A novel image noise reduction method for composite multistable stochastic resonance systems
In the field of digital signal processing, image denoising is an more and more significant research direction. For the traditional noise reduction theory, noise is considered to be harmful, and the image quality can be improved by analyzing noise characteristics and filtering noise. The appearance o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-03-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023016389 |
| _version_ | 1797851799097442304 |
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| author | Shangbin Jiao Jiaqiang Shi Yi Wang Ruijie Wang |
| author_facet | Shangbin Jiao Jiaqiang Shi Yi Wang Ruijie Wang |
| author_sort | Shangbin Jiao |
| collection | DOAJ |
| description | In the field of digital signal processing, image denoising is an more and more significant research direction. For the traditional noise reduction theory, noise is considered to be harmful, and the image quality can be improved by analyzing noise characteristics and filtering noise. The appearance of stochastic resonance theory proves that noise can be used to enhance signal, which brings new inspiration to image processing. The classical bistable stochastic resonance model has the problems of high potential barrier and easy saturation, which is not conducive to the improvement of image denoising effect. In this paper, a novel type of stochastic resonance potential well model is quoted, which solves the above shortcomings of the bistable stochastic resonance model, and then combines it with the Gaussian model to propose a composite multistable stochastic resonance model. The dynamic principle of the model in signal detection is described, and the influence of system parameters on image noise reduction is analyzed. The whale optimization algorithm is used to optimize the model parameters, and an adaptive compound multistable stochastic resonance system is established to process pictures and measured radar images under different noise backgrounds. The simulation experiment and engineering application show that the model proposed in this paper solves the problem of high potential barrier and easy saturation of the bistable model, and has better image noise reduction ability compared with Wiener filter, median filter, classical bistable stochastic resonance system and novel type of stochastic resonance potential well system. |
| first_indexed | 2024-04-09T19:23:40Z |
| format | Article |
| id | doaj.art-ab4b933169b5449d978d4c938c7f992b |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-09T19:23:40Z |
| publishDate | 2023-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-ab4b933169b5449d978d4c938c7f992b2023-04-05T08:25:28ZengElsevierHeliyon2405-84402023-03-0193e14431A novel image noise reduction method for composite multistable stochastic resonance systemsShangbin Jiao0Jiaqiang Shi1Yi Wang2Ruijie Wang3School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, 710048, China; Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an, 710048, China; Corresponding author. School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, 710048, China.School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, 710048, ChinaSchool of Automation and Information Engineering, Xi'an University of Technology, Xi'an, 710048, China; Department of Aeronautical Engineering, Shaanxi Polytechnic Institute, Xianyang, 712000, ChinaSchool of Mathematics and Statistics, Ankang University, Ankang, 725000, ChinaIn the field of digital signal processing, image denoising is an more and more significant research direction. For the traditional noise reduction theory, noise is considered to be harmful, and the image quality can be improved by analyzing noise characteristics and filtering noise. The appearance of stochastic resonance theory proves that noise can be used to enhance signal, which brings new inspiration to image processing. The classical bistable stochastic resonance model has the problems of high potential barrier and easy saturation, which is not conducive to the improvement of image denoising effect. In this paper, a novel type of stochastic resonance potential well model is quoted, which solves the above shortcomings of the bistable stochastic resonance model, and then combines it with the Gaussian model to propose a composite multistable stochastic resonance model. The dynamic principle of the model in signal detection is described, and the influence of system parameters on image noise reduction is analyzed. The whale optimization algorithm is used to optimize the model parameters, and an adaptive compound multistable stochastic resonance system is established to process pictures and measured radar images under different noise backgrounds. The simulation experiment and engineering application show that the model proposed in this paper solves the problem of high potential barrier and easy saturation of the bistable model, and has better image noise reduction ability compared with Wiener filter, median filter, classical bistable stochastic resonance system and novel type of stochastic resonance potential well system.http://www.sciencedirect.com/science/article/pii/S2405844023016389Image noise reductionStochastic resonanceBistable modelCompound multistable modelWhale optimization algorithm |
| spellingShingle | Shangbin Jiao Jiaqiang Shi Yi Wang Ruijie Wang A novel image noise reduction method for composite multistable stochastic resonance systems Heliyon Image noise reduction Stochastic resonance Bistable model Compound multistable model Whale optimization algorithm |
| title | A novel image noise reduction method for composite multistable stochastic resonance systems |
| title_full | A novel image noise reduction method for composite multistable stochastic resonance systems |
| title_fullStr | A novel image noise reduction method for composite multistable stochastic resonance systems |
| title_full_unstemmed | A novel image noise reduction method for composite multistable stochastic resonance systems |
| title_short | A novel image noise reduction method for composite multistable stochastic resonance systems |
| title_sort | novel image noise reduction method for composite multistable stochastic resonance systems |
| topic | Image noise reduction Stochastic resonance Bistable model Compound multistable model Whale optimization algorithm |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023016389 |
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