Image Enhancement Based on Generative Adversarial Neural Network

Abstract

In this paper, we present an image enhancement scheme based on generative adversarial neural network. We use deep learning to decompose the image to obtain the shadow layer and the reflection layer image, and then perform image enhancement for the shadow layer image. In addition to being faster than the traditional method, the method we proposed also achieves better results. In this way, the overexposed or dark parts of the picture can be repaired, and more complete picture information can be obtained. For the repair of the shadow layer, we use a neural network for algorithm simulation. The Generative Adversarial Neural Network makes the training and testing speed more accurate and faster by giving conditional restrictions.