We describe a new digital method of superresolution or restoration of band-limited images in the presence of noise. The restoration procedure is an iterative regularized pseudoinverse (RPI) algorithm that is based on the principle of least squares. This method acquires the advantage of tolerance to noise by incorporating additional constraints of nonnegativity of the object and adaptive regularization as well as the finite extent of the object. After discussing the convergence of the iterative RPI algorithm, we present some results of computer simulations that demonstrate the effectiveness of the proposed method.
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Maeda et al. (1984) studied this question.
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