Enhancement of image degraded by fog using cost function based on human visual model

Dongjun Kim, Changwon Jeon, Bonghyup Kang, Hanseok Ko

Research output: Contribution to conferencePaper

19 Citations (Scopus)

Abstract

In foggy weather conditions, images become degraded due to the presence of airlight that is generated by scattering light by fog particles. In this paper, we propose an effective method to correct the degraded image by subtracting the estimated airlight map from the degraded image. The airlight map is generated using multiple linear regression, which models the relationship between regional airlight and the coordinates of the image pixels. Airlight can then be estimated using a cost function that is based on the human visual model, wherein a human is more insensitive to variations of the luminance in bright regions than in dark regions. For this objective, the luminance image is employed for airlight estimation. The luminance image is generated by an appropriate fusion of the R, G, and B components. Representative experiments on real foggy images confirm significant enhancement in image quality over the degraded image.

Original languageEnglish
Pages64-67
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI - Seoul, Korea, Republic of
Duration: 2008 Aug 202008 Aug 22

Other

Other2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI
CountryKorea, Republic of
CitySeoul
Period08/8/2008/8/22

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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    Kim, D., Jeon, C., Kang, B., & Ko, H. (2008). Enhancement of image degraded by fog using cost function based on human visual model. 64-67. Paper presented at 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI, Seoul, Korea, Republic of. https://doi.org/10.1109/MFI.2008.4648109