关键词: 矿井视频监控系统, 小波阈值去噪, 非局部均值滤波, 峰值信噪比, 均方根误差

Abstract: A large number of the image information acquistition sensors of the mine video monitoring system are placed in the environment with the characteristics of low light,high density of dust,which is resulted in the images obtained by the image information acquistitions with the characteristics of low contrast and high density of noise,so,the effective monitoring of mine production is influenced to some extent.Combing with the wavelet thresholding algorithm and non-local means filtering algorithm (NLM),the filtering algorithm of mine monitoring video image is proposed.The obatined original mine monitoring video image is conducted single-layer wavelet transform,the obatined low-frequency and high-frequency coefficients are processed as following:①the low-frequency coefficient is conducted single-layer wavelet transform,the secondly low-freqency coefficient 1 and secondly high-frequency coefficients 1 are obtained,the secondly high-frequency coefficients 1 area filtered by the improved wavelet thresholding denoising model proposed in this papaer,the filtered secondly high-frequency coefficients 1 are reconstructed,the low-frequency image is acquired;②the high-coefficients are conducted single-layer wavelet transform,the secondly low-frequency coefficient 2 and secondly high-frequency coefficents 2 are obtained,the secondly high-frequency coefficients 2 are set to zero,the secondly low-frequency coefficients 2 are processed by the soft wavelet thresholding denoising model,the filtered secondly low-frequency coefficients are reconstructed to obtain the high-frequency image.The above low-frequency and high-frequency image are intergrated,the processed mine monitoring video image wih high resolution.The programme of the algorithm proposed in the papaer is writed by VB language,the experimental results show that the resolution of the image processed by the algorithm proposed in this paper is higher to the ones of the hard wavelet thresholding denoising model,soft wavelet thresholding denoising model and non-local means filtering algorithm,besides that,the PSNR and RMSE of the algorithm proposed in this papaer are also superior to the others.

Key words: Mine video monitoring system, Wavelet thresholding denoising, Non-local means filtering, PSNR, RMSE