  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.
