To address the severe degradation in image quality caused by sand and dust weather conditions, a sand and dust image enhancement method based on the Lab color space is proposed. The enhancement process is decomposed into two steps: color correction and detail enhancement. The color correction part includes color bias removal and brightness stretching. Firstly, the shift characteristics of the sand and dust image histograms in the Lab and YUV color spaces are studied. Then, a Lab space color correction algorithm is proposed to correct the histogram shift, and brightness stretching is applied to enhance the image contrast after color bias removal. For detail enhancement, a haze removal method based on the estimation transmission map of saturation is introduced to further enhance the image?’?s detail information. Experimental results indicate that compared to other algorithms, the proposed algorithm can effectively remove the color bias brought by sand and dust at different levels,and demonstrates the best performance in terms of time efficiency for small and medium-sized images. In terms of quantitative evaluation, the method proposed in this paper achieves a 3.2% improvement based on a no-reference perception-based image quality evaluator and a 10.7% improvement based on an entropy-based no-reference image quality assessment. Therefore,it can effectively remove the color bias and restore clear images.