基于饱和度运算单幅图像去雾算法

在雾、霾等恶劣的天气条件下,大气介质中悬浮粒子的散射和吸收作用会严重退化户外拍摄图像,造成图像识别率降低.从单色大气散射模型和暗原色先验规律,提出面向视觉感知的HSI颜色模型的饱和度的新算法,从而实现图像去雾,对于去雾图像最小值像素点采用极大值和极小值进行估计,并对透射率进行修正.该算法能够有效地提高清晰度,能很好地运用于单幅图像去雾.

Single image defogging algorithm based on saturation operation

In Bad weather,such as fog,haze and mist,the scattering and absorption of the suspended particles can significantly degrade the visibility of outdoor scenes in the atmospheric media.This algorithm starting with the monochromatic atmospheric scattering model and dark channel prior,defines a novel saturation operation based on the HSI color model for visual perception.It helps to realize defogging for the original image and according to estimating the maximum and minimum of the least valve of the image defogging pixel to revise the transmittance.The algorithm in this thesis has a significant effect on the improvement of the sharpness and it is appropriate for single image defogging.Bad weather,such as fog,haze and mist,can significantly degrade the visibility of outdoor scenes due to the suspending in the atmospheric medium.This algorithm starts with the atmosphere scattering model and dark channel prior,defines a novel saturation operation based on the HSI color model for visual perception,and the original image was defogged.In comparison with other algorithms,the experimental results show that the running efficiency of the proposed method is improved.And the proposed method effectively enhances clarity,so it is appropriate for single image defogging.