Using a hybrid of fuzzy theory and neural network filter for image dehazing applications

Jyun Guo Wang, Shen Chuan Tai, Chin Ling Lee, Cheng Jian Lin, Tsung Hung Lin

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

Abstract

When photographs are being taken in an outdoor environment, the medium in air will cause light attenuation and further reduce image quality, and this impact is especially obvious in a hazy environment. Reduction of image quality results in the loss of information, which renders an image recognition system unable to identify objects in the image. In order to eliminate the hazy effect on images and improve the visual quality, this paper presents an efficient method combining the fuzzy inference system and the neural network filter to solve image dehazing. During dehazing, the fuzzy inference system is adopted to estimate the variations in light attenuation, and the erosion of morphological operation and the neural network filter are used to eliminate the halation and achieve optimization in transmission map refinement. Finally, the brightest 1% of the atmospheric light is utilized to calculate the color vector of atmospheric light to eliminate color cast. The experimental results indicate that the proposed method is superior to other dehazing methods.

Original languageEnglish
Title of host publication2016 International Joint Conference on Neural Networks, IJCNN 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages692-697
Number of pages6
ISBN (Electronic)9781509006199
DOIs
Publication statusPublished - 2016 Oct 31
Event2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada
Duration: 2016 Jul 242016 Jul 29

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2016-October

Other

Other2016 International Joint Conference on Neural Networks, IJCNN 2016
CountryCanada
CityVancouver
Period16-07-2416-07-29

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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