# Saturation-Based Airlight Color Restoration of Hazy Images
## 4 Experimental Results and Discussions
### Performance Evaluation Using Ground Truth Image
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Image** & **HRDCP** & **NGCCLAHE** & **WSDACC** & **Proposed** \\ \hline \multirow{8}{*}{PSNR} & Column 1 & 25.6801 & 27.6232 & 12.9887 & 29.3583 \\  & Column 2 & 18.3533 & 20.6083 & 13.9061 & 21.9567 \\  & Column 3 & 18.5879 & 24.1812 & 14.3154 & 25.4478 \\  & Column 4 & 30.8870 & 30.2614 & 13.8340 & 31.8312 \\  & Column 5 & 18.8900 & 19.9033 & 15.2217 & 21.8796 \\  & Column 6 & 17.9036 & 16.6909 & 13.6151 & 18.6536 \\  & Column 7 & 21.8741 & 22.5892 & 12.3425 & 23.5417 \\  & Column 8 & 23.6716 & 23.1715 & 14.6542 & 24.4558 \\  & **Average** & **21.9810** & **23.1286** & **13.8597** & **24.6406** \\ \hline \multirow{8}{*}{CIEDE 2000} & Column 1 & 65.0429 & 58.3551 & 68.994 & 55.5198 \\  & Column 2 & 80.8358 & 83.0109 & 101.178 & 70.1804 \\  & Column 3 & 71.6801 & 64.0757 & 83.9369 & 59.0298 \\  & Column 4 & 62.8703 & 60.0154 & 102.421 & 44.4957 \\  & Column 5 & 87.177 & 86.2875 & 86.9605 & 67.5862 \\  & Column 6 & 73.3669 & 74.9258 & 88.2843 & 71.7223 \\  & Column 7 & 67.9032 & 70.0154 & 97.6982 & 57.9881 \\  & Column 8 & 73.1579 & 75.1231 & 84.7146 & 62.4879 \\  & **Average** & **72.75426** & **71.47611** & **89.27344** & **61.12628** \\ \hline \multirow{8}{*}{CIE94} & Column 1 & 40.996 & 37.9644 & 61.1512 & 35.6449 \\  & Column 2 & 56.8746 & 54.1844 & 64.2783 & 51.4884 \\  & Column 3 & 55.6438 & 47.5759 & 64.1364 & 46.0510 \\  & Column 4 & 38.7339 & 39.17 & 62.4296 & 37.1594 \\  & Column 5 & 55.4124 & 53.6296 & 59.5817 & 43.9504 \\  & Column 6 & 57.1691 & 57.7260 & 64.5412 & 54.5976 \\  & Column 7 & 50.4363 & 47.0993 & 64.8543 & 45.4348 \\  & Column 8 & 46.5830 & 45.4304 & 59.5978 & 43.7097 \\  & **Average** & **50.2311** & **47.8475** & **62.5713** & **44.7545** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of PSNR, CIEDE2000, and CIE94 of the Dense-HAZE dataset. The results of the visual comparison of the O-HAZE images showed that the hazy images in Figure 13 had general gray-tone haze as opposed to those of Dense-HAZE; thus, the existing color restoration methods damaged the color information of objects to some degree, as discussed in Section 4.1. When compared to the ground truth images, the resulting HRDCP and NGCCLAHE images showed clear color distortion of the objects, and in particular, the hue became excessively brighter than in the original images. Further, HRDCP applied excessive contrast improvement on Figure 13, resulting in large shadows on the images, and compared to the original images, the edges of close objects were severely emphasized. Furthermore, WSDACC increased the red color in some hazy images, resulting in color cast. In contrast, our method increased the visibility of hazy areas, preserving the object color close to that of the ground truth images. In particular, our results preserved the object color and increased the contrast of the areas where haze existed, producing natural results without visual burdens. The quantitative comparison of the restoration images of O-HAZE in Table 3, similar to Table 2, showed that our proposed method showed the best results. Our proposed method demonstrated greater deviations from Dense-HAZE compared to existing methods and achieved superior visibility improvement and color restoration performance values. The results in Table 4 show that the proposed algorithm has a faster execution time than WSDACC, but it took longer than NGCCLAHE and WSDACC due to the computational process of clustering. Figure 13: Comparison of the resulting images from O-HAZE dataset (**a**) ground truth image; (**b**) hazy image; (**c**) HRDCP; (**d**) NGCCLAHE; (**e**) WSDACC; (**f**) proposed dehazing method. color space for both color correction and dehazing to address the problem of color distortion in traditional RGB channels. The proposed method first white-balances only the hue of the airglow or sky area, and not the entire scene, reflecting the nature of the fog which is directly affected.