Dust and fog image-sharpening algorithm based on atmospheric scattering model in coal face

Abstract

A large number of suspended particles such as dust and water fog is produced in the process of coal mining, which leads to the degradation of images such as low illumination, high dust concentration, and uneven fog distribution. The existing image-sharpening methods are not ideal. An algorithm based on atmospheric scattering model is proposed to restore the dust and fog image in coal face, which solves the problem of inaccurate estimation of atmospheric scattering model parameters in a complex coal mining environment. It mainly includes three parts: Segmenting the image according to the dust and fog concentration of the coal mining image; Estimating the ambient light value and transmittance of each region; After fusing the regional parameters, the clear image is restored based on atmospheric scattering model. Firstly, by analyzing the dust and fog distribution characteristics in coal face, according to the information of image channel difference and brightness, the dust and fog image of coal face is divided into dense fog region and non-dense fog region. Then, the Max-RGB method is used to estimate the initial illumination map of the dust and fog image. To better retain the structure information and edge information of the dust and fog image, the initial illumination map is refined, and the ambient light values of the two regions are calculated by using the refined illumination map; In the dense fog region, according to the dust and fog concentration and distribution characteristics, the transmittance is estimated by using the optimized color attenuation model; In the non-dense fog region, the transmittance is calculated by using the dark channel prior and the ambient light matrix of the region. Finally, the ambient light matrix and transmittance matrix in different regions are alpha fused, and the guidance filter is used to suppress the noise generated in the fusion process while retaining the image edge information, to obtain the global ambient light and transmittance values, which are substituted into the atmospheric scattering model to restore the low illumination of dust and fog image. In order to verify the effectiveness of the proposed algorithm, two representative algorithms are selected for comparison. Experiments show that the proposed algorithm can effectively reduce the dust and fog concentration in the image, improve the image illumination, retain the image edge information, and the overall performance is better.

Keywords

• dust and fog image in coal face
• atmospheric scattering model
• region segmentation
• alpha fusion
• image-sharpening