Single Image Dehazing with a Generic Model-Agnostic Convolutional Neural Network

Abstract

A simple convolutional neural network is proposed in this letter and is trained end-to-end to restore clear images from hazy inputs. The proposed network is generic and agnostic in the sense that it is not designed specifically for image dehazing and, in particular, it has no knowledge of the atmosphere scattering model. Remarkably, this network achieves record-breaking dehazing performance on several standard data sets that are synthesized using the atmosphere scattering model. This surprising finding suggests that there might be a need to rethink the predominant plug-in approach to image dehazing.