Target temperature estimation from thermal infrared (TIR) imagery is a complex task that becomes increasingly more difficult as the target size approaches the size of a projected pixel. At that point the assumption of pixel homogeneity is invalid as the radiance value recorded at the sensor is the result of energy contributions from the target material and any other background material that falls within a pixel boundary. More often than not, thermal infrared pixels are heterogeneous and therefore subpixel temperature extraction becomes an important capability. Typical subpixel estimation approaches make use of multispectral or hyperspectral sensors. These technologies are expensive and multispectral or hyperspectral thermal imagery might not be readily available for a target of interest. A methodology was developed to retrieve the temperature of an object that is smaller than a projected pixel of a single-band TIR image using physics-based modeling. Physics-based refers to the utilization of the Multi-Service Electro-optic Signature (MuSES) heat transfer model, the MODerate spectral resolution atmospheric TRANsmission (MODTRAN) atmospheric propagation algorithm, and the Digital Imaging and Remote Sensing Image Generation (DIRSIG) synthetic image generation model to reproduce a collected thermal image under a number of user-supplied conditions. A target space is created and searched to determine the temperature of the subpixel target of interest from a collected TIR image. The methodology was tested by applying it to single-band thermal imagery collected during an airborne campaign. The emissivity of the targets of interest ranged from 0.02 to 0.91 and the temperature extraction error for the high emissivity targets were similar to the temperature extraction errors found in published papers that employed multi-band techniques
