Abstract: Due to the existing factors of dust and uneven illumination in mine,so,the images obtained by mine video monitoring system are usually containe a lot of noise and the brightness of the image is uneven,it affect the real-time effective monitoring of the main production status to some extent.In orde to process mine video monitoring images with high effects,an improved fuzzy median filtering algorithm is proposed.Firstly,an adaptive calculation method of improved fuzzy membership degree coefficient is put forward,the minimum,maximum and average grey values of the pixels of each filtering window of mine video monitoring image are taken as the thresholds to calculate the fuzzy membership degree coefficients of the grey values of different pixels,so the deficiencies of setting many thresholds of the classical calculation method of fuzzy membership degree coefficient is overcame;then,the fuzzy weighted median filtering is conducted based on the fuzzy membership degree coefficients;finally,in view of the different fuzzy degree of the filtered image,the gray histogram of fitered image is conducted equalization processing to enhance the overall visual effects of the image.The program of the algorithm proposed in this paper is written by C# language,the experimental data are the two mine video monitoring images acquired from a mine.The fuzzy median filtering algorithm,weighted median filtering algorithm and switch median filtering algorithm are used to conduct contrast analysis of the filtering effects,the above experimental results of the algorithms are evaluated by peak signal to noise ratio (PSNR) and time-consuming,the experimental results show that the performance of the improved fuzzy median filtering algorithm is superior to the fuzzy median filtering algorithm,weighted median filtering algorithm and switch median filtering algorithm,besides that,the time-consuming of the improved fuzzy median filtering algorithm is less than the orther three algorithms,it can provide the reference for processing a large number of mine video monitoring images effectively.

Key words: Mine video monitoring system, Fuzzy membership degree coefficient, Fuzzy median filtering, Histogram equalization, Peak signal to noise ratio