Haze removal using dark channel for remote sensing images of natural disaster
Yuquan Gan, Wen De-sheng, Le Wang, Xiaohui Gao, Cui-Yu Wei · Institutional Repository of Xi'an Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (Xian Institute of Optics and Precision Mechanics) · 2015
In order to remove the haze in natural disaster remote sensing images, an approach based on dark channel and hazy image degradation model was presented, which could remove the haze by using guided filter. Firstly, images of natural disaster were divided into fog area and mist area by threshd, and different methods were used to obtain the dark channel of the images.Then, guided filter was used to optimize the transmmission map, and the contrast of the images was stretched to improve the dynamic range of the images. A series of natural disaster remote sensing images were chosen to test the alogrithm of haze removal. Finally, a series of evaluate parameters were proposed to assess the method. The result shows that the proposed algorithm can remove the haze of the images, improve the image quality, and enhance the color and detail of the images, so that the high-quality images can be obtained, which meet the requirements of haze removal for natural disaster remote sensing images to some extent. ©, 2015, Chinese Optical Society. All right reserved.