The atmospheric correction of thermal infrared (TIR) imagery involves the combined tasks of separation of atmospheric transmittance, downwelling flux and upwelling radiance from the surface material spectral emissivity and temperature. The problem is ill posed and is thus hampered by spectral ambiguity among several possible feasible combinations of atmospheric temperature, constituent profiles, and surface material emissivities and temperatures. For many materials, their reflectance spectra in the Vis-SWIR provide a means of identification or at least classification into generic material types, vegetation, soil, etc. If Vis-SWIR data can be registered to TIR data or collected simultaneously as in sensors like the MASTER sensor, then the additional information on material type can be utilized to help lower the ambiguities in the TIR data. If the Vis-SWIR and TIR are collected simultaneously the water column amounts obtained form the atmospheric correction of the Vis-SWIR can also be utilized in reducing the ambiguity in the atmospheric quantities. The TIR atmospheric correction involves expansions in atmospheric and material emissivity basis sets. The method can be applied to hyperspectral and ultraspectral data, however it is particularly useful for multispectral TIR, where spectral smoothness techniques cannot be readily applied. The algorithm is described, and the approach applied to a MASTER sensor data set.