Method of image enhancement in coal mine based on improved retex fusion algorithm in HSV space

Coal mine safety monitoring technology has always been an important part of the mining process. Underground video monitoring is an important means to ensure the safety of coal mine. However, the quality of monitoring image directly determines the effectiveness of monitoring. At present, due to the influence of coal mine dust and low illumination, the enhancement effect of coal mine video image needs to be improved. Aiming at this problem, this paper proposes a method to fuse the improved bilateral filtering algorithm and multi-scale Retinex algorithm under the condition of HSV spatial transformation. First of all, aiming at the problems that are prone to halos and edge blur in the multi-scale Retinex algorithm, it is enhanced by the improved method of bilateral filtering and the multi-scale Retinex algorithm.The bilateral filter with added correction function is used as the center surround function in the multi-scale Retinex algorithm.At the same time, the image is transformed from RGB space to HSV space, keeping the hue component unchanged, and the brightness component is enhanced by the fusion Retinex algorithm, and the saturation component is cor-rected.Finally, the image is converted from HSV space to RGB space to complete the image enhancement.The experimental results show that the improved fusion Retinex algorithm is better than theMulti-Scale Retinex (MSR) and Multi-Scale Retinex with Color Restoration (MSRCR) algorithm in color and edge blur processing. At the same time, compared with the MSR algorithm, the image mean value, standard deviation, peak signal-to-noise ratio and information entropy are improved by 15.24%, 16.54%, 42.77% and 2.82% respectively. Compared with the MSRCR algorithm, it has improved by 8.13%, 5.51%, 10.90%, and 0.59% respectively.Experiments show that the improved fusion Retinex algorithm enhances the image brightness and contrast, suppresses image halation and edge blurring, and provides a decision support for coal mine safe production and smart mine construction. © 2020, Editorial Office of Journal of China Coal Society. All right reserved.