SpinCam: High-Speed Imaging via a Rotating Point-Spread Function

被引:1
作者
Chan, Dorian [1 ]
Sheinin, Mark [1 ]
O'Toole, Matthew [1 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
来源
2023 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2023) | 2023年
基金
美国国家科学基金会;
关键词
PHOTOGRAPHY; ALGORITHM; VIDEO;
D O I
10.1109/ICCV51070.2023.00990
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
High-speed cameras are an indispensable tool used for the slow-motion analysis of scenes. However, the fixed bandwidth of any imaging system quickly becomes a bottleneck, resulting in a fundamental trade-off between the camera's spatial and temporal resolutions. In recent years, compressive high-speed imaging systems have been proposed to circumvent these issues by optically encoding the signal and using a reconstruction procedure to recover a video. Our work proposes a novel approach for compressive high-speed imaging based on temporally coding the camera's point-spread function (PSF). By mechanically spinning a diffraction grating in front of a camera, the sensor integrates an image blurred by a PSF that continuously rotates over time. We also propose a deconvolution-based reconstruction algorithm to reconstruct videos from these measurements. Our method achieves superior light efficiency and handles a wider scene class than prior methods. Also, our mechanical design yields flexible temporal resolution that can be easily increased, potentially allowing capture at 192 kHz-far higher than prior works. We demonstrate a prototype for various applications, including motion capture and particle image velocimetry (PIV).
引用
收藏
页码:10755 / 10765
页数:11
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