Abstract

A technique for deconvolving an image from both a single convolution and an ensemble of differently blurred images is presented. The method is more robust than the earlier blind deconvolution algorithms proposed by Ayers and Dainty [ Opt. Lett. 13, 547 ( 1988)] and Davey et al. [ Opt. Commun. 69, 353 ( 1989)]. The performance of the algorithm in the presence of noise is evaluated. It is also demonstrated how the algorithm can be modified to utilize the much greater amount of information contained in an ensemble of differently blurred pictures of an image. Reconstructions using both computer simulations and infrared astronomical speckle data are presented. The speckle reconstructions are compared with those obtained by both Fourier phase retrieval and bispectral estimation.

© 1992 Optical Society of America

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