Theoretical analysis of image processing using parameter-tuning stochastic resonance technique

Bohou Xu, Zhong-Ping Jiang, Xingxing Wu, Daniel W. Repperger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Parameter-tuning stochastic resonance has been successfully applied to one-dimensional signal processing. This paper explores the feasibility to extend this technique for image processing. Based on the two-dimensional nonlinear bistable dynamic system, the equation satisfied by the system output probability density function is derived for the first time. The corresponding equation for the one-dimensional system is the famous Fokker-Planck-Kolmogorov (FPK) equation. The stationary solution, eigenvalues and eigenfunctions of this equation are then investigated. The upper bound of the system response speed and the related calculation algorithm which are necessary for the applications of this technique to image processing are also proposed in this paper. Finally, the potential applications of this approach in image processing and some future research are suggested.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 American Control Conference, ACC
Pages1747-1752
Number of pages6
DOIs
StatePublished - 2007
Event2007 American Control Conference, ACC - New York, NY, United States
Duration: Jul 9 2007Jul 13 2007

Other

Other2007 American Control Conference, ACC
CountryUnited States
CityNew York, NY
Period7/9/077/13/07

Fingerprint

Image processing
Tuning
Fokker Planck equation
Eigenvalues and eigenfunctions
Probability density function
Signal processing
Dynamical systems

Keywords

  • Filtering
  • Image processing
  • Nonlinear systems
  • Stochastic resonance
  • Stochastic systems

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Xu, B., Jiang, Z-P., Wu, X., & Repperger, D. W. (2007). Theoretical analysis of image processing using parameter-tuning stochastic resonance technique. In Proceedings of the 2007 American Control Conference, ACC (pp. 1747-1752). [4282316] https://doi.org/10.1109/ACC.2007.4282316

Theoretical analysis of image processing using parameter-tuning stochastic resonance technique. / Xu, Bohou; Jiang, Zhong-Ping; Wu, Xingxing; Repperger, Daniel W.

Proceedings of the 2007 American Control Conference, ACC. 2007. p. 1747-1752 4282316.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Xu, B, Jiang, Z-P, Wu, X & Repperger, DW 2007, Theoretical analysis of image processing using parameter-tuning stochastic resonance technique. in Proceedings of the 2007 American Control Conference, ACC., 4282316, pp. 1747-1752, 2007 American Control Conference, ACC, New York, NY, United States, 7/9/07. https://doi.org/10.1109/ACC.2007.4282316
Xu B, Jiang Z-P, Wu X, Repperger DW. Theoretical analysis of image processing using parameter-tuning stochastic resonance technique. In Proceedings of the 2007 American Control Conference, ACC. 2007. p. 1747-1752. 4282316 https://doi.org/10.1109/ACC.2007.4282316
Xu, Bohou ; Jiang, Zhong-Ping ; Wu, Xingxing ; Repperger, Daniel W. / Theoretical analysis of image processing using parameter-tuning stochastic resonance technique. Proceedings of the 2007 American Control Conference, ACC. 2007. pp. 1747-1752
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