Fast single image de-hazing using characteristics of RGB channel of foggy image

Dubok Park, David K. Han, Changwon Jeon, Hanseok Ko

Research output: Contribution to journalArticle

11 Citations (Scopus)


Images captured under foggy conditions often exhibit poor contrast and color. This is primarily due to the air-light which degrades image quality exponentially with fog depth between the scene and the camera. In this paper, we restore fog-degraded images by first estimating depth using the physical model characterizing the RGB channels in a single monocular image. The fog effects are then removed by subtracting the estimated irradiance, which is empirically related to the scene depth information obtained, from the total irradiance received by the sensor. Effective restoration of color and contrast of images taken under foggy conditions are demonstrated. In the experiments, we validate the effectiveness of our method compared with conventional method.

Original languageEnglish
Pages (from-to)1793-1799
Number of pages7
JournalIEICE Transactions on Information and Systems
Issue number8
Publication statusPublished - 2013 Aug 27



  • Air-light
  • De-hazing
  • Depth estimation
  • Image restoration

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Software
  • Artificial Intelligence
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition

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