31 July 2002 Neural network identification and restoration of blurred images
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Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477158
Event: Second International Conference on Image and Graphics, 2002, Hefei, China
Abstract
There are different techniques available for solving of the restoration problem including Fourier domain techniques, regularization methods, recursive and iterative filters to name a few. But without knowing at least approximate parameters of the blur, these methods often show poor results. If incorrect blur model is chosen then the image will be rather distorted much more than restored. 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 it is possible to identify the type of the distorting operator by using simple single-layered neural network. Four types of blur operators are considered: defocus, rectangular, motion, and Gaussian ones. The parameters of the corresponding operator are identified by using a similar neural network. After identification of the blur type and its parameters the image can be restored using different methods. Some fundamentals of image restoration techniques are also considered.
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Viktor N. Karnaukhov, Viktor N. Karnaukhov, Igor N. Aizenberg, Igor N. Aizenberg, Constantine Butakoff, Constantine Butakoff, A V Karnaukhov, A V Karnaukhov, Nikolay S. Merzlyakov, Nikolay S. Merzlyakov, Olga Milukova, Olga Milukova, Yujin Zhang, Yujin Zhang, "Neural network identification and restoration of blurred images", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477158; https://doi.org/10.1117/12.477158
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