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15 November 2007 Double regularization approach to iterative blind multispectral image restoration
Li Chen, Changjie Wang
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Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 67870L (2007) https://doi.org/10.1117/12.748550
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
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.
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Li Chen and Changjie Wang "Double regularization approach to iterative blind multispectral image restoration", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67870L (15 November 2007); https://doi.org/10.1117/12.748550
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KEYWORDS
Image restoration
Image processing
Multispectral imaging
Algorithms
Image deconvolution
Algorithm development
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