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Keywords = xBn MWIR camera

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14 pages, 8597 KB  
Article
AI-Based Enhancing of xBn MWIR Thermal Camera Performance at 180 Kelvin
by Michael Zadok, Zeev Zalevsky and Benjamin Milgrom
Sensors 2025, 25(10), 3200; https://doi.org/10.3390/s25103200 - 19 May 2025
Cited by 2 | Viewed by 1561
Abstract
Thermal imaging technology has revolutionized various fields, but current high operating temperature (HOT) mid-wave infrared (MWIR) cameras, particularly those based on xBn detectors, face limitations in size and cost due to the need for cooling to 150 Kelvin. This study explores the potential [...] Read more.
Thermal imaging technology has revolutionized various fields, but current high operating temperature (HOT) mid-wave infrared (MWIR) cameras, particularly those based on xBn detectors, face limitations in size and cost due to the need for cooling to 150 Kelvin. This study explores the potential of extending the operating temperature of these cameras to 180 Kelvin, leveraging advanced AI algorithms to mitigate the increased thermal noise expected at higher temperatures. This research investigates the feasibility and effectiveness of this approach for remote sensing applications, combining experimental data with cutting-edge image enhancement techniques like Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN). The findings demonstrate the potential of 180 Kelvin operation for xBn MWIR cameras, particularly in daylight conditions, paving the way for a new generation of more affordable and compact thermal imaging systems. Full article
(This article belongs to the Section Sensing and Imaging)
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