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A New Approach to Degraded Image Processing Based on Two-Dimensional Parameter-Induced Stochastic Resonance

Bohou Xu1, Yibing Yang1, Zhong-Ping Jiang2, Daniel W. Repperger3

Department of Mechanics, State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, P.R.China
Department of Electrical and Computer Engineering, Polytechnic Institute of NYU, Brooklyn, NY 11201, U.S.A.
Air Force Research Lab., Wright-Patterson AFB, OH 45433, U.S.A.

Computer Modeling in Engineering & Sciences 2010, 57(2), 159-174. https://doi.org/10.3970/cmes.2010.057.159

Abstract

A modified two-dimensional parameter-induced stochastic resonance (2D-PSR) system is proposed. Both theoretical and simulation results indicate that the 2D-PSR system performs a resonant-like behavior when system parameters are properly adjusted. When applied to degraded image processing, 2D-PSR technique is proved to be able to attain higher SNR gain than traditional linear filters. Due to its strong robustness to environmental changes, adaptability, and complementarities with other methods, the proposed 2D-PSR technique turns out to be promising in the field of image processing.

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APA Style
Xu, B., Yang, Y., Jiang, Z., Repperger, D.W. (2010). A new approach to degraded image processing based on two-dimensional parameter-induced stochastic resonance. Computer Modeling in Engineering & Sciences, 57(2), 159-174. https://doi.org/10.3970/cmes.2010.057.159
Vancouver Style
Xu B, Yang Y, Jiang Z, Repperger DW. A new approach to degraded image processing based on two-dimensional parameter-induced stochastic resonance. Comput Model Eng Sci. 2010;57(2):159-174 https://doi.org/10.3970/cmes.2010.057.159
IEEE Style
B. Xu, Y. Yang, Z. Jiang, and D.W. Repperger, “A New Approach to Degraded Image Processing Based on Two-Dimensional Parameter-Induced Stochastic Resonance,” Comput. Model. Eng. Sci., vol. 57, no. 2, pp. 159-174, 2010. https://doi.org/10.3970/cmes.2010.057.159



cc Copyright © 2010 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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