论文标题
decay2distill：利用空间扰动和正规化自我监督图像
Decay2Distill: Leveraging spatial perturbation and regularization for self-supervised image denoising
论文作者
论文摘要
在过去的几年中，未配对的图像DeNoising取得了有希望的发展。无论表现如何，方法都倾向于在很大程度上依赖潜在的噪声属性或任何并不总是实用的假设。另外，如果我们可以从结构的角度而不是噪声统计数据解决问题，那么我们可以实现更强大的解决方案。通过这种动机，我们提出了一个自制的剥皮计划，该计划是不成功的，依赖于空间降解，然后进行正规化的改进。我们的方法比以前的方法显示出可观的改进，并且在不同数据域上表现出一致的性能。
Unpaired image denoising has achieved promising development over the last few years. Regardless of the performance, methods tend to heavily rely on underlying noise properties or any assumption which is not always practical. Alternatively, if we can ground the problem from a structural perspective rather than noise statistics, we can achieve a more robust solution. with such motivation, we propose a self-supervised denoising scheme that is unpaired and relies on spatial degradation followed by a regularized refinement. Our method shows considerable improvement over previous methods and exhibited consistent performance over different data domains.
