - 081941638X

SN - 9780819416384

VL - 2308

SP - 232

EP - 243

BT - Proceedings of SPIE - The International Society for Optical Engineering

ER -

Kang MG, Katsaggelos AK. Globally optimal smoothing functional for multichannel image restoration. In Proceedings of SPIE - The International Society for Optical Engineering. p 1 ed. Vol. 2308. 1994. p. 232-243