Tanaorn Bamroongshawgasame, Xi Zhang, Qiliang Li
Thermal infrared imaging has emerged as a transformative sensing technology, enabling non-contact, real-time visualization of temperature variations across a wide range of applications, including aerospace and defense, autonomous navigation, medical diagnostics, and industrial monitoring. Driven by advances in infrared detector materials, sensor architectures, and signal processing algorithms, thermal imaging systems have significantly improved in sensitivity, spatial and thermal resolution, and operational versatility. This review provides an in-depth examination of the fundamental principles of infrared detection, detailing the operating mechanisms and performance characteristics of thermal, conventional photon, and quantum engineered photon detectors. Advanced developments such as uncooled microbolometers, quantum well and superlattice photodetectors, and high-operating-temperature sensors are discussed in the context of enhancing performance while reducing cost and power consumption. The paper also explores emerging applications where infrared imaging is integrated with artificial intelligence for intelligent perception, predictive maintenance, and autonomous decision-making. Critical technical challenges, including emissivity variability, atmospheric interference, thermal drift, and high power demands, are examined alongside current solutions such as multispectral imaging, deep learning-based denoising, and novel calibration techniques. Finally, future directions are proposed, highlighting opportunities in materials science, computational imaging, and sensor fusion to unlock the next generation of compact, intelligent, and high-performance thermal imaging systems. This review aims to serve as a comprehensive resource for researchers and engineers seeking to advance the capabilities and applications of infrared thermography.