Research on Image Enhancement Algorithm Base on Convolutional Neural Network in Scotopic Vision Environment

The limitation of human visual contrast resolution makes it impossible that people to clearly distinguish the image information obtained in the scotopic vision environment. In view of the low brightness, unclear content and low contrast of the image obtained in the scotopic vision environment, an image enhancement algorithm based on convolutional neural network is proposed. First, the image data sets required for experimental training are captured by image acquisition equipment. Secondly, using the algorithm principle of the GAN network, to construct a convolutional neural network model, and the obtained image is input into an image generation network can get an enhanced image, where the input image includes an image in a scotopic vision environment and its brightness channel image, the image generation network is structured by an autoencoder network, and then according to the characteristics of the image to constructed different loss functions. Theoretical analysis and experimental results show that the enhancement effect of traditional image enhancement algorithm on these images is very limited, while image enhancement using convolutional neural network can ensure the accuracy of the algorithm and achieve a good effect. The method in this paper obviously improves the scotopic vision environment image visual effect, make the image clearer, meets the requirements of people to the naked eye to watch.