Infrared and Laser Engineering, Volume. 53, Issue 5, 20240049(2024)
Deep learning-based infrared imaging degradation model identification and super-resolution reconstruction
Fig. 6. Blur kernel varies with working temperature and spatial position
Fig. 7. (a) Calibrated blur kernels; (b) Blur kernels predicted by blur kernel modeling network
Fig. 9. (a) Real-world image acquisition system; (b) Experimental set up inside the test chamber
Fig. 10. Visual results of different methods on “scene 1” images captured at different working temperature for scale factor 4
Fig. 11. Visual results of different methods on “scene2” images captured at different working temperature for scale factor 4
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Junfeng Cao, Qinghai Ding, Depeng Zou, Hengjia Qin, Haibo Luo. Deep learning-based infrared imaging degradation model identification and super-resolution reconstruction[J]. Infrared and Laser Engineering, 2024, 53(5): 20240049
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Received: Jan. 27, 2024
Accepted: --
Published Online: Jun. 21, 2024
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