Affiliation:
1. State Key Laboratory of Precision Spectroscopy School of Physics and Electronic Science East China Normal University Shanghai 200241 China
2. North Night Vision Technology Co. Ltd Kunming 650217 China
3. Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan 030006 China
4. Joint Research Center of Light Manipulation Science and Photonic Integrated Chip of East China Normal University and Shandong Normal University East China Normal University Shanghai 200241 China
Abstract
AbstractCompressed ultrafast photography (CUP) can capture irreversible or difficult‐to‐repeat dynamic scenes at the imaging speed of more than one billion frames per second, which is obtained by compressive sensing‐based image reconstruction from a compressed 2D image through the discretization of detector pixels. However, an excessively high data compression ratio in CUP severely degrades the image reconstruction quality, thereby restricting its ability to observe ultrafast dynamic scenes with complex spatial structures. To address this issue, a discrete illumination‐based CUP (DI‐CUP) with high fidelity is reported. In DI‐CUP, the dynamic scenes are loaded into an ultrashort laser pulse train with controllable sub‐pulse number and time interval, thus the data compression ratio, as well as the overlap between adjacent frames, is greatly decreased and flexibly controlled through the discretization of dynamic scenes based on laser pulse train illumination, and high‐fidelity image reconstruction can be realized within the same observation time window. Furthermore, the superior performance of DI‐CUP is verified by observing femtosecond laser‐induced ablation dynamics and plasma channel evolution, which are hardly resolved in the spatial structures using conventional CUP. It is anticipated that DI‐CUP will be widely and dependably used in the real‐time observations of various ultrafast dynamics.
Funder
National Natural Science Foundation of China
Science and Technology Commission of Shanghai Municipality
Fundamental Research Funds for the Central Universities