Dual-frequency angular-multiplexed fringe projection profilometry with deep learning: breaking hardware limits for ultra-high-speed 3D imaging
基于深度学习的双频角度复用条纹投影轮廓测量技术：突破硬件限制，实现超高速3D成像
デュアル周波数角度多重縞模造形計測と深層学習：超高速3Dイメージングのためのハードウェア限界の突破
딥러닝 기반 이중 주파수 각도 다중화 프린지 프로젝션 프로파일로미터: 초고속 3D 이미징을 위한 하드웨어 한계 극복
Profilometría de proyección de franjas angularmente multiplexadas de doble frecuencia con aprendizaje profundo: superando los límites del hardware para imágenes 3D ultra-rápidas
Profilométrie par projection de franges angulaire multiplexée à double fréquence avec apprentissage profond : dépasser les limites matérielles pour l'imagerie 3D ultra-rapide
Двухчастотная углово-мультиплексированная проекционная профилометрия с глубоким обучением: преодоление аппаратных ограничений для сверхвысокоскоростного 3D-визуализирования
¹ Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
中国 南京 南京理工大学电子工程与光电技术学院 智能计算成像实验室
² Key Laboratory of Shock Wave Physics and Detonation Physics, Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621900, China
中国 绵阳 中国工程物理研究院流体物理研究所 冲击波物理与爆轰物理全国重点实验室
³ Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing 210019, China
中国 南京 南京理工大学智能计算成像研究院
⁴ Jiangsu Key Laboratory of Visual Sensing & Intelligent Perception, Nanjing 210094, China
中国 南京 江苏省光谱成像与智能感知重点实验室
⁵ State key Laboratory of Extreme Environment Optoelectronic Dynamic Measurement Technology and Instrument, Taiyuan 030051, China
中国 太原 极限环境光电动态测试技术与仪器全国重点实验室
⁶ Institute of Micromechanics and Photonics, Warsaw University of Technology, 8 Sw. A. Boboli St., Warsaw 02-525, Poland
Recent advancements in artificial intelligence have transformed three-dimensional (3D) optical imaging and metrology, enabling high-resolution and high-precision 3D surface geometry measurements from one single fringe pattern projection. However, the imaging speed of conventional fringe projection profilometry (FPP) remains limited by the native sensor refresh rates due to the inherent "one-to-one" synchronization mechanism between pattern projection and image acquisition in standard structured light techniques.
Here, we present dual-frequency angular-multiplexed fringe projection profilometry (DFAMFPP), a deep learning-enabled 3D imaging technique that achieves high-speed, high-precision, and large-depth-range absolute 3D surface measurements at speeds 16 times faster than the sensor's native frame rate. By encoding multi-timeframe 3D information into a single multiplexed image using multiple pairs of dual-frequency fringes, high-accuracy absolute phase maps are reconstructed using specially trained two-stage number-theoretical-based deep neural networks.
We validate the effectiveness of DFAMFPP through dynamic scene measurements, achieving 10,000 Hz 3D imaging of a running turbofan engine prototype with only a 625 Hz camera. By overcoming the sensor hardware bottleneck, DFAMFPP significantly advances high-speed and ultra-high-speed 3D imaging, opening new avenues for exploring dynamic processes across diverse scientific disciplines.
