论文标题
在星空下跳舞：在星光下录像
Dancing under the stars: video denoising in starlight
论文作者
论文摘要
由于低光子计数，弱光成像极具挑战性。使用敏感的CMOS摄像机，目前有可能在月光下在夜间拍摄视频（0.05-0.3 Lux Illumination）。在本文中，我们首次在星光下展示了星光下的影片视频（不存在月亮，$ <$ 0.001勒克斯）。为了实现这一目标，我们开发了一个基于GAN的物理噪声模型，以更准确地代表最低光级别的相机噪声。使用此噪声模型，我们使用模拟嘈杂的视频剪辑和真实的嘈杂静止图像来训练视频Denoiser。我们捕获了一个5-10 fps视频数据集，其显着运动约为0.6-0.7 millilux，没有主动照明。与替代方法相比，我们在最低的光级别上实现了改进的视频质量，这是第一次在星光下进行的逼真的视频。
Imaging in low light is extremely challenging due to low photon counts. Using sensitive CMOS cameras, it is currently possible to take videos at night under moonlight (0.05-0.3 lux illumination). In this paper, we demonstrate photorealistic video under starlight (no moon present, $<$0.001 lux) for the first time. To enable this, we develop a GAN-tuned physics-based noise model to more accurately represent camera noise at the lowest light levels. Using this noise model, we train a video denoiser using a combination of simulated noisy video clips and real noisy still images. We capture a 5-10 fps video dataset with significant motion at approximately 0.6-0.7 millilux with no active illumination. Comparing against alternative methods, we achieve improved video quality at the lowest light levels, demonstrating photorealistic video denoising in starlight for the first time.
