@inproceedings{Nikolas1991,
abstract = {The problem of multi-channel restoration using both within and between-channel deterministic information is considered. A multi-channel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images will yield suboptimal results when applied to multi-channel images, since between-channel information is not utilized. Multi-channel least squares restoration filters are developed using two approaches, the set theoretic and the constrained optimization. A geometric interpretation of the estimates of both filters is given. Color images, that is, three-channel imagery with red, green, and blue components, are considered. Constraints that capture the within and between-channel properties of color images are developed. Issues associated with the computation of the two estimates are addressed. Finally, experiments using color images are shown.},
author = {Galatsanos, N.P. and Katsaggelos, A.K. and Chin, R.T. and Hillery, Allen},
booktitle = {[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing},
doi = {10.1109/ICASSP.1991.150911},
isbn = {0-7803-0003-3},
issn = {07367791},
pages = {2509--2512 vol.4},
publisher = {IEEE},
title = {{Two methods for least squares multi-channel image restoration}},
url = {http://ieeexplore.ieee.org/document/150911/},
volume = {4},
year = {1991}
}

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