Color Fourier Ptychography Microscopy Using Three-Dimensional Convolutional Neural Network

Fig. 3. Color reconstruction results of different algorithms. (a) HR image; (b) color LR image; (c) reconstructed HR image of red channel; (d) proposed algorithm; (e) spectrum multiplexing FPM algorithm^[25]; (f) three-channel separated FPM algorithm

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Fig. 4. Numerical simulation results of resolution target as input sample. (a) HR image; (b) color LR image; (c) reconstructed HR image of red channel; (d) proposed algorithm; (e) spectrum multiplexing FPM algorithm^[25]; (f) three-channel separated FPM algorithm

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Fig. 5. Image reconstruction results of experimental system. (a) Color LR image; (b) proposed algorithm; (c) spectrum multiplexing FPM algorithm^[25]; (d) three-channel separated FPM algorithm

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Table 1. RMSE and SSIM of different algorithms
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Table 1. RMSE and SSIM of different algorithms
Algorithm RMSE SSIM
Three-channel separated FPM 0.0067 0.9926
Spectrum multiplexing FPM^[25] 0.1243 0.9820
Proposed algorithm 0.0389 0.9053

Table 2. RMSE and SSIM of different algorithms
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Table 2. RMSE and SSIM of different algorithms
Algorithm RMSE SSIM
Three-channel separated FPM 0.0318 0.9482
Spectrum multiplexing FPM^[25] 0.9698 0.0811
Proposed algorithm 0.0789 0.9301

Table 3. Number of LR images and capturing time of different algorithms
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Table 3. Number of LR images and capturing time of different algorithms
Algorithm Number ofLR images Capturingtime /s
Three-channel separated FPM 723 ~717
Spectrum multiplexing FPM^[25] 241 ~165
Proposed algorithm 243 ~217

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Muyang Zhang, Yanmei Liang. Color Fourier Ptychography Microscopy Using Three-Dimensional Convolutional Neural Network[J]. Acta Optica Sinica, 2020, 40(20): 2011001

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