Infrared Image Super-Resolution: A Systematic Review and Future Trends

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Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu, Shinichiro Omachi

Published: 2025, Last Modified: 06 Nov 2025IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Image super-resolution (SR) is a fundamental task in computer vision and image processing. The challenge of super-resolving infrared (IR) or thermal images represents a key and persistent research frontier in the deep learning era. Different from visible-light SR, infrared image super-resolution (IRSR) is challenged by the distinct properties of thermal images, which typically exhibit low contrast, limited high-frequency details, and sensor-specific noise. This survey provides a comprehensive review of IRSR, covering its applications, the inherent limitations of IR imaging hardware, and a detailed taxonomy of processing methodologies. In addition, we discuss the critical roles of datasets and evaluation metrics in the field. Finally, we highlight current technological gaps and identify promising future directions for the community.