Yi Huang, Tao Xiong. Deep Iterative Filter Adaptive Network for Simple Lens Imaging System[J]. Laser & Optoelectronics Progress, 2024, 61(10): 1037003
- Laser & Optoelectronics Progress
- Vol. 61, Issue 10, 1037003 (2024)
Fig. 1. The process of making the optical lens. (a) Self-designed single glued lens; (b) PSF of lens at 20° FOV
Fig. 2. Deep iterative adaptive convolution
Fig. 3. Deblurring network with DIFAN
Fig. 4. Comparison of different restoration methods based on simulation dataset. (a) Original blurred image; (b) recovery results of ISD-Deblur; (c) recovery results of DeblurGAN-v2 ; (d) recovery results of proposed DIFAN; (e) ground truth images
Fig. 5. Comparison of network restoration effects based on simulation datasets at different field angles
Fig. 6. Network restoration effect of simulation data set with a plano-convex lens at 15° field of view angle
Fig. 7. Distortion correction and display-capture experiments
Fig. 8. Image pairs taken using display capture devices
Fig. 9. Experimental results. (a) The original blurred images; (b) image recovery results from the network; (c) ground truth images
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Table 1. Comparison of ablation studies
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Table 2. Quantitative comparisons of reconstruction performance
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Table 3. Quantitative comparison of DIFAN restoration comparison experiments under different field of view angles
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Table 4. Quantitative comparison of comparative experiments of different network restoration methods under 15° field of view angle of plano-convex lens
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