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.

基于一个重新构建的沙尘风暴散射模型，我们提出了一种名为AOSR-Net的全能沙尘风暴去除网络模型，该模型通过整合中间参数直接建立图像映射关系，从而解决了沙尘图像增强领域中过度增强和弱泛化的问题。实验结果表明，该AOSR-Net模型在合成和真实沙尘风暴图像上显示出优于最先进算法的优越性。

AOSR-Net: 全方位沙尘暴去除网络