The performance of automatic target recognition (ATR) systems using thermal infrared images is limited by the low contrast in intensity for terrestrial scenes. We are developing a thermal imaging technique where, in each image pixel, a combination of intensity and polarization data is captured simultaneously. In this paper, we demonstrate, using synthetic polarization images, that a combination of intensity and polarization data will significantly improve the performance of detection and classification functions in an ATR system. The images were generated using a ray tracing computer program, modified to calculate the polarization characteristics of thermal radiation emitted from surfaces. We developed novel polarization- sensitive target edge detection, segmentation, and recognition algorithms. A set of performance metrics for the evaluation showed that, for large ranges of viewing elevation and aspect angles, using a combination of polarization and intensity data significantly improves the performance of the algorithms over using only the intensity data.