Fast Non-Line-Of-Sight Imaging with Two-Step Deep Remapping,ACS Photonics

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Fast Non-Line-Of-Sight Imaging with Two-Step Deep Remapping
ACS Photonics ( IF 6.5 ) Pub Date : 2022-06-03 , DOI: 10.1021/acsphotonics.2c00186
Dayu Zhu ₁ , Wenshan Cai _{1,

2}

Affiliation

Conventional imaging only records the photons directly sent from the object to the detector, whereas non-line-of-sight (NLOS) imaging takes the indirect light into account. Most NLOS solutions employ a transient scanning process, followed by a physical-based algorithm to reconstruct the NLOS scenes. However, transient detection requires sophisticated apparatus, long scanning time, and low robustness to the ambient environment, and the reconstruction algorithms are typically time consuming and computationally expensive. Here, we propose a new NLOS solution with innovations on both equipment and algorithm. We apply inexpensive Lidar for detection, with much higher scanning speed and better compatibility to real-world imaging. Our reconstruction framework is deep learning based, with generative two-step remapping strategy to guarantee high reconstruction fidelity. The overall detection and reconstruction process allows for millisecond responses, with state-of-the-art reconstruction performance. We have experimentally tested the proposed solution on both synthetic and real objects and further demonstrated our method to be applicable for full-color NLOS imaging.

中文翻译：

具有两步深度重映射的快速非视距成像

传统成像仅记录从物体直接发送到探测器的光子，而非视距 (NLOS) 成像则考虑了间接光。大多数 NLOS 解决方案采用瞬态扫描过程，然后使用基于物理的算法来重建 NLOS 场景。然而，瞬态检测需要复杂的设备、较长的扫描时间和对周围环境的低鲁棒性，并且重建算法通常耗时且计算量大。在这里，我们提出了一种新的 NLOS 解决方案，在设备和算法上都有创新。我们使用廉价的激光雷达进行检测，具有更高的扫描速度和更好的与现实世界成像的兼容性。我们的重建框架是基于深度学习的，使用生成式两步重映射策略来保证高重建保真度。整个检测和重建过程允许毫秒级的响应，具有最先进的重建性能。我们已经在合成和真实物体上对所提出的解决方案进行了实验测试，并进一步证明了我们的方法适用于全彩色 NLOS 成像。

更新日期：2022-06-03

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