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- W2149183719 abstract "We derive Kronecker product approximations, with the help of tensor decompositions, to construct approximations of severely ill-conditioned matrices that arise in three-dimensional (3-D) image processing applications. We use the Kronecker product approximations to derive preconditioners for iterative regularization techniques; the resulting preconditioned algorithms allow us to restore 3-D images in a computationally efficient manner. Through examples in microscopy and medical imaging, we show that the Kronecker approximation preconditioners provide a powerful tool that can be used to improve efficiency of iterative image restoration algorithms." @default.
- W2149183719 created "2016-06-24" @default.
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- W2149183719 date "2006-03-01" @default.
- W2149183719 modified "2023-09-25" @default.
- W2149183719 title "Kronecker product approximation for preconditioning in three-dimensional imaging applications" @default.
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- W2149183719 doi "https://doi.org/10.1109/tip.2005.863112" @default.
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