Research Article Vol. 11, No. 1 / January 2024 / Optica 73 Spinning metasurface stack for spectro-polarimetric thermal imaging Xueji Wang, Ziyi Yang, Fanglin Bao, Tyler Sentz, AND Zubin Jacob* Elmore Family School of Electrical and Computer Engineering, Birck Nanotechnology Center, Purdue University, West Lafayette, Indiana 47907, USA *zjacob@purdue.edu Received 25 September 2023; revised 13 November 2023; accepted 17 November 2023; published 11 January 2024 Spectro-polarimetric imaging in the long-wave infrared (LWIR) region plays a crucial role in applications from night vision and machine perception to trace gas sensing and thermography. However, the current generation of spectro- polarimetric LWIR imagers suffers from limitations in size, spectral resolution, and field of view (FOV). While meta-optics-based strategies for spectro-polarimetric imaging have been explored in the visible spectrum, their poten- tial for thermal imaging remains largely unexplored. In this work, we introduce an approach for spectro-polarimetric decomposition by combining large-area stacked meta-optical devices with advanced computational imaging algo- rithms. The co-design of a stack of spinning dispersive metasurfaces along with compressive sensing and dictionary learning algorithms allows simultaneous spectral and polarimetric resolution without the need for bulky filter wheels or interferometers. Our spinning-metasurface-based spectro-polarimetric stack is compact (< 10 × 10 × 10 cm) and robust, and it offers a wide field of view (20.5◦). We show that the spectra
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Spinning metasurface stack for spectro-polarimetric thermal imaging
Xueji Wang, Ziyi Yang, Fanglin Bao, Tyler Sentz, Zubin Jacob
Research context
Spectro-polarimetric imaging in the long-wave infrared (LWIR) region plays a crucial role in applications from night vision and machine perception to trace gas sensing and thermography. However, the current generation of spectro-polarimetric LWIR imagers suffers from limitations in size, spectral resolution, and field of view (FOV). While meta-optics-based strategies for spectro-polarimetric imaging have been explored in the visible spectrum, their potential for thermal imaging remains largely unexplored. In this work, we introduce an approach for spectro-polarimetric decomposition by combining large-area stacked meta-optical devices with advanced computational imaging algorithms. The co-design of a stack of spinning dispersive metasurfaces along with compressive sensing and dictionary learning algorithms allows simultaneous spectral and polarimetric resolution without the need for bulky filter wheels or interferometers. Our spinning-metasurface-based spectro-polarimetric stack is compact (<10×10×10cm) and robust, and it offers a wide field of view (20.5°). We show that the spectral resolving power of our system substantially enhances performance in machine learning tasks such as m
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Xueji Wang, Ziyi Yang, Fanglin Bao, Tyler Sentz, Zubin Jacob. Spinning metasurface stack for spectro-polarimetric thermal imaging. Optica (2024). https://doi.org/10.1364/optica.506813
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