Research on Improved Retinex-Based Image Enhancement Method for Mine Monitoring

An improved Retinex fusion image enhancement algorithm is proposed for the traditional denoising methods and problems of halo enlargement overexposure after caused by existing algorithm. First, a homomorphic filtering used to enhance each RGB component underground coal mine surveillance convert from space HSV space. Second, bilateral multi-scale retinex with color restoration (MSRCR) algorithms are luminance V while keeping hue H unchanged. Third, adaptive nonlinear stretching transform saturation S-component. Last, three elements combined converted back MATLAB simulation experiments verify superiority Based on same dataset experimental environment, has more uniform histogram distribution than (msr) MSRCR through comparative experiments. At time, peak signal-to-noise ratio (PSNR), structural similarity (SSIM), standard deviation, average gradient, mean value, colour picture information entropy images were 8.28, 0.15, 4.39, 7.38, 52.92 2.04, respectively, compared MSR algorithm, 3.97, 0.02, 34.33, 60.46, 26.21, 1.33, The results show that quality, brightness contrast enhanced significantly enhanced, amount in photos increases, considerably reduced, anti-distortion performance also improved.