Low illumination Image Enhancement based on Improved Retinex Algorithm

Low illumination Image Enhancement based on Improved Retinex Algorithm

Aiming at the problems of insufficient illumination and low contrast of low illumination image, an improved Retinex low illumination image enhancement algorithm is proposed. Firstly, the brightness component V of the original image is extracted in HSV color space, and its enhancement by Single-Scale Retinex (SSR) is used to obtain the reflection component. For the edge problem caused by the estimation of illumination component, the Gaussian weighted bilateral filter is used as the filter function to maintain the edge information. Then, the saturation component S is adaptively stretched to improve the color saturation. However, different low illumination images have different contrast, and some images have insufficient contrast enhancement, so a global adaptive algorithm is introduced to modify the contrast and obtain the final image. According to the logarithmic characteristics of human vision, it can adaptively enhance the contrast of different images without over enhancement. Experimental results show that the proposed algorithm can effectively improve the visual quality of the image, the contrast is improved significantly and image edge details are protected, and objective evaluations such as average gradient, information entropy and peak signal-to-noise ratio have been improved.