Image Defogging Combining Colour Space and Fog Line Dark Channel

ZHENG Chaoyu; CHENG Fang

doi:10.3969/j.issn.1672-9722.2025.11.039

Abstract：This paper addresses the problem that the problem that traditional defogging methods do not recover the colour of the image to a high degree and can easily lead to artefacts and block effects in the transition edge areas and depth of field areas.In this paper,an image fusion defogging algorithm combining colour space and fog line dark channel prior is proposed.Firstly,based on the rough transmittance values estimated by the dak channel method,the transmittance valuations of several fog lines are correct-ed and adaptively adjusted to obtain a defogged image with low saturation and dark colours using the improved atmospheric light val-ues and transmittance valuations.Secondly,the original fogged image is converted to HSI colour space and the S and I components are enhanced using the MSRCR algorithm to obtain a second image with high saturation and high luminance.Finally,the two images are linearly fused by using weighted averaging to obtain the recovered image.The experimental results show that the proposed new method can effectively avoid the halo effect and colour distortion while better preserving the colour characteristics and detail informa-tion of the original fogged images meanwhile,the mean values of peak signal-to-noise ratio,structural similarity and information en-tropy of the method in five groups of images are 16.9699,0.8381 and 7.5203,respectively,which are all better than the other four comparison algorithms and have certain feasibility.