Electronic Science and Technology ›› 2020, Vol. 33 ›› Issue (4): 61-65.doi: 10.16180/j.cnki.issn1007-7820.2020.04.011

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Research on Fog Removal Based on Dark Primary Color Optimization Algorithms

LU Huan   

  1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 20093, China
  • Received:2019-05-17 Online:2020-04-15 Published:2020-04-23


In the traditional dark-primary prior dehazing algorithm, the fogging effect in some scenes could not meet the assumption of dark primary color a priori, which leaded to poor dehazing; effect. In this paper, an improved dehazing algorithm was proposed based on the above results. Firstly, the atmospheric scattering model was established according to McCartnet’s theory. Then the transmission map was roughly estimated according to the dark channel prior theory. The tolerance parameter was introduced and the threshold was set to recalculate the transmission map of the high light regions. To achieve self-adapted function of transmission map in high light regions. In order to restore the dark color of the image, an improved linear adjustment method was applied to adjust the brightness of the image. The experimental results showed that compared with the original algorithm, the improved algorithm could effectively estimate the atmospheric light value and reduced the color distortion of the high light regions. The restored image could maintain sufficient brightness without losing the details of the image, and the visual effect was remarkable improved.

Key words: dehazing, dark channel prior, high light regions, transmissionmap, brightness

CLC Number: 

  • TP391.41