Based on Gamma RNet of low illumination image enhancement algorithm

When taking pictures in low light, affected by the limited and low light of the shooting equipment, the pictures taken usually have color distortion, low brightness, low contrast, large noise and other problems that will affect the visual effect. In order to solve the problem of images in low light environment, an adaptive Gamma-RNet algorithm is proposed by combining adaptive Gamma transform[1] with improved Retinex-Net algorithm, which can effectively improve the effect of images in low light environment. In this paper, the RedGreenBlue color modeRGB image under low light is converted into Hue, Saturation, Value HSV image color space conversion, and then the adaptive Gamma transform is used to improve the brightness of the image[2]. Then, to solve the problem of low brightness of the image after adaptive Gamma transform, the improved Retinex-Net algorithm is used to improve the image brightness. The experimental results show that the combination of adaptive Gamma transform and Retinex-Net algorithm can better enhance the image quality under low illumination.