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Cybernetics and programming
Reference:

Development of an automated procedure for solving the problem of reconstructing blurry digital images

Korobeinikov Anatolii Grigor'evich

Doctor of Technical Science

professor, Pushkov institute of terrestrial magnetism, ionosphere and radio wave propagation of the Russian Academy of Sciences St.-Petersburg Filial

199034, Russia, g. Saint Petersburg, ul. Mendeleevskaya, 1

Korobeynikov_A_G@mail.ru
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Fedosovskii Mikhail Evgen'evich

PhD in Technical Science

Ph.D. in Technical Sciences, Professor, Head of the Systems and technological safety technology Department, St. Petersburg National Research University of Information Technologies, Mechanics and Optics, General Director of "Diakont"

197101, Russia, Saint Petersburg, Kronverskii prospekt, 49

diakont@diakont.com
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Aleksanin Sergei Andreevich

graduate student, St. Petersburg State University of Information Technologies, Mechanics and Optics

197101, Russia, Saint Petersburg, Kronverkskii Prospekt, 49

Aleksanin@diakont.com
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DOI:

10.7256/2306-4196.2016.1.17867

Review date:

04-02-2016


Publish date:

11-02-2016


Abstract: The study is devoted to methods allowing solving the problem of reconstructing blurry digital images. The authors give a mathematical formulation of the problem of removing blurring from the image. The article presents the Volterra type I equation integral equation. Based on a set of methods that solve this integral equation, the authors propose an automated procedure for solving the problem of reconstructing blurry digital images. The paper discussed in detail the method of Tikhonov regularization. Numerical experiments for different types of digital images are held. The authors give recommendation for choosing the regularization parameter. The research methodology is based on the methods for solving incorrectly posed problems, such as the task of removing the blurring of the digital image. The novelty of the research lies in the uniform approach to solving the problem of removing the blurring of a digital image. This approach has been applied to various kinds of digital images. The results of the selection of the regularization parameter, obtained using numerical experiments are different for different types of images, as expected.


Keywords: blur images, convolution, blind deconvolution, eliminate blurring, image enhancement, image processing, picture, discrepancy, Tikhonov regularization method, The automated procedure
This article written in Russian. You can find full text of article in Russian here .

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