Multi-channel blind blur identification and image restoration

Chunqi Chang; Sze Fong Yau; Paul Kwok; F. K. Lam; Francis H.Y. Chan

Multi-channel blind blur identification and image restoration

Chunqi Chang, Sze Fong Yau, Paul Kwok, F. K. Lam, Francis H.Y. Chan

Hong Kong Metropolitan University

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper considers the problem of multi-channel blind image restoration and blur identification. By constructing the blind identification problem into an optimization problem, we propose a subspace decomposition based algorithm to blindly identify the blur functions. The proposed algorithm is inherently the same as many of the others in the literature, but at significantly reduced computation complexity. Let M be the number of blurred images available, N₁×N₂ be the size of the images and L₁×L₂ be the size of blur functions, our algorithm has a computation complexity of O(M²L₁²L₂²N₁N₂), as compared to O(M⁴L₁²L₂²N₁N₂) for previous works. The proposed algorithm is therefore more suitable for practical applications.

Original language	English
Pages (from-to)	533-536
Number of pages	4
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	3545
Publication status	Published - 1998
Event	Proceedings of the 1998 International Symposium on Multispectral Image Processing, ISMIP'98 - Wuhan, China Duration: 21 Oct 1998 → 23 Oct 1998

Cite this

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title = "Multi-channel blind blur identification and image restoration",

abstract = "This paper considers the problem of multi-channel blind image restoration and blur identification. By constructing the blind identification problem into an optimization problem, we propose a subspace decomposition based algorithm to blindly identify the blur functions. The proposed algorithm is inherently the same as many of the others in the literature, but at significantly reduced computation complexity. Let M be the number of blurred images available, N1×N2 be the size of the images and L1×L2 be the size of blur functions, our algorithm has a computation complexity of O(M2L12L22N1N2), as compared to O(M4L12L22N1N2) for previous works. The proposed algorithm is therefore more suitable for practical applications.",

author = "Chunqi Chang and Yau, {Sze Fong} and Paul Kwok and Lam, {F. K.} and Chan, {Francis H.Y.}",

year = "1998",

language = "English",

volume = "3545",

pages = "533--536",

note = "Proceedings of the 1998 International Symposium on Multispectral Image Processing, ISMIP'98 ; Conference date: 21-10-1998 Through 23-10-1998",

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TY - JOUR

T1 - Multi-channel blind blur identification and image restoration

AU - Chang, Chunqi

AU - Yau, Sze Fong

AU - Kwok, Paul

AU - Lam, F. K.

AU - Chan, Francis H.Y.

PY - 1998

Y1 - 1998

N2 - This paper considers the problem of multi-channel blind image restoration and blur identification. By constructing the blind identification problem into an optimization problem, we propose a subspace decomposition based algorithm to blindly identify the blur functions. The proposed algorithm is inherently the same as many of the others in the literature, but at significantly reduced computation complexity. Let M be the number of blurred images available, N1×N2 be the size of the images and L1×L2 be the size of blur functions, our algorithm has a computation complexity of O(M2L12L22N1N2), as compared to O(M4L12L22N1N2) for previous works. The proposed algorithm is therefore more suitable for practical applications.

AB - This paper considers the problem of multi-channel blind image restoration and blur identification. By constructing the blind identification problem into an optimization problem, we propose a subspace decomposition based algorithm to blindly identify the blur functions. The proposed algorithm is inherently the same as many of the others in the literature, but at significantly reduced computation complexity. Let M be the number of blurred images available, N1×N2 be the size of the images and L1×L2 be the size of blur functions, our algorithm has a computation complexity of O(M2L12L22N1N2), as compared to O(M4L12L22N1N2) for previous works. The proposed algorithm is therefore more suitable for practical applications.

UR - http://www.scopus.com/inward/record.url?scp=0032304138&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0032304138

SN - 0277-786X

VL - 3545

SP - 533

EP - 536

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

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

T2 - Proceedings of the 1998 International Symposium on Multispectral Image Processing, ISMIP'98

Y2 - 21 October 1998 through 23 October 1998

ER -

Multi-channel blind blur identification and image restoration

Abstract

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