Neural network identification and restoration of blurred images

Viktor N. Karnaukhov; Igor N. Aizenberg; Constantine Butakoff; A V Karnaukhov; Nikolay S. Merzlyakov; Olga Milukova; Yujin Zhang

doi:10.1117/12.477158

31 July 2002 Neural network identification and restoration of blurred images

Viktor N. Karnaukhov, Igor N. Aizenberg, Constantine Butakoff, A V Karnaukhov, Nikolay S. Merzlyakov, Olga Milukova, Yujin Zhang

Author Affiliations +

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.

Citation Download Citation

Viktor N. Karnaukhov, Igor N. Aizenberg, Constantine Butakoff, A V Karnaukhov, Nikolay S. Merzlyakov, Olga Milukova, and Yujin Zhang "Neural network identification and restoration of blurred images", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477158

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available