Laser & Optoelectronics Progress, Volume. 61, Issue 4, 0411002(2024)
Phase Compensation Algorithm for Off-Axis Digital Holography Based on a Radial Basis Function Neural Network(Invited)
Fig. 1. Wavefront relationship in CCD recording process
Fig. 2. Topology of RBF network in phase recovery
Fig. 3. Flow chart of RBF phase recovery algorithm
Fig. 4. Simulation results: (a) Digital hologram; (b) Fourier spectrum; (c) FTM initial reconstruction phase; (d) RBF compensation phase and selected training scatters; (e) corrected phase; (f) the simulated object, SCM, PCA and RBF data at the white line section
Fig. 5. The change of loss function with the number of iterations
Fig. 6. System diagram
Fig. 7. Experimental results. (a) Digital hologram; (b) PCA reconstruction phase; (c) SCM reconstruction phase; (d) RBF reconstruction phase; (e) DEM reconstruction phase; (f) the white line section data in Fig. 7 (a)
Fig. 8. Experimental results. (a) Digital hologram; (b) the mask for obtaining training data; (c) SCM reconstruction phase; (d) PCA reconstruction phase; (e) DEM reconstruction phase; (f) RBF reconstruction phase
Fig. 9. The phase difference value between DEM and RBF
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Youzhou Shi, Yihui Wu, Wenchao Zhou. Phase Compensation Algorithm for Off-Axis Digital Holography Based on a Radial Basis Function Neural Network(Invited)[J]. Laser & Optoelectronics Progress, 2024, 61(4): 0411002
Category: Imaging Systems
Received: Apr. 18, 2023
Accepted: May. 29, 2023
Published Online: Feb. 22, 2024
The Author Email: Zhou Wenchao (zhouvc@ciomp.ac.cn)