Real-time non-line-of-sight computational imaging using spectrum filtering and motion compensation.

IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Jun-Tian Ye, Yi Sun, Wenwen Li, Jian-Wei Zeng, Yu Hong, Zheng-Ping Li, Xin Huang, Xianghui Xue, Xin Yuan, Feihu Xu, Xiankang Dou, Jian-Wei Pan
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引用次数: 0

Abstract

Non-line-of-sight (NLOS) imaging aims at recovering the shape and albedo of hidden objects. Despite recent advances, real-time video of complex and dynamic scenes remains a major challenge owing to the weak signal of multiply scattered light. Here we propose and demonstrate a framework of spectrum filtering and motion compensation to realize high-quality NLOS video for room-sized scenes. Spectrum filtering leverages a wave-based model for denoising and deblurring in the frequency domain, enabling computational image reconstruction with a small number of sampling points. Motion compensation tailored with an interleaved scanning scheme can compute high-resolution live video during the acquisition of low-quality image sequences. Together, we demonstrate live NLOS videos at 4 fps for a variety of dynamic real-life scenes. The results mark a substantial stride toward real-time, large-scale and low-power NLOS imaging and sensing applications.

利用频谱滤波和运动补偿进行实时非视距计算成像。
非视线(NLOS)成像旨在恢复隐藏物体的形状和反照率。尽管最近取得了一些进展,但由于多重散射光信号微弱,复杂动态场景的实时视频仍然是一个重大挑战。在此,我们提出并演示了一个频谱滤波和运动补偿框架,以实现房间大小场景的高质量 NLOS 视频。频谱滤波利用基于波的模型在频域中进行去噪和去毛刺处理,只需少量采样点即可实现计算图像重建。采用交错扫描方案的运动补偿可在采集低质量图像序列时计算出高分辨率的实时视频。我们共同演示了各种动态现实场景下每秒 4 帧的实时 NLOS 视频。这些成果标志着我们向实时、大规模、低功耗 NLOS 成像和传感应用迈出了实质性的一步。
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CiteScore
11.70
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