A protector is placed in front of the camera lens for mobile devices to avoid damage, while the protector itself can be easily scratched accidentally, especially for plastic ones. The artifacts appear in a wide variety of patterns, making it difficult to see through them clearly. Removing image artifacts from the scratched lens protector is inherently challenging due to the occasional flare artifacts and the co-occurring interference within mixed artifacts. Though different methods have been proposed for some specific distortions, they seldom consider such inherent challenges. In our work, we consider the inherent challenges in a unified framework with two cooperative modules, which facilitate the performance boost of each other. We also collect a new dataset from the real world to facilitate training and evaluation purposes. The experimental results demonstrate that our method outperforms the baselines qualitatively and quantitatively. The code and datasets will be released after acceptance.

翻译：在移动设备的相机镜头前通常放置保护膜以防止损坏，但保护膜本身（尤其是塑料材质的）容易被意外划伤。这些伪影呈现出多种多样的图案，使得难以透过它们清晰地观察。由于偶尔出现的耀斑伪影以及混合伪影中的共存干扰，从划伤的镜片保护膜中去除图像伪影本身极具挑战性。尽管已有针对某些特定失真的不同方法被提出，但它们很少考虑此类固有的挑战。在本工作中，我们将这些固有挑战纳入一个统一框架，通过两个协作模块相互促进性能提升。我们还收集了一个来自真实世界的新数据集，以促进训练和评估。实验结果表明，我们的方法在定性和定量上均优于基线方法。相关代码和数据集将在论文接收后发布。