High-quality, multispectral thermal infrared sensors can, under certain conditions, be used to measure more than one surface temperature in a single pixel. Surface temperature retrieval in general is a difficult task, because even for a single unknown surface, the problem is under-determined. For the example of an N-band sensor, a pixel with two materials at two temperatures will, in principle, have 2(N + 1) unknowns (N emissivities and one temperature for each of two materials). In addition, the upwelling path and reflected downwelling radiances must be considered. Split-window (two or more bands) and multi-look (two or more images of the same scene) techniques provide additional information that can be used to reduce the uncertainties in temperature retrieval. Further reduction in the uncertainties is made if the emissivities are known, either a priori (e.g., for water) or by ancillary measurements. Ultimately, if the number of unknowns is reduced sufficiently, the performance of the sensor will determine the achievable temperature sensitivity. This paper will explore the temperature sensitivity for a pixel with two temperatures that can be obtained under various assumptions of sensor performance, atmospheric conditions, number of bands, number of looks, surface emissivity knowledge, and surface composition. Results on synthetic data sets will be presented.