Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)

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Analysis, Comparison and Application Scenarios of Nighttime Infrared Image Technology

Authors
Zijun Jin1, *
1International College, Chongqing University of Posts and Telecommunications, Chongqing, China
*Corresponding author. Email: 2024215667@stu.cqupt.edu.cn
Corresponding Author
Zijun Jin
Available Online 24 April 2026.
DOI
10.2991/978-94-6239-648-7_40How to use a DOI?
Keywords
Infrared imaging; Night vision; Technical Challenges
Abstract

As a breakthrough technology that transcends human visual limitations, nighttime infrared imaging demonstrates immense potential and application value across military, civilian, and industrial sectors. This paper systematically reviews the research progress of nighttime infrared imaging technology, focusing on its current applications, core challenges, and future development trends in various fields. The article first analyzes the technical principles and characteristics of active and passive infrared imaging, comparing performance differences and application scenarios between refrigerated and non-refrigerated infrared detectors. Building on this foundation, it elaborates on innovative applications and implementation effects of infrared technology in nighttime security monitoring, autonomous driving perception, industrial inspection, and medical diagnosis. Simultaneously, the paper thoroughly examines prominent issues in current infrared imaging technology, including insufficient image resolution/contrast, sensitivity to environmental interference, high cost constraints on widespread adoption, and limitations in intelligent processing algorithms. Finally, the article outlines emerging trends in cutting-edge directions such as multispectral fusion imaging, novel low-dimensional material detectors, and deep learning-enhanced processing, providing reference for further research and application of nighttime infrared imaging technology.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)
Series
Advances in Computer Science Research
Publication Date
24 April 2026
ISBN
978-94-6239-648-7
ISSN
2352-538X
DOI
10.2991/978-94-6239-648-7_40How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zijun Jin
PY  - 2026
DA  - 2026/04/24
TI  - Analysis, Comparison and Application Scenarios of Nighttime Infrared Image Technology
BT  - Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)
PB  - Atlantis Press
SP  - 362
EP  - 369
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-648-7_40
DO  - 10.2991/978-94-6239-648-7_40
ID  - Jin2026
ER  -