Infrared thermography accurately depicts the surface temperature distribution of objects in the form of two-dimensional images and has been widely used in many industrial applications such as medical diagnosis, fault detection, energy consumption monitoring and intelligent driving. In this article, the three major challenges that limit the development of infrared thermography is addressed. First of all, the modeling and denoising method is presented to eliminate fixed pattern noise in focal plane array sensor which is the key component in infrared imaging system. Secondly, IR signal reconstruction methodologies are introduced to overcome problems, such as complicated fabrication process, low yield and expensive price of IRFPA, to facilitate large-scale industrial applications. Finally, multi-modal information fusion technology is explored to restore the information lost during the process of 2D image acquisition and to improve the performance of target detection based on multi-spectral information. The latest advances in infrared imaging signal processing technology provide new theory and technology for the development of the next generation of high-quality, high-resolution, low-cost three dimensional infrared imaging system.