Quantifying effluent flow with event-based sensors

C. Bjorn Kjellstrand; Lilian K. Casias; Kaylin Hagopian; Christian A. Pattyn; Christopher Saltonstall; Joshua Shank

doi:10.1117/12.3029595

4 October 2024 Quantifying effluent flow with event-based sensors

C. Bjorn Kjellstrand, Lilian K. Casias, Kaylin Hagopian, Christian A. Pattyn, Christopher Saltonstall, Joshua Shank

Proceedings Volume 13149, Unconventional Imaging, Sensing, and Adaptive Optics 2024; 1314912 (2024) https://doi.org/10.1117/12.3029595
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Abstract

Event-based sensors (EBSs) consist of a pixelated focal plane array in which each pixel is an independent asynchronous change detector. The analog asynchronous array is read by a synchronous digital readout and written to disk. As a result, EBS pixels consume minimal power and bandwidth unless the scene changes. Furthermore, the change detectors have a very large dynamic range (~120 dB) and rapid response time (~20 us). A framing camera with comparable speed requires ~3 orders of magnitude more power and ~2 orders of magnitude higher bandwidth. Remote sensing deployed in the field requires low power, low bandwidth, and low complexity algorithms. An EBS inherently allows for low power and low bandwidth, but there is a lack of mature image analysis algorithms. While analysis of conventional imagers draws from decades of image processing algorithms, EBS data is a fundamentally different format; a series of x, y, asynchronous time, and polarization change (increase/decrease) as opposed to x, y, and intensity at a regularly sampled framerate. Our team has worked to develop and refine image processing algorithms that use EBS data directly.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

C. Bjorn Kjellstrand, Lilian K. Casias, Kaylin Hagopian, Christian A. Pattyn, Christopher Saltonstall, and Joshua Shank "Quantifying effluent flow with event-based sensors", Proc. SPIE 13149, Unconventional Imaging, Sensing, and Adaptive Optics 2024, 1314912 (4 October 2024); https://doi.org/10.1117/12.3029595

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