Laser & Optoelectronics Progress, Volume. 61, Issue 8, 0809001(2024)
Color Hologram Reconstruction Based on Deep Learning
Fig. 1. Hologram recording optical path map
Fig. 2. Zero filling reconstruction of color hologram. (a) Green light reconstruction image; (b) blue light reconstruction image; (c) red light reconstruction image (d) synthetic color holographic reconstruction image
Fig. 3. Schematic diagram of CHR-Net structure
Fig. 4. Deep supervision mechanism
Fig. 5. Example of dataset production
Fig. 6. Network error curve
Fig. 7. Output results from three branches under deep supervision; (a) Original image; (b) out2; (c) out1; (d) out
Fig. 8. Comparison of reconstruction effects of different algorithms. (a) Original images; (b) S-FFT reconstruction images; (c) U-Net reconstruction images; (d) CHR-Net reconstruction images
Fig. 9. Verification of Fresnel hologram reconstruction from actual shooting. (a) Original image; (b) S-FFT reconstruction image; (c) U-Net reconstruction image; (d) CHR-Net reconstruction image
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Juntong Liu, Jinbin Gui, Aishuai Chen, Xiandong Ma, Xianfei Hu. Color Hologram Reconstruction Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2024, 61(8): 0809001
Category: Holography
Received: Jun. 8, 2023
Accepted: Jul. 31, 2023
Published Online: Mar. 5, 2024
The Author Email: Gui Jinbin (jinbingui@163.com)