Constrained optimization for image restoration using nonlinear programming

The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear programming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty func...

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Bibliographic Details
Published inICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing Vol. 10; pp. 676 - 679
Main Authors Chia-Lung Yeh, Roland Chin
Format Conference Proceeding
LanguageEnglish
Published IEEE 1985
Subjects
Constraint optimization
Convergence
Degradation
Entropy
Filters
Gradient methods
H infinity control
Image restoration
Image storage
Optimization methods
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DOI10.1109/ICASSP.1985.1168350

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Summary:The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear programming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty function method of nonlinear programming is used. Both linear or nonlinear object function, and linear or nonlinear constraint functions can be incorporated in the formulation. This formulation provides a generalized approach to solve constrained optimization problems for image restoration. Experiments using this scheme have been performed. The results are compared with those obtained from other restoration methods and the comparative study is presented.
DOI:10.1109/ICASSP.1985.1168350