论文标题
24小时彩色成像的集成增强解决方案
An Integrated Enhancement Solution for 24-hour Colorful Imaging
论文作者
论文摘要
当前的24小时户外成像的行业实践是使用辅助辅助（NIR）照明的硅相机。这将导致彩色图像在白天对比度较差，并且在夜间没有色彩。对于这种困境，所有现有的解决方案都试图分别捕获RGB和NIR图像。但是，他们需要额外的硬件支持，并遭受各种缺点，包括短寿命，高价，特定的用法场景等。在本文中，我们提出了一种新颖而集成的增强解决方案，无论是在阳光白天还是极低的夜晚，都会产生透明的色彩图像。我们的关键想法是将VIS和NIR信息与混合信号分开，并用NIR信号自适应地增强VIS信号作为帮助。为此，我们构建了一个光学系统来收集新的Vis-Nir-Mix数据集，并基于CNN提供了具有物理意义的图像处理算法。广泛的实验显示出了出色的结果，这证明了我们解决方案的有效性。
The current industry practice for 24-hour outdoor imaging is to use a silicon camera supplemented with near-infrared (NIR) illumination. This will result in color images with poor contrast at daytime and absence of chrominance at nighttime. For this dilemma, all existing solutions try to capture RGB and NIR images separately. However, they need additional hardware support and suffer from various drawbacks, including short service life, high price, specific usage scenario, etc. In this paper, we propose a novel and integrated enhancement solution that produces clear color images, whether at abundant sunlight daytime or extremely low-light nighttime. Our key idea is to separate the VIS and NIR information from mixed signals, and enhance the VIS signal adaptively with the NIR signal as assistance. To this end, we build an optical system to collect a new VIS-NIR-MIX dataset and present a physically meaningful image processing algorithm based on CNN. Extensive experiments show outstanding results, which demonstrate the effectiveness of our solution.
