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Proceedings Paper

Multichannel blind blur identification and image restoration
Author(s): Chunqi Chang; SzeFong Mark Yau; Paul Kwok; F. K. Lam; Francis H. Y. Chan
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Paper 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 X N2 be the size of the images and L1 X L2 be the size of blur functions, our algorithm has a computational complexity of O(M2L21L22N1N2), as compared to O(M4L21L22N1N2) for previous works. The proposed algorithm is therefore more suitable for practical applications.

Paper Details

Date Published: 25 September 1998
PDF: 4 pages
Proc. SPIE 3545, International Symposium on Multispectral Image Processing (ISMIP'98), (25 September 1998); doi: 10.1117/12.323593
Show Author Affiliations
Chunqi Chang, Univ. of Hong Kong (China)
SzeFong Mark Yau, Hong Kong Univ. of Science and Technology (Hong Kong)
Paul Kwok, Univ. of Hong Kong (China)
F. K. Lam, Univ. of Hong Kong (Hong Kong)
Francis H. Y. Chan, Univ. of Hong Kong (China)

Published in SPIE Proceedings Vol. 3545:
International Symposium on Multispectral Image Processing (ISMIP'98)
Ji Zhou; Anil K. Jain; Tianxu Zhang; Yaoting Zhu; Mingyue Ding; Jianguo Liu, Editor(s)

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