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Single-shot compressed ultrafast photography at one hundred …
- https://www.nature.com/articles/nature14005/
- Here we demonstrate a two-dimensional dynamic imaging technique, compressed ultrafast photography (CUP), which can capture non-repetitive time-evolving events at up to 10 11 frames per second ...
Compressed Ultrafast Photography - 100 Billion Frames Per Second
- https://unfoldanswers.com/compressed-ultrafast-photography/
- The Compressed Ultrafast Photography (CUP) technique is stupendously fast. It was experimented in media laboratory of MIT in 2011 and had a speed of 1 trillion fps but this approach could only work for scenes that can be replayed at will with nearly perfect reproducible nature. It took them an hour to have enough shots to make real-time video ...
Compressed Ultrafast Photography
- http://coilab.caltech.edu/research_6.html
- Compressed ultrafast photography (CUP), as a single-shot ultrafast computational imaging modality, overcomes this limitation. Synergistically combining compressed sensing and streak imaging, CUP can image non-repetitive transient events at 100 billion frames per second. In addition, akin to conventional photography, CUP is receive-only.
Single-shot compressed ultrafast photography at one hundred …
- https://pubmed.ncbi.nlm.nih.gov/25471883/
- Here we demonstrate a two-dimensional dynamic imaging technique, compressed ultrafast photography (CUP), which can capture non-repetitive time-evolving events at up to 10(11) frames per second. Compared with existing ultrafast imaging techniques, CUP has the prominent advantage of measuring an x-y-t (x, y, spatial coordinates; t, time) scene ...
Ultrafast Camera Takes Trillions of Images per Second …
- https://www.photonics.com/Articles/Ultrafast_Camera_Takes_Trillions_of_Images_per/a64007
- MONTREAL, Canada, and PASADENA, Calif., Oct. 15, 2018 — Single-shot 10-trillion-frame-per-second compressed ultrafast photography (CUP) is now …
Lensless ultrafast optical imaging - PMC
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9016062/
- Similar to the pioneer high-speed photography experiments in the 1900s, these single-shot ultrafast optical imaging methods can be generally categorized as active detection methods and passive detection methods 4. Active-detection methods probe the ultrafast dynamics through modulation of the ultrafast optical pulses, while passive-detection ...
Single-shot compressed ultrafast photography: a review
- https://www.researchgate.net/publication/339577611_Single-shot_compressed_ultrafast_photography_a_review
- Compressed ultrafast photography (CUP) is a burgeoning single-shot computational imaging technique that provides an imaging speed as high as 10 trillion frames per second and a sequence depth of ...
Hyperspectrally Compressed Ultrafast Photography
- https://link.aps.org/doi/10.1103/PhysRevLett.124.023902
- The spatial, temporal, and spectral information in optical imaging play a crucial role in exploring the unknown world and unencrypting natural mysteries. However, the existing optical imaging techniques can only acquire the spatiotemporal or spatiospectral information of the object with the single-shot method. Here, we develop a hyperspectrally compressed ultrafast …
Single-Shot Ultraviolet Compressed Ultrafast Photography
- https://onlinelibrary.wiley.com/doi/10.1002/lpor.202000122
- Compressed ultrafast photography (CUP) is an emerging potent technique that allows imaging a nonrepeatable or difficult-to-produce transient event in a single shot. Despite many recent advances, existing CUP techniques operate only at visible and near-infrared wavelengths. In addition, spatial encoding via a digital micromirror device (DMD) in ...
Deep-learning-based image reconstruction for compressed …
- https://pubmed.ncbi.nlm.nih.gov/32796968/
- Compressed ultrafast photography (CUP) is a computational optical imaging technique that can capture transient dynamics at an unprecedented speed. Currently, the image reconstruction of CUP relies on iterative algorithms, which are time-consuming and often yield nonoptimal image quality. To solve this problem, we develop a deep-learning-based ...
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