Synthesis of thermal hyperspectral imagery

Patent metadata

Field	Value
Publication number	US-11818446-B2
Application number	US-202117351828-A
Country	US
Kind code	B2
Filing date	Jun 18, 2021
Priority date	Jun 18, 2021
Publication date	Nov 14, 2023
Grant date	Nov 14, 2023

Abstract

A system simulates hyperspectral imaging data or multispectral imaging data for a simulated sensor. Blackbody radiance of real-world thermal imagery data is computed using a Planck function, which generates a simulated spectral hypercube. Spectral emissivity data for background materials are multiplied by a per-pixel weighting function, which generates weighted spectral emissivity data. The simulated spectral hypercube is multiplied by the weighted spectral emissivity data, which generates background data in the simulated spectral hypercube. Simulated targets are inserted the background data using the Planck function. The simulated spectral hypercube is modified, and then it is used to estimate a mission measure of effectiveness of the simulated sensor.

First claim

The invention claimed is:

1. A process for simulating hyperspectral imaging data or multispectral imaging data for a simulated sensor for use in designing and testing infrared planetary observation systems, the process comprising:
receiving into a computer processor real-world thermal imagery data and spectral emissivity for two or more background materials;
computing blackbody radiance of the real-world thermal imagery data using a Planck function, thereby generating a simulated spectral hypercube of data;
multiplying the 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.

2. The process of claim 1 , wherein the mission measure of effectiveness comprises a probability of detection for a given probability of a false alarm.

3. The process of claim 1 , wherein the computation of the blackbody radiance is executed over a range of wavelengths.

4. The process of claim 1 , wherein the spectral emissivity data are received from a spectral library.

5. The process of claim 1 , wherein the multiplication of the simulated spectral hypercube of data by the weighted spectral emissivity data is executed on a per pixel basis.

6. The process of claim 1 , wherein the weighting function comprises a classification of each pixel as containing one or more materials with a fractional abundance estimate.

7. The process of claim 1 , wherein the real-world thermal imagery data and the simulated spectral hypercube of data comprise one or more of medium wave infrared (MWIR) data, long wave infrared (LWIR) data, and very long wave infrared (VLWIR) data.

8. 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 and spectral emissivity for two or more background materials;
computing blackbody radiance of the real-world thermal imagery data using a Planck function, thereby generating a simulated spectral hypercube of data;
multiplying the 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.

9. The non-transitory machine-readable medium of claim 8 , wherein the mission measure of effectiveness comprises a probability of detection for a given probability of a false alarm.

10. The non-transitory machine-readable medium of claim 8 , wherein the computation of the blackbody radiance is executed over a range of wavelengths.

11. The non-transitory machine-readable medium of claim 8 , wherein the spectral emissivity data are received from a spectral library.

12. The non-transitory machine-readable medium of claim 8 , wherein the multiplication of the simulated spectral hypercube of data by the weighted spectral emissivity data is executed on a per pixel basis.

13. The non-transitory machine-readable medium of claim 8 , wherein the weighting function comprises a classification of each pixel as containing one or more materials with a fractional abundance estimate.

14. The non-transitory machine-readable medium of claim 8 , wherein the real-world thermal imagery data and the simulated spectral hypercube of data comprise one or more of medium wave infrared (MWIR) data, long wave infrared (LWIR) data, and very long wave infrared, (VLWIR) data.

15. 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 and spectral emissivity for two or more background materials;
computing blackbody radiance of the real-world thermal imagery data using a Planck function, thereby generating a simulated spectral hypercube of data;
multiplying the 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.

16. The system of claim 15 , wherein the mission measure of effectiveness comprises a probability of detection for a given probability of a false alarm.

17. The system of claim 15 , wherein the computation of the blackbody radiance is executed over a range of wavelengths.

18. The system of claim 15 , wherein the spectral emissivity data are received from a spectral library.

19. The system of claim 15 , wherein the multiplication of the simulated spectral hypercube of data by the weighted spectral emissivity data is executed on a per pixel basis.

20. The system of claim 15 , wherein the weighting function comprises a classification of each pixel as containing one or more materials with a fractional abundance estimate; and wherein the real

Assignees

• Raytheon Co

Inventors

• Zywicki Randall W
• Mann David Christopher

Classifications

• G01J5/56 Primary

  Electrical features thereof · CPC title

• H04N23/11 Primary

  for generating image signals from visible and infrared light wavelengths · CPC title

• G01J5/53

  Reference sources, e.g. standard lamps; Black bodies · CPC title

• G01J5/54

  Optical arrangements · CPC title

• G01J2005/0077

  Imaging · CPC title