Type of blur and blur parameters identification using neural network and its application to image restoration

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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 multi-valued 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. © Springer-Verlag Berlin Heidelberg 2002.

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Aizenberg, I., Bregin, T., Butakoff, C., Karnaukhov, V., Merzlyakov, N., & Milukova, O. (2002). Type of blur and blur parameters identification using neural network and its application to image restoration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2415 LNCS, pp. 1231–1236). Springer Verlag. https://doi.org/10.1007/3-540-46084-5_199

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