Type of Blur and Blur Parameters Identification Using Neural Network and Its Application to Image Restoration

Authors:
Igor Aizenberg;Taras Bregin;Constantine Butakoff;Victor N. Karnaukhov;Nickolay S. Merzlyakov;Olga Milukova
Affiliations:
-;-;-;-;-;-
Venue:
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Year:
2002

Citing 2
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Abstract

The original solution of the blur and blur parameters identification problem is presented in this paper. A neural network based on multivalued neurons is used for the blur and blur parameters identification. It is shown that using simple single-layered neural network it is possible to identify the type of the distorting operator. Four types of blur are considered: defocus, rectangular, motion and Gaussian ones. The parameters of the corresponding operator are identified using a similar neural network. After a type of blur and its parameters identification the image can be restored using several kinds of methods.