Abstract

An event camera is a neuromorphic vision sensor with a high dynamic range (HDR), high temporal resolution (HTR), low latency, and low power consumption. A polarimeter is an instrument for measuring the state of polarization of light. Currently, most imaging polarimeters are limited in dynamic range and frame rate when used with frame-based cameras. We can establish an event-based imaging polarimeter using the principle of the event camera to obtain HDR and HTR polarized event streams for processing polarization information. However, because of the short history and high cost of event cameras, developing an event-based imaging polarimeter requires substantial resources. We propose an event-based imaging polarimeter simulation method with a single division of focal plane image based on the existing research on event simulation. This method can easily convert existing data into a polarized event stream. It is beneficial to lower the requirement of processing polarized event streams and to create large datasets for deep learning.

© 2023 Optica Publishing Group

Self-calibration for Mueller polarimeters based on DoFP polarization imagers

Xiaobo Li, François Goudail, and Shih-Chi Chen
Opt. Lett. 47(6) 1415-1418 (2022)

Fast Mueller matrix microscope based on dual DoFP polarimeters

Tongyu Huang, Ruoyu Meng, Ji Qi, Yudi Liu, Xingjian Wang, Yan Chen, Ran Liao, and Hui Ma
Opt. Lett. 46(7) 1676-1679 (2021)

Optimal tradeoff between precision and sampling rate in DoFP imaging polarimeters

Xiaobo Li, Haofeng Hu, Matthieu Boffety, Stéphane Roussel, Tiegen Liu, and François Goudail
Opt. Lett. 44(24) 5900-5903 (2019)

Demosaicking DoFP images using edge compensation method based on correlation

Jianqiao Xin, Zheng Li, Shiguang Wu, and Shiyong Wang
Opt. Express 31(9) 13536-13551 (2023)

Event-based dual photography for transparent scene reconstruction

Xiaomeng Liu, Joshua D. Rego, Suren Jayasuriya, and Sanjeev J. Koppal
Opt. Lett. 48(5) 1304-1307 (2023)