Synthesis of thermal hyperspectral imagery

A non-transitory machine-readable medium comprising instructions that when executed by a computer processor execute a process comprising:

• receiving into a computer processor real-world thermal imagery data;
• computing blackbody radiance of the real-world thermal imagery data using a Planck function, thereby generating a simulated spectral hypercube of data;
• multiplying spectral emissivity data for two or more background materials by a per-pixel weighting function, thereby generating weighted spectral emissivity data and a mixture of materials within a pixel;
• multiplying the simulated spectral hypercube of data by the weighted spectral emissivity data, thereby generating background data in the simulated spectral hypercube of data;
• inserting simulated targets using target material and target temperatures into the background data using the Planck function;
• modifying the simulated spectral hypercube of data by adding one or more of an effect of atmospheric transmission, path radiance, and turbulence;
• modifying the simulated spectral hypercube of data by adding one or more sensor effects comprising noise, a modular transfer function loss due to diffraction, a sampling of the simulated sensor, an optical aberration, a scanning of the simulated sensor, and a line-of-sight motion of the simulated sensor;
• and
• using the simulated spectral hypercube of data to estimate a mission measure of effectiveness of the simulated sensor.

A system comprising:

• a computer processor;
• and
• a computer memory coupled to the computer processor;
• wherein the computer processor and the computer memory are operable for:
• receiving into a computer processor real-world thermal imagery data;
• computing blackbody radiance of the real-world thermal imagery data using a Planck function, thereby generating a simulated spectral hypercube of data;
• multiplying spectral emissivity data for two or more background materials by a per-pixel weighting function, thereby generating weighted spectral emissivity data and a mixture of materials within a pixel;
• multiplying the simulated spectral hypercube of data by the weighted spectral emissivity data, thereby generating background data in the simulated spectral hypercube of data;
• inserting simulated targets using target material and target temperatures into the background data using the Planck function;
• modifying the simulated spectral hypercube of data by adding one or more of an effect of atmospheric transmission, path radiance, and turbulence;
• modifying the simulated spectral hypercube of data by adding one or more sensor effects comprising noise, a modular transfer function loss due to diffraction, a sampling of the simulated sensor, an optical aberration, a scanning of the simulated sensor, and a line-of-sight motion of the simulated sensor;
• and
• using the simulated spectral hypercube of data to estimate a mission measure of effectiveness of the simulated sensor.