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

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

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

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