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.
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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: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_199
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DOI: https://doi.org/10.1007/3-540-46084-5_199
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