Advances in deep learning for infrared image processing and exploitation

Erik Blasch; Zheng Liu; Yufeng Zheng

doi:10.1117/12.2619140

27 May 2022 Advances in deep learning for infrared image processing and exploitation

Erik Blasch, Zheng Liu, Yufeng Zheng

Proceedings Volume 12107, Infrared Technology and Applications XLVIII; 121071M (2022) https://doi.org/10.1117/12.2619140
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

Since the rise of deep learning (DL), methods are being proposed daily for all kinds of applications such as systems that include radar, infrared (IR), and electro-optical (EO) imagery. The most common DL application uses the convolutional neural network (CNN) for visual (VIS) imagery as data sets are available for training. This paper highlights recent advances of DL for Infrared (IR) applications by conducting a literature review for IR only and IR plus another modality (e.g., Visual+IR). For IR DL developments, the paper examines that of (1) applications (medical, non-destructive evaluation, target recognition), (2) sensing (space, air, ground), and (3) multi-modal (transfer learning, image enhancement, band selection); while determining aspects for improving the IR sensor design.

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Citation Download Citation

Erik Blasch, Zheng Liu, and Yufeng Zheng "Advances in deep learning for infrared image processing and exploitation", Proc. SPIE 12107, Infrared Technology and Applications XLVIII, 121071M (27 May 2022); https://doi.org/10.1117/12.2619140

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