• Laser & Optoelectronics Progress
  • Vol. 57, Issue 16, 161003 (2020)
Zengli Liu and Yu Fu*
Author Affiliations
  • Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan 650504, China
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    DOI: 10.3788/LOP57.161003 Cite this Article Set citation alerts
    Zengli Liu, Yu Fu. Image Dehazing Algorithm Based on Adaptive Constraint Correction of Transmittance[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161003 Copy Citation Text show less

    Abstract

    In order to solve the problem of color offset distortion and halo effect when using traditional dehazing algorithms to process the images with large areas of sky and abrupt changes of scene depth, an image dehazing optimization algorithm based on transmittance adaptive constraint correction is proposed. The algorithm combines automatic and manual estimation in the atmospheric light value estimation stage, which is convenient for users to further adjust the dehazing results according to their needs. For the estimation of transmittance, first, the lower limit of the estimation of transmittance is obtained through the boundary constraint of the scene radiance to replace the fixed value set in the traditional algorithm. Then, the threshold value is set to determine whether the pixel is within the same depth of scene, and the corresponding adaptive correction is made according to the intensity difference ratio to optimize the estimation of transmittance. The results show that this algorithm can achieve a better image dehazing effect for the haze image. It can not only restore the clear image, enhance the visual effect, and usability of the images, but also effectively avoid the color deviation artifact in the bright area of the image and halo effect in the sudden changes of depth of areas.
    Zengli Liu, Yu Fu. Image Dehazing Algorithm Based on Adaptive Constraint Correction of Transmittance[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161003
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