AOSR-Net: All-in-One Sandstorm Removal Network
Yazhong Si Xulong Zhang Fan Yang Jianzong Wang Ning Cheng Jing Xiao
Most existing sandstorm image enhancement methods are based on traditional
theory and prior knowledge, which often restrict their applicability in
real-world scenarios. In addition, these approaches often adopt a strategy of
color correction followed by dust removal, which makes the algorithm structure
too complex. To solve the issue, we introduce a novel image restoration model,
named all-in-one sandstorm removal network (AOSR-Net). This model is developed
based on a re-formulated sandstorm scattering model, which directly establishes
the image mapping relationship by integrating intermediate parameters. Such
integration scheme effectively addresses the problems of over-enhancement and
weak generalization in the field of sand dust image enhancement. Experimental
results on synthetic and real-world sandstorm images demonstrate the
superiority of the proposed AOSR-Net over state-of-the-art (SOTA) algorithms.