Low-quality images under harsh atmospheric conditions such as colored fog， smoke and dust are characterized by low visibility and color cast， which bring difficulties to human observation and computer vision applications. Current enhancement algorithms for such images usually ignore the influence of the distance from the scene to the camera on the color cast. In order to better restore color while enhancing visibility， a relationship model between visibility reduction， color cast and distance and its solution method are proposed. First， the distance is estimated by the local brightness of the image， and the color cast matrix of the image is estimated by the distance. Then， the visibility and color restored image is obtained by solving the degradation model. Finally， the restored image is fused with a contrast limited adaptive histogram equalization （CLAHE）enhanced image by distance weighting for further detail enhancement. Experiments show that， compared with similar methods， the proposed method achieves high image quality evaluation indexes and has significantly better color recovery results.