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An iterative method for restoring noisy blurred images

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4 Author(s)
Katsaggelos, A.K. ; Georgia Institute of Technology, Atlanta, Georgia ; Biemond, J. ; Mersereau, R.M. ; Schafer, R.W.

This paper introduces a new iterative image restoration method which is capable of restoring noisy, blurred images by incorporating a priori knowledge about the image and noise statistics into the iterative procedure. The iteration equation consists of a prediction part which is based on a noncausal image model description and an innovation part which is weighted by a gain factor. The gain is computed using a linear MSE optimization procedure and is updated at each step of the iteration. This image restoration scheme can be interpreted as an iterative procedure with a statistical constraint on the image data.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.  (Volume:9 )

Date of Conference:

Mar 1984