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Proceedings Paper

Double regularization approach to iterative blind multispectral image restoration
Author(s): Li Chen; Changjie Wang
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Paper Abstract

In this paper, we present a new iterative blind multispectral image restoration algorithm based on double regularization (DR). The motivation for DR when applied to multispectral restoration lies in its effectiveness towards edge preservation in joint blur identification and image restoration. With consideration for both the intra- and inter-channel blurring function in the multiple-input multiple-output (MIMO) systems, an alternating minimization (AM) procedure with conjugate gradient optimization (CGO) scheme is formulated to implement restoration iteratively. The derivation of DR optimization shows that optimal restoration result can be achieved even when the MIMO systems suffer from inter-channel interference. Experimental results show that it is effective in performing blind mutichannel restoration when applied to color images.

Paper Details

Date Published: 15 November 2007
PDF: 6 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67870L (15 November 2007); doi: 10.1117/12.748550
Show Author Affiliations
Li Chen, Wuhan Univ. of Science and Technology (China)
Changjie Wang, The Second Ship Research and Institute of Wuhan (China)

Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing
Henri Maître; Hong Sun; Jianguo Liu; Enmin Song, Editor(s)

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