Aiming at the problems of poor effect and low processing efficiency of image defogging algorithms,a fast defogging algorithm based on image fusion is proposed.Firstly,the original image is down-sampled to reduce the image size.The original image is copied to produce two images,and then the two images are converted to HSV color space respectively.For the first converted image,the v component is reduced and the accuracy of transmittance is improved.For the second converted image,the v component is adaptively processed and the s component is linearly stretched to improve the image color saturation.Then,the processed images are re-converted to RGB color space.The first re-converted image is defogged by using the improved dark channel algorithm and then histogram stretched.Finally,the two fused images are resampled.The experimental results show that the image after defogging has good subjective visual effect. Objectively,the complexity of the algorithm is reduced,and the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM),Information Entropy (IE) and Standard Deviation (SD) are significantly improved,which verify the effectiveness of the algorithm.