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:调查红外(IR)图像(或热成像)超级分辨率是深层学习过程中持续关注的一个问题。这项调查旨在提供IR图像超分辨率的全面观点,包括其应用、硬件成像系统难题和图像处理方法分类。此外,还讨论了IR图像超分辨率任务中的数据集和评价指标。此外,还着重指出了当前技术的缺陷和可供社区探索的可能前景方向。为了应对该领域的快速发展,我们打算定期更新以下网站的相关出色工作:https://github.com/yongsongH/Infrared_Image_SR_Suvey。