Image Super-Resolution (SR) is essential for a wide range of computer vision and image processing tasks. Investigating infrared (IR) image (or thermal images) super-resolution is a continuing concern within the development of deep learning. This survey aims to provide a comprehensive perspective of IR image super-resolution, including its applications, hardware imaging system dilemmas, and taxonomy of image processing methodologies. In addition, the datasets and evaluation metrics in IR image super-resolution tasks are also discussed. Furthermore, the deficiencies in current technologies and possible promising directions for the community to explore are highlighted. To cope with the rapid development in this field, we intend to regularly update the relevant excellent work at \url{https://github.com/yongsongH/Infrared_Image_SR_Survey

翻译：图像超分辨率是计算机视觉和图像处理任务中至关重要的一环。在深度学习的发展过程中，红外图像（或热成像图像）的超分辨率研究持续受到关注。本综述旨在提供红外图像超分辨率的全面视角，涵盖其应用、硬件成像系统困境以及图像处理方法的分类体系。此外，还讨论了红外图像超分辨率任务中的数据集和评估指标。进一步地，本文指出了当前技术的不足之处以及社区值得探索的可能方向。为应对该领域的快速发展，我们计划定期更新相关优秀研究成果，链接为：\url{https://github.com/yongsongH/Infrared_Image_SR_Survey}。