基于光子有效遮挡的机会主动成像揭示隐藏场景
Revealing hidden scenes by photon-efficient occlusion-based opportunistic active imaging
摘要：
能够看到周围的角落，即，从隐藏场景在周围环境中的反射中恢复隐藏场景的细节在广泛的应用中具有相当大的意义。然而，从典型表面反射的光的漫射性质导致在所收集的光中的空间信息的混合，从而排除有用的场景重建。在这里，我们采用了一种计算成像技术，机会主义地利用存在的遮挡物体，阻碍探测光传播的隐藏场景，撤销混合，大大提高场景恢复。重要的是，我们的技术避免了需要超快的飞行时间测量所采用的大多数以前的方法来隐藏场景成像。此外，它以基于精确的前向模型和计算算法的光子有效方式这样做，这些算法共同尊重三次反弹光传播和单光子检测的物理学。使用我们的方法，我们展示了隐藏的表面反射率模式的重建在米级的环境中，从非时间分辨的测量。最终，我们的技术代表了一个实例，丰富和有前途的新的成像方式与成像科学的重要潜在影响。
英文摘要：
The ability to see around corners, i.e., recover details of a hidden scene from its reflections in the surrounding environment, is of considerable interest in a wide range of applications. However, the diffuse nature of light reflected from typical surfaces leads to mixing of spatial information in the collected light, precluding useful scene reconstruction. Here, we employ a computational imaging technique that opportunistically exploits the presence of occluding objects, which obstruct probe-light propagation in the hidden scene, to undo the mixing and greatly improve scene recovery. Importantly, our technique obviates the need for the ultrafast time-of-flight measurements employed by most previous approaches to hidden-scene imaging. Moreover, it does so in a photon-efficient manner based on an accurate forward model and a computational algorithm that, together, respect the physics of three-bounce light propagation and single-photon detection. Using our methodology, we demonstrate reconstruction of hidden-surface reflectivity patterns in a meter-scale environment from non-time-resolved measurements. Ultimately, our technique represents an instance of a rich and promising new imaging modality with important potential implications for imaging science.
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