Please use this identifier to cite or link to this item:
http://elar.urfu.ru/handle/10995/102048
Title: | Restoration of Static JPEG Images and RGB Video Frames by Means of Nonlinear Filtering in Conditions of Gaussian and Non-Gaussian Noise |
Authors: | Sokolov, R. I. Abdullin, R. R. |
Issue Date: | 2017 |
Publisher: | Blackwell Publishing Ltd |
Citation: | Sokolov R. I. Restoration of Static JPEG Images and RGB Video Frames by Means of Nonlinear Filtering in Conditions of Gaussian and Non-Gaussian Noise / R. I. Sokolov, R. R. Abdullin. — DOI 10.1002/2017RS006392 // Radio Science. — 2017. — Vol. 52. — Iss. 11. — P. 1363-1373. |
Abstract: | The use of nonlinear Markov process filtering makes it possible to restore both video stream frames and static photos at the stage of preprocessing. The present paper reflects the results of research in comparison of these types image filtering quality by means of special algorithm when Gaussian or non-Gaussian noises acting. Examples of filter operation at different values of signal-to-noise ratio are presented. A comparative analysis has been performed, and the best filtered kind of noise has been defined. It has been shown the quality of developed algorithm is much better than quality of adaptive one for RGB signal filtering at the same a priori information about the signal. Also, an advantage over median filter takes a place when both fluctuation and pulse noise filtering. ©2017. American Geophysical Union. All Rights Reserved. |
Keywords: | IMAGE RESTORATION NON-GAUSSIAN NOISE NONLINEAR MARKOV FILTERING SIGNAL PROCESSING GAUSSIAN DISTRIBUTION IMAGE PROCESSING IMAGE RECONSTRUCTION INFORMATION FILTERING MARKOV PROCESSES MEDIAN FILTERS NONLINEAR FILTERING RESTORATION SIGNAL PROCESSING SIGNAL TO NOISE RATIO COMPARATIVE ANALYSIS FILTER OPERATIONS IMAGE FILTERING NON-GAUSSIAN NOISE PRIORI INFORMATION PROCESS FILTERING SIGNAL FILTERING SPECIAL ALGORITHMS GAUSSIAN NOISE (ELECTRONIC) |
URI: | http://elar.urfu.ru/handle/10995/102048 |
Access: | info:eu-repo/semantics/openAccess |
SCOPUS ID: | 85038216671 |
WOS ID: | 000418251400005 |
PURE ID: | 953138a2-bf81-4b01-8e65-ff3d7b42ae40 6212436 |
ISSN: | 486604 |
DOI: | 10.1002/2017RS006392 |
Appears in Collections: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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2-s2.0-85038216671.pdf | 2,91 MB | Adobe PDF | View/Open |
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