Aiming at the problems of detail loss,color distortion,and incomplete dehazing of image dehazing algorithms,this paper proposes a dehazing algorithm with channel estimation of the upper and lower boundaries of the light veil and adaptive fusion of atmospheric light.Firstly,the upper boundary of the atmospheric light veil is estimated according to the minimum channel of the foggy image,and the lower boundary of the atmospheric light veil is obtained based on B channel of the foggy image,RG channel difference compensation,and linear transformation.The upper and lower boundaries are optimized for approximation,and the two boundaries are fused by the wavelet transform. Secondly,the average value of the three channels of RGB and the middle channel of brightness are used to obtain different rough atmospheric light,and the average brightness value is used as the regulator for adaptive fusion.Finally,the haze-free image is recovered by using the haze removal model.The experimental results show that the images recovered by the proposed algorithm are thoroughly defogged,clear and natural,and can retain more image details with good effectiveness and robustness.