Image restoration based on constrained total least squares

Xiangchao Gan; Alan Wee-Chung Liew; Hong Yan

doi:10.1109/ICASSP.2004.1326516

Image restoration based on constrained total least squares

Xiangchao Gan
, Alan Wee-Chung Liew
, Hong Yan

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

In constrained total least squares algorithm (CTLS), the selection of a minimal algebraic set of linearly independent random variables to express the noise matrix ΔC is an important task. In this paper, A fast algorithm is provided using the possibly dependent random variables set. We showed that it can be viewed as a combination of Mesarovic et al' s CTLS method and RLS method when the noise is Gaussian. Our experimental study indicated that our algorithm has better visual and objective quality, while having a much lower computation cost. Moreover, our algorithm can also handle a more general noise model.

Original language	English
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	3
DOIs	https://doi.org/10.1109/ICASSP.2004.1326516
Publication status	Published - 2004
Event	Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada Duration: 17 May 2004 → 21 May 2004

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title = "Image restoration based on constrained total least squares",

abstract = "In constrained total least squares algorithm (CTLS), the selection of a minimal algebraic set of linearly independent random variables to express the noise matrix ΔC is an important task. In this paper, A fast algorithm is provided using the possibly dependent random variables set. We showed that it can be viewed as a combination of Mesarovic et al' s CTLS method and RLS method when the noise is Gaussian. Our experimental study indicated that our algorithm has better visual and objective quality, while having a much lower computation cost. Moreover, our algorithm can also handle a more general noise model.",

author = "Xiangchao Gan and Liew, \{Alan Wee-Chung\} and Hong Yan",

year = "2004",

doi = "10.1109/ICASSP.2004.1326516",

language = "English",

volume = "3",

journal = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

issn = "0736-7791",

publisher = "IEEE",

note = "Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing ; Conference date: 17-05-2004 Through 21-05-2004",

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TY - JOUR

T1 - Image restoration based on constrained total least squares

AU - Gan, Xiangchao

AU - Liew, Alan Wee-Chung

AU - Yan, Hong

PY - 2004

Y1 - 2004

N2 - In constrained total least squares algorithm (CTLS), the selection of a minimal algebraic set of linearly independent random variables to express the noise matrix ΔC is an important task. In this paper, A fast algorithm is provided using the possibly dependent random variables set. We showed that it can be viewed as a combination of Mesarovic et al' s CTLS method and RLS method when the noise is Gaussian. Our experimental study indicated that our algorithm has better visual and objective quality, while having a much lower computation cost. Moreover, our algorithm can also handle a more general noise model.

AB - In constrained total least squares algorithm (CTLS), the selection of a minimal algebraic set of linearly independent random variables to express the noise matrix ΔC is an important task. In this paper, A fast algorithm is provided using the possibly dependent random variables set. We showed that it can be viewed as a combination of Mesarovic et al' s CTLS method and RLS method when the noise is Gaussian. Our experimental study indicated that our algorithm has better visual and objective quality, while having a much lower computation cost. Moreover, our algorithm can also handle a more general noise model.

UR - https://www.scopus.com/pages/publications/4544327725

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-4544327725&origin=recordpage

U2 - 10.1109/ICASSP.2004.1326516

DO - 10.1109/ICASSP.2004.1326516

M3 - RGC 21 - Publication in refereed journal

SN - 0736-7791

VL - 3

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 17 May 2004 through 21 May 2004

ER -

Image restoration based on constrained total least squares

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