In the following article, the science and technology behind infrared imaging is described with many examples. The history of the discovery of the infrared part of the electromagnetic spectrum is outlined along with a physical explanation of infrared radiation and some of the applications of infrared technology in industry. Detailed descriptions of typical infrared imaging systems along with infrared imaging system modeling is provided. The next section includes a lengthy description of modern image processing, in other words, how a computer can be used to improve and analyze the images produced from infrared imaging systems. Several clutter and infrared image quality metrics, such as texture and entropy, are examined and their relevance to ground vehicle target acquisition is described. Texture and entropy metrics are computed for several example images and then compared to an experimental probability of detection in the Visual Perception Lab. Comparison of computational metrics to experimental human perception metrics is a very important type of visual image assessment. The use of human perception experiments as a qualifier and validator of infrared imagery quality along with experimental protocols are described. Image processing modern approaches such as relative clutter, probability of edge, image fusion, and fuzzy logic image fusion are explained in detail. Finally, there are examples of the use of infrared imaging for important problems in industry and to the US Army, such as using infrared imaging to detect ice on the external surface of the NASA Space Transport System and how infrared imaging can be used for the purpose of burred mine detection and homeland security applications.