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AOSR-Net: All-in-One Sandstorm Removal Network

arXiv 2309.08838 ↗First posted 16 Sep 2023cs.CV eess.IVcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 44 references that are in the map. First posted on arXiv 16 Sep 2023.

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References · 13

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  12. 2023PMVC: Data Augmentation-Based Prosody Modeling for Expressive Voice Conversioncited by 3
1 more
  1. 2023Dynamic Alignment Mask CTC: Improved Mask-CTC with Aligned Cross Entropycited by 2

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