A comprehensive survey on image dehazing for different atmospheric scattering models

Image dehazing techniques are widely used in complex outdoor environments and are commonly categorized based on learning mechanisms. However, the imaging mechanism reveals the reasons for the degradation of hazy images, and the imaging physics process is essential for solving clean image reconstruction. Therefore, different from the previous categorization based solely on learning mechanisms, we propose a more fundamental approach that divides the techniques based on the imaging models used and analyze the advantages and disadvantages of various imaging models to find reasonable computational methods for image reconstruction. This paper focuses on analyzing the principles of different atmospheric imaging models and discusses the dehazing methods based on these models. In addition, we also discuss the development of atmospheric scattering models and the application of different atmospheric imaging models in image dehazing. Finally, this paper presents the application effects of different atmospheric scattering models on thin fog and dense fog datasets. Various issues and challenges faced by existing image dehazing techniques are described, and further research questions are proposed.