V. V. Khryashchev, E. A. Sokolenko, I. V. Apalkov, D. K. Kuykin, Yaroslavl State University, Yaroslavl, Russia
SYNCHROINFO JOURNAL. Volume 5, Number 2 (2019). P. 10-13.
The purpose of this work is to develop efficient and low computational complexity methods for image restoration from phases of their discrete Fourier transform. It is shown how an artificial neural network can be applied to such image restoration problem. Comparisons between neural network approach and iterative method constructed on algorithm of Gerchberg and Saxton are given. In order to reduce computational complexity a complex algorithm, which has combine denominations of different methods is developed. We illustrate the usefulness of this approach by using different images with or without noise. Efficiency and restoration capability of the methods are tested and illustrated through simulation results.
Keywords: restoration, high-quality image, Gerchberg-Saxton algorithm.
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