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Identification and restoration of noisy blurred images using the expectation-maximization algorithm

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3 Author(s)
R. L. Lagendijk ; Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands ; J. Biemond ; D. E. Boekee

A maximum-likelihood approach to the blur identification problem is presented. The expectation-maximization algorithm is proposed to optimize the nonlinear likelihood function in an efficient way. In order to improve the performance of the identification algorithm, low-order parametric image and blur models are incorporated into the identification method. The resulting iterative technique simultaneously identifies and restores noisy blurred images

Published in:

IEEE Transactions on Acoustics, Speech, and Signal Processing  (Volume:38 ,  Issue: 7 )