测试科学与仪器2026，Vol.17Issue(2)：267-277,11.DOI:10.62756/jmsi.1674-8042.2026023
结合SLIC超像素分割和透射率优化的图像去雾算法
Image defogging algorithm combining SLIC super-pixel segmentation and transmission optimization
李积英 1刘钰 1刘洁1
作者信息
- 1. 兰州交通大学 电子与信息工程学院,甘肃 兰州 730070
- 折叠
摘要
Abstract
When images are captured under hazy conditions,light is attenuated and deflected by particle scattering,resulting in reduced brightness and color distortion,which affects the imaging quality of the visual system.This paper proposes a defogging method that combines super-pixel segmentation and transmission optimization.First,the complexity of the haze image was calculated using color entropy to adaptively determine the number of super-pixel blocks.The simple linear iterative clustering(SLIC)super-pixel segmentation method was used to obtain super-pixel blocks with the same features.And the super-pixel block with the highest score was selected as a candidate block to accurately estimate the atmospheric light value.Then,the transmission was estimated using the multiscale dark channel prior and the non-local haze-lines prior,and then the initial transmission after fusion was obtained by wavelet transform.In addition,a guided filter based on unsharp masking was introduced to further improve the transmission estimation accuracy.Finally,an atmospheric scattering model was used to invert the haze-free image.We have conducted a large number of quantitative and qualitative experiments on three datasets,and the results show that the proposed algorithm can achieve a better de-fogging effect,especially in the sky region,where the image restoration effect is more prominent.关键词
超像素块/大气光值/多尺度暗通道先验/非局部雾线先验/透射率融合/非锐化掩模Key words
super-pixel blocks/atmospheric light value/multiscale dark channel prior/non-local haze-lines prior/transmission fusion/unsharpened masking引用本文复制引用
李积英,刘钰,刘洁..结合SLIC超像素分割和透射率优化的图像去雾算法[J].测试科学与仪器,2026,17(2):267-277,11.
