Identification and Restoration of Images with Symmetric Noncausal Blurs
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چکیده
In this paper, a parallel identification and restoration procedure is described for images with symmetric, noncausal blurs. It is shown that the identification problem can be specified as a parallel set of one-dimensional complex autoregressive moving-average (ARMA) identification problems. By expressing the ARMA models as equivalent infiniteorder autoregressive (AR) models, an entirely linear estimation procedure can be followed. It will be shown that under the condition of blur symmetry, it is possible to reconstruct a useful noncausal set of MA (blur) parameters from the identified minimum-phase set. The thus identified image model and blur parameters are supplied to a parallel Kalman restoration filter. Several identification and restoration results on image data are given as examples.
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