A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learning

With the development of convolutional neural networks, hundreds deep learning based dehazing methods have been proposed. In this paper, we provide a comprehensive survey on supervised, semi-supervised, and unsupervised single image dehazing. We first discuss physical model, datasets, network modules, loss functions, evaluation metrics that are commonly used. Then, main contributions various algorithms categorized summarized. Further, quantitative qualitative experiments baseline carried out. Finally, unsolved issues challenges can inspire future research pointed A collection useful materials is available at https://github.com/Xiaofeng-life/AwesomeDehazing.