# A Nighttime and Daytime Single-Image Dehazing Method
## 4 Experimental Results and Discussion
### Real Haze-Free Image Comparison  
Apart from the above experiments, we also tested 80 images from two public image datasets, O-HAZE and I-HAZE [32] for verification. These are dehazing benchmarks that include real hazy and haze-free images. Figure 7 shows a part of the experimental results, and Table 3 shows the average objective indicators of these two datasets. Through the comparison in Figure 7, we can see that our results are close to the real haze-free image. At the same time, it confirms the advantages and disadvantages of the previous methods. All of the indicators in Table 3, except for the PSNR in O-HAZE, are higher than the existing methods. This indicator is lower than other methods because O-HAZE contains a lot of white dense fog scenes. When estimating the ambient illumination through the local filter window, the ambient illumination may be overestimated due to the influence of white dense haze, resulting in haze residue. Therefore, it is a defect of the proposed method to deal with the local white dense haze.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Fig**} & \multicolumn{2}{c}{**[PERSON] et al. [26]**} & \multicolumn{2}{c}{**[PERSON] et al. [24]**} & \multicolumn{2}{c}{**[PERSON] et al. [25]**} & \multicolumn{2}{c}{**[PERSON]**} \\ \cline{2-13}  & **SSIM** & **PSNR** & **CIEDE** & **SSIM** & **PSNR** & **CIEDE** & **SSIM** & **PSNR** & **CIEDE** & **SSIM** & **PSNR** & **CIEDE** \\ \hline N1 & 0.648 & 17.078 & 19.390 & 0.662 & 16.827 & 24.269 & **0.813** & **23.473** & 13.374 & 0.722 & 21.302 & **12.715** \\ N2 & 0.785 & 22.409 & 20.535 & 0.604 & 16.792 & 24.755 & 0.853 & **24.581** & 19.095 & **0.875** & 23.336 & 9.879 \\ N3 & 0.617 & 16.087 & 18.850 & 0.390 & 10.847 & 38.178 & 0.773 & 22.188 & 16.037 & **0.807** & **23.065** & **10.441** \\ N4 & 0.835 & 20.538 & 24.970 & 0.509 & 12.383 & 31.265 & 0.802 & 17.728 & 19.609 & **0.862** & **27.378** & **8.717** \\ N5 & 0.721 & 17.354 & 19.806 & 0.791 & 19.226 & 19.437 & 0.886 & 19.814 & 20.679 & **0.893** & **23.855** & **9.641** \\ N6 & 0.505 & 15.928 & 38.064 & 0.464 & 12.897 & 34.054 & **0.856** & 22.522 & 16.096 & 0.850 & **26.994** & **6.379** \\ N7 & 0.754 & 19.301 & 24.117 & 0.578 & 12.760 & 29.582 & **0.864** & 19.481 & 13.986 & 0.840 & **23.879** & **9.816** \\ N8 & 0.789 & 20.211 & 15.214 & 0.557 & 14.504 & 29.129 & 0.919 & 24.864 & 13.196 & **0.937** & **28.517** & **5.432** \\ N9 & 0.544 & 13.537 & 24.930 & 0.516 & 16.180 & 21.882 & 0.785 & 21.197 & 20.353 & **0.847** & **24.699** & **9.159** \\ N10 & 0.624 & 14.883 & 21.399 & 0.488 & 12.455 & 32.707 & **0.812** & **22.313** & 15.336 & 0.770 & 20.74 & **14.063** \\ \hline AVG & 0.682 & 17.733 & 22.727 & 0.556 & 14.487 & 28.526 & 0.836 & 21.816 & 16.776 & **0.840** & **24.382** & **9.624** \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison Index of Nighttime Dehazing Effect.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Fig**} & \multicolumn{2}{c}{**[PERSON] et al. [9]**} & \multicolumn{2}{c}{**[PERSON] et al. [14]**} & \multicolumn{2}{c}{**[PERSON] et al. [21]**} & \multicolumn{2}{c}{**[PERSON] et al. [15]**} & \multicolumn{2}{c}{**[PERSON]**} \\ \cline{2-13}  & **SSIM** & **PSNR** & **CIEDE** & **SSIM** & **PSNR** & **CIEDE** & **SSIM** & **PSNR** & **CIEDE** & **SSIM** & **PSNR** & **CIEDE** & **SSIM** & **PSNR** & **CIEDE** \\ \hline D1 & 0.814 & 13.271 & 18.816 & 0.504 & 8.828 & 35.924 & 0.750 & 9.465 & 31.349 & 0.494 & 8.951 & 33.463 & 0.764 & **21.993** & **5.157** \\ D2 & **0.908** & 17.852 & 14.675 & 0.833 & 18.941 & 12.504 & 0.864 & 17.658 & 18