Iterative Fusion Defogging Algorithm Based on Wavelet Transform

The image collected outdoors in a foggy environment is prone to low contrast and loss of details. To solve this problem, our study proposes an image fusion method based on multiscale Retinex theory and wavelet transform to restore foggy images. First, the MSR algorithm was used to enhance the collected foggy image. Then, the "db5" wavelet basis was used to merge the brightness component V of the foggy image and the enhanced image, and the saturation component of the foggy image was constrained. Finally, the defogging image was generated. The threshold value was set, and the fog image with relatively high fog concentration was second iteratively fused using wavelet transform to remove residual fog. The experimental results show that the proposed algorithm can effectively restore foggy images with different concentrations. Moreover, the image after fog removal can enhance the details of the dark area, improve the image color, and enrich the image information. Using wavelet fusion preserves more image information so that the image color is rich and natural. Thus, the entire smooth fusion image has a good restoration effect.