Based on single image defogging algorithm
Saisai Zhang, Yimin Tian, Yunfei Du, Hongmei Chen · Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022) · 2023
The atmosphere contains many tiny, suspended particles, and due to the scattering and absorption of these particles, images can show reduced visibility, distorted colors’, blurred details and other situations. Many computer vision applications are unable to accept these degraded images and therefore require high quality input images to ensure accurate work, provided by a defogging method. Single image deblurring utilizes physical models where transmission estimation is an important parameter in obtaining a fog-free image. The fog image is analyzed and pre-processed to highlight details and make it more suitable for human and machine recognition. The analysis of different deblurring methods divides them mainly into methods based on image a priori recovery, image enhancement and deep learning. The content of defogging-related algorithms is described, and future directions are analyzed.