Optoelectronics Letters

, Volume 13, Issue 6, pp 452–456 | Cite as

Single image defogging based on particle swarm optimization

  • Fan Guo (郭璠)
  • Cong Zhou (周聪)
  • Li-jue Liu (刘丽珏)
  • Jin Tang (唐琎)
Article
  • 22 Downloads

Abstract

Due to the lack of enough information to solve the equation of image degradation model, existing defogging methods generally introduce some parameters and set these values fixed. Inappropriate parameter setting leads to difficulty in obtaining the best defogging results for different input foggy images. Therefore, a single image defogging algorithm based on particle swarm optimization (PSO) is proposed in this letter to adaptively and automatically select optimal parameter values for image defogging algorithms. The proposed method is applied to two representative defogging algorithms by selecting the two main parameters and optimizing them using the PSO algorithm. Comparative study and qualitative evaluation demonstrate that the better quality results are obtained by using the proposed parameter selection method.

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Copyright information

© Tianjin University of Technology and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Fan Guo (郭璠)
    • 1
  • Cong Zhou (周聪)
    • 1
  • Li-jue Liu (刘丽珏)
    • 1
  • Jin Tang (唐琎)
    • 1
  1. 1.School of Information Science and EngineeringCentral South UniversityChangshaChina

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