Single Image Haze Removal Using Ambient Light Estimation and Region Segmentation
Yuji Araki, Koichi Ichige · 2018
In this paper, we propose an accurate single image haze removal method that divides hazed images into regions in advance, where haze removal processing is difficult, and applies it to the estimation of ambient light. In addition, we propose a method of iterative haze removal for further improving image accuracy. The conventional method has a problem that the amount of haze is estimated larger than the actual amount in the regions where the distance between the photographic spot and subject is long, and causes that ambient light cannot be estimated accurately. The regions which are difficult to be processed mainly white and sky regions. If those regions are processed in the same way as the other regions, bad effects are observed such as the image becomes darker or its color changes too much. In the proposed method, the regions which are difficult to estimate the amount of haze are divided into multiple regions by extracting pixels similar to the feature pixels, and then ambient light is determined from the regions where haze removal processing is easy. The proposed method can easily extract the appropriate color of haze for any given image.