Image Dehazing Algorithm Based on Atmospheric Scattering Model
Zhaomin Li · 2022
With the development of electronic circuit technology and optical imaging technology, the resolution and clarity of captured images are getting higher and higher. However, in hazardous weather conditions such as heavy fog, the photos taken can be extremely damaging. The main cause of image damage is that the surface light of the venue interacts with particles suspended in the air during the approximation process, resulting in loss of image detail, tone conversion and reduced satisfaction, and the problem of not being able to cover the surface. This paper aims to study the image dehazing algorithm based on atmospheric scattering model. In this paper, an image dehazing algorithm based on atmospheric scattering model is studied in depth, and a material-robust and highly stable blur removal algorithm is proposed. In this case, the custom blur polarization algorithm treats the magnitude of the polarization as a general variable, resulting in a generally dull, low-level, low-toned image, with loss of image information. Filtering is recommended. Initially, two polarization maps were obtained under optimal and worst conditions using a polarization imaging system, and then the intensity of the surface light was calculated by division of the quadtree and proper optimization of the appropriate parameters as intensity. And using a general filter, the scattered light around the surface is calculated by the distorted path, then the image without blur is restored according to the deblurring pattern, the final image is destroyed. Experiments have shown that the algorithm in this paper is about 400 times faster than the DCP algorithm, and the user satisfaction is also above 70%.