## 3 Results and Discussion
### Effect of Water Spray Removal  
The experimental results for three different scenes are presented in the following discussions, and the corresponding weather conditions are also listed in Table 1. Firstly, using Scene One shown in Figure 5a as an example, this image was taken at the North Gate of Xidian University, Xi'an, with low contrast and weak visibility. After being processed by the image enhancement algorithm in reference [24], in Figure 5b, the outlines of the buildings become more distinct. However, the whole image is still shielded by a piece of gauze due to the scattering effect. In comparison, the image in Figure 5c processed by our method shows enhancement effects in not only contrast but also the details of the image. For instance, the building marked by the red rectangle in Figure 5b is over 1.2 km away from the camera and is hardly visible in Figure 5a,b, while Figure 5c provides a much clearer image of this building as well as the buildings around it. In addition, for the nearby building about 0.83 km away from the camera outlined by a green rectangle in Figure 5a, its contrast is sharply enhanced. Overall, the method proposed in this study works well to improve the contrast of rainy-day images and optimize water spray opaque regions to some extent in rainy-day images. To demonstrate more quantitative data, a horizontal line of the intensity value versus the horizontal position of the image is plotted in Figure 5. Taking the vertical position of pixel 246 from the top, this horizontal line passes through buildings A, B, C, D, and E labeled in Figure 5c. The three shaded areas labeled by 1, 2, and 3 represent the background between A and B, B and C, and C and D, respectively. The variant trends of the blue and red curves are very similar, but the contrast of the image denoted by the blue curve is superior to that of the red one, which is improved by about 2.6 times. This is due to the removal of water spray scattering effects, which can highlight the buildings out of the background of the sky. Experimental results for the second scene are exhibited in Figure 6. The original rainy-day image in Figure 6a exhibits low contrast, whereas Figure 6b presents a much better result processed by the proposed method. Detailed improvements can be noticed through the buildings labeled as A, B, and C. Firstly, the definition and visibility are significantly improved. Not only is the building outline much clearer, but also more details (such as floors of the building) emerge in the processed image. Secondly, the horizontal lines of vertical pixels 120 and 85 from the top pass through buildings A, B, and C, and cranes D and E in both the original rainy-day image and the reconstructed image by our method. Areas 1, 3, and 4 marked by the green rectangle clearly highlight the building and cranes A, D, and E in the reconstructed image, respectively. Furthermore, a small distance between buildings B and C is also significantly exhibited by the prominent peak of the red curve in \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **Scene One** & **Scene Two** & **Scene Three** \\ \hline Temperature (°C) & 20 & 21 & 25 \\ Rainfall capacity & 1.9 & 1 & 0.6 \\ (mm/h) & 99\% & 90\% & 55\% \\ Wind strength & 5 & 10 & 10 \\ Wind direction & North & North & North \\ Rain level & Light rain & Light rain & Drizzle \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Weather conditions of different scenes. Figure 5: Rainy-day image of Scene One; (**a**) the original image; (**b**) the image reconstructed by the image enhancement algorithm [24]; (**c**) the image reconstructed by the proposed method; (**d**) horizontal line plot at the vertical position pixel 246 from the top for (**a–c**). the shaded area 2. As for contrast, the black curve presents a gentle variation trend, while the sharp concave peaks emerge from the red curve. In addition, the tower cranes show in Figure 6e,f also clearly display the changes (from invisible to visible).