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@article{biggs_97,
    author = {David S. C. Biggs and Mark Andrews},
    journal = {Appl. Opt.},
    keywords = {Algorithms; Atmospheric turbulence; Image restoration; Linear filtering; Phase retrieval; Space telescopes},
    number = {8},
    pages = {1766--1775},
    publisher = {OSA},
    title = {Acceleration of iterative image restoration algorithms},
    volume = {36},
    month = {Mar},
    year = {1997},
    url = {http://ao.osa.org/abstract.cfm?URI=ao-36-8-1766},
    doi = {10.1364/AO.36.001766},
    abstract = {A new technique for the acceleration of iterative image restorationalgorithms is proposed. The method is based on the principles of vectorextrapolation and does not require the minimization of a cost function. Thealgorithm is derived and its performance illustrated withRichardson--Lucy (R--L) and maximum entropy (ME) deconvolutionalgorithms and the Gerchberg--Saxton magnitude and phase retrievalalgorithms. Considerable reduction in restoration times is achieved withlittle image distortion or computational overhead per iteration. The speedupachieved is shown to increase with the number of iterations performed and iseasily adapted to suit different algorithms. An example R--L restorationachieves an average speedup of 40 times after 250 iterations and an ME method20 times after only 50 iterations. An expression for estimating theacceleration factor is derived and confirmed experimentally. Comparisons withother acceleration techniques in the literature reveal significantimprovements in speed and stability.},
}
