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Abstract
The goal of this article is to describe a unified approach based on the assumption of additive Gaussian noise and regularization theory that illustrates the flavor of such multidimensional image reconstruction problems and the associated challenges. Efficient iterative methods are described for the solution of these problems. Indeed, a crucial point in the solution to the problems considered in this article is the size of the data set and the need for efficient algorithms.
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