论文标题
基于分散的多距离信号的时空断层扫描及其用于使用移动平台解决不断发展的云的应用
Spatiotemporal tomography based on scattered multiangular signals and its application for resolving evolving clouds using moving platforms
论文作者
论文摘要
我们使用少量的移动摄像机来得出一个随时间变化的半透明对象的计算机断层扫描（CT）。我们特别关注被动散射层析成像，这是一个非线性问题。我们证明了动态云的方法，因为云对地球的气候产生了重大影响。散射状态CT假定静态对象。现有的4D CT方法依赖于线性图像形成模型，并且通常取决于重要的先验。在本文中，讨论了适当恢复所需的角度和时间采样率。如果使用这些速率，则纸张会导致随时间变化的对象的表示，从而简化了4D CT断层扫描。该任务是使用基于梯度的优化来实现的。我们在基于物理学的模拟和产生现实数据的实验中证明了这一点。
We derive computed tomography (CT) of a time-varying volumetric translucent object, using a small number of moving cameras. We particularly focus on passive scattering tomography, which is a non-linear problem. We demonstrate the approach on dynamic clouds, as clouds have a major effect on Earth's climate. State of the art scattering CT assumes a static object. Existing 4D CT methods rely on a linear image formation model and often on significant priors. In this paper, the angular and temporal sampling rates needed for a proper recovery are discussed. If these rates are used, the paper leads to a representation of the time-varying object, which simplifies 4D CT tomography. The task is achieved using gradient-based optimization. We demonstrate this in physics-based simulations and in an experiment that had yielded real-world data.
