Fig. 1. Thermal images with water ripple FPN in the near-earth sky. (a) Original image; (b) correction image

Fig. 2. Block diagram of temporal high-pass filtering NUC algorithm

Fig. 3. Real-time processing effect of ITHP&GM on FPGA platform. (a) Frame 1; (b) frame 13; (c) frame 55; (d) frame 99

Fig. 4. Infrared imaging detectors for industrial gas leakage gas cloud, which are used in chemical industry parks and oil and gas fields, and their application scenarios

Fig. 5. Infrared polarization thermal imaging system. (a) Time-sharing MW-IR; (b) multi-aperture LW-IR

Fig. 6. Design and fabrication of focus plane polarizer array. (a) 4 polarization; (b) 3 polarization+1 intensity

Fig. 7. Uncooled polarization thermal imaging experimental system and its polarization degree image

Fig. 8. Schematic of pre-polarizer thermal imager correction

Fig. 9. Comparison of polarization images before and after correction. (a) I; (b) Q; (c) U; (d) α; (e) p

Fig. 10. Super-frame HDR thermal imaging system based on long-wave IRFPA

Fig. 11. HDR thermal imaging reconstructed from 3 frames at different integration times

Fig. 12. Flow chart of multi-integral time image fusion-detail enhancement cascade HDR image fusion

Fig. 13. Imaging effect of typical HDR scene^[56]

Fig. 14. HDR IR radiation source and its dynamic scene image and signal changes of mid-temperature dynamic radiation source^[57]

Fig. 15. [in Chinese]

Fig. 16. [in Chinese]

Fig. 17. Distributed bionic compound eye thermal imaging. (a) Sub-aperture 1; (b) sub-aperture 2; (c) sub-aperture 3; (d) sub-aperture 4; (e) stitched image with large FOV

Fig. 18. TIV-Net training framework

Fig. 19. Dual-channel infrared and color visible imaging acquisition and processing. (a) Ground platform; (b) UAV platform

Fig. 20. Model conversion results of FLIR data set training on our infrared image test set

Fig. 21. Model conversion results of our own data set training on our infrared image test set