Low-light image enhancement based on deep learning: a survey

Abstract

Images taken under low light or dim backlight conditions usually have insufficient brightness, low contrast, and poor visual quality of the image, which leads to increased difficulty in computer vision and human recognition of images. Therefore, low illumination enhancement is very important in computer vision applications. We mainly provide an overview of existing deep learning enhancement algorithms in the low-light field. First, a brief overview of the traditional enhancement algorithms used in early low-light images is given. Then, according to the neural network structure used in deep learning and its learning algorithm, the enhancement methods are introduced. In addition, the datasets and common performance indicators used in the deep learning enhancement technology are introduced. Finally, the problems and future development of the deep learning enhancement method for low-light images are described.