Image dehazing algorithm based on sky regionsegmentation and edge optimization

Abstract

Abstract: Aiming at the insufficient processing ability of the traditional dark channel prior algorithm for the sky area and the sudden depth of field area, and the degraded problems such as halo and color distortion in the restored image, a dehazing algorithm that combines area segmentation and edge optimization algorithm is proposed in this paper. Firstly, an efficient adaptive threshold segmentation algorithm is proposed to separate the sky and non-sky regions in foggy images, and the global atmospheric light value is solved in the sky area. Secondly, the dark channel and transmittance of the sky area of the foggy image are analyzed to derive the transmittance weight map, and then the transmittance of the sky area is obtained. For the non-sky area. an edge optimization algorithm is proposed to improve the dark channel and suppress the appearance of the halo phenomenon. Then the transmittance is refined by guided filtering, and the image is restored by using the atmospheric scattering model. Finally, tone mapping is performed on the restored image to make it more consistent with the visual characteristics of human eyes. The experimental results show that the proposed algorithm in this paper significantly improves dehazing effectiveness, restores the natural appearance of the sky region, effectively suppresses edge halos, and delivers superior performance in both subjective vision and objective indicators.

Key words: dark channel prior, division of sky, transmittance weight, edge optimization, tone mapping

CLC Number:

TP391

ZHAO Xiao-qiang, ZHOU Kang-yi. Image dehazing algorithm based on sky regionsegmentation and edge optimization[J]. Journal of Lanzhou University of Technology, 2025, 51(1): 92-99.

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