Image Restoration Based on Constrained Total Least Squares
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In constrained total least squares algorithm (CTLS), the selection of a minimal algebraic set of linearly independent random variables to express the noise matrix ?C is an important task. In this paper, A fast algorithm is provided using the possibly dependent random variables set. We showed that it can be viewed as a combination of Mesarovic et al' s CTLS method and RLS method when the noise is Gaussian. Our experimental study indicated that our algorithm has better visual and objective quality, while having a much lower computation cost. Moreover, our algorithm can also handle a more general noise model.
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'04
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