Most methods proposed for restoring images acquired by the Hubble Space Telescope rely on prior knowledge of the telescope's point-spread function; however, for many images, this function is not known precisely and must be inferred from the noisy measured data. In this paper, we address this problem and discuss a maximum-likelihood estimation technique for simultaneously determining the nature of the aberrations and for recovering the underlying object from a noisy, degraded image.
Pages 206-211
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