Thermal Image Enhancement Construct For "Seeing Through Obscurants"

Thermal radiation from objects varies within spectral bands according to Planck's law. By modeling measurements of such radiation as a linear sum of contributions from multiple sources, a thermal image may be separated into multiple images of independent objects that represent the original, composite scene. We pose the scene decomposition as an inverse source separation problem, where multiple spectral images are used to improve temperature resolution of the estimated scene. Based on this concept, a unique algorithm is being developed that will enable thermal imagers to "see through certain obscurants" with image enhancement. Numerical simulations along with real images from multiple bands (MWIR and LWIR) suggest the feasibility of selective source removal and radiative spectral extrapolation, which can lead to thermal image enhancement and improved sensor performance. Practical issues related to the use of multiple spectral images (such as image registration and choice of sensing bands) are also discussed.