This study aims to deal with the blur and color distortion of images collected by imaging equipment in hazy weather, enhance the detail information of foggy images, and improve the contrast and clarity of original images. The RGB channels of color images are processed by corresponding image enhancement algorithms. The global histogram equalization makes the whole gray histogram evenly distributed; the wavelet transform algorithm decomposes color images at multiple levels, and the multi-scale Retinex algorithm is adopted for the multi-scale transformation of images through the Gaussian convolution operation. The experimental results show that the global histogram equalization, the wavelet transform, and the multi-scale Retinex algorithm can enhance the hazy scenes in original images with their own advantages and disadvantages. Among the three algorithms, the multi-scale Retinex algorithm achieves the best dehazing and enhancement because of its enhanced brightness, prominent detail information, and slight distortion.