# Saturation-Based Airlight Color Restoration of Hazy Images
## 4 Experimental Results and Discussions
### Visual Comparison of Various Hazy Images  
In this study, Laboratory for Image and Video Engineering (LIVE) [34] and sand dust image [35] datasets were used as test images to perform dehazing on actual hazy and color-cast images. Through Figures 8 and 9, the dehazing performance on various color-cast hazy images was evaluated. Figures 8 and 9 show the visual evaluation of the hazy images of various concentrations and hazy images damaged by various colors, respectively. The visual evaluation in Figure 8 shows that HRDCP resulted in an intensified halo effect, shadowing, and a grayscale effect with increased haze concentration, and in particular, the saturation of the image dropped significantly due to the excessive contrast improvement in the image with a lower-middle concentration. In addition, HRDCP added red color to the sky area due to the white balance in the low image, with an extremely small addition of haze color. NGCCLAHE also added red color to the low image, and reduced saturation in the lower-middle image. In contrast, WSDACC increased color distortion as the yellow haze was distributed widely in the image. The proposed method showed excellent visual results for all images in Figure 8, and in the low image, it showed superb results in both visibility improvement and color restoration. Furthermore, it preserved as much as possible the sky area and lighting area, which are susceptible to distortion, noise, or shadowing. Figure 9 presents the color restoration performance against the red, yellow, green, and blue color-cast images in order, all of which included objects such as trees, rivers, and lakes whose colors are similar to hazy veils. As shown in Figure 9, HRDCP, which offers strong color restoration performance, lost the color information of the scenes in all test images. While NGCCLAHE exhibited a considerable improvement over HRDCP, the loss of color information was considerable in the case of large-scale scenes in the yellow or blue image, such as trees or lakes. WSDACC introduced color distortions for images with high saturation haze veils, similar to that in Figure 9. In contrast, our approach used an airlight color detection algorithm to preserve the original colors of scenes, even those closely resembling haze. Figure 8: Color restoration results of hazy images at various concentration levels: (**a**) original hazy image, (**b**) HRDCP, (**c**) NGCCLAHE, (**d**) WSDACC, and (**e**) proposed dehazing method. Figure 9: Color restoration results of hazy images cast with various colors: (**a**) original hazy image, (**b**) HRDCP, (**c**) NGCCLAHE, (**d**) WSDACC, and (**e**) proposed dehazing method. In this study, the results of the general hazy images, in which airlight is in grayscale, are shown in Figure 10, and the versatility of the algorithm was evaluated. To verify the dehazing performance of the distant scenes shown in Figure 10, their detailed shots are shown in Figure 11. The detailed areas correspond to the white squares in Figure 10.  
In this paper, quality parameters and no-reference evaluation metrics are used to evaluate the quality of typical fog images. For the resulting image in Figure 10, the edge ratio (e) [36], the mean slope ratio (\(\mathbf{r}\)) [36], fog reduction factor (FRF) [37], and perception-based image quality evaluator (PIQE) [38] were used as quality evaluation metrics to show the quantitative results. Of these, the higher the e, \(\mathbf{r}\), FRF, and PIQE, the better the quality, and the lower the PIQE, the better the value. The results of all quality metrics for Figure 10 are shown in Table 1.  
Figure 10 shows images with high saturation or those in which an object occupies a large area of the image. In particular, test images 1-4 biased the histogram of the image with the colors of red vehicles, orange flowers, yellow fields, and green mountains. The detailed shots in Figure 11 show the close scenes in test 1 and the distant scenes in tests 2-6.