Iterative identification and restoration of images
- 6 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
The blur identification problem is formulated as a constrained maximum-likelihood problem. The constraints directly incorporate a priori known relations between the blur (and image model) coefficients, such as symmetry properties, into the identification procedure. The resulting nonlinear minimization problem is solved iteratively, yielding a very general identification algorithm. An example of blur identification using synthetic data is given.Keywords
This publication has 4 references indexed in Scilit:
- Identification and restoration of images with symmetric noncausal blursIEEE Transactions on Circuits and Systems, 1988
- Identification of image and blur parameters for the restoration of noncausal blursIEEE Transactions on Acoustics, Speech, and Signal Processing, 1986
- Maximum likelihood and prediction error methodsAutomatica, 1980
- Maximum likelihood identification of stochastic linear systemsIEEE Transactions on Automatic Control, 1970