U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization Camera
We present a novel high-resolution complex field extraction technique utilizing U-Net-based architecture to effectively overcome the inherent resolution limitations of polarization cameras with micro-polarized arrays. Our method extracts high-resolution complex field information, achieving a resolut...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/11/12/1172 |
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| author | Askari Mehdi Yongjun Lim Kwan-Jung Oh Jae-Hyeung Park |
| author_facet | Askari Mehdi Yongjun Lim Kwan-Jung Oh Jae-Hyeung Park |
| author_sort | Askari Mehdi |
| collection | DOAJ |
| description | We present a novel high-resolution complex field extraction technique utilizing U-Net-based architecture to effectively overcome the inherent resolution limitations of polarization cameras with micro-polarized arrays. Our method extracts high-resolution complex field information, achieving a resolution comparable to that of the original polarization camera. Utilizing the parallel phase-shifting digital holography technique, we extracted high-resolution complex field information from four high-resolution phase-shifted interference patterns predicted by our network directly at the hologram plane. Extracting the object’s complex field directly at the hologram plane rather than the object’s plane, our method eliminates the dependency on numerical propagation during dataset acquisition, enabling reconstruction of objects at various depths without DC and conjugate noise. By training the network with real-valued interference patterns and using only a single pair of low- and high-resolution input and ground truth interference patterns, we simplify computational complexity and improve efficiency. Our simulations demonstrate the network’s robustness to variations in random phase distributions and transverse shifts in the input patterns. The effectiveness of the proposed method is demonstrated through numerical simulations, showing an average improvement of over 4 dB in peak-signal-to-noise ratio and 25% in intensity normalized cross-correlation metrics for object reconstruction quality. |
| format | Article |
| id | doaj-art-702fd70ed442457ca027bc1ccd2b2712 |
| institution | DOAJ |
| issn | 2304-6732 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Photonics |
| spelling | doaj-art-702fd70ed442457ca027bc1ccd2b27122025-08-20T02:43:45ZengMDPI AGPhotonics2304-67322024-12-011112117210.3390/photonics11121172U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization CameraAskari Mehdi0Yongjun Lim1Kwan-Jung Oh2Jae-Hyeung Park3Inter-University Semiconductor Research Center, Seoul National University, Seoul 08826, Republic of KoreaImmersive Media Research Section, Media Research Division, Electronics and Telecommunications Research Institute, 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of KoreaImmersive Media Research Section, Media Research Division, Electronics and Telecommunications Research Institute, 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of KoreaDepartment of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of KoreaWe present a novel high-resolution complex field extraction technique utilizing U-Net-based architecture to effectively overcome the inherent resolution limitations of polarization cameras with micro-polarized arrays. Our method extracts high-resolution complex field information, achieving a resolution comparable to that of the original polarization camera. Utilizing the parallel phase-shifting digital holography technique, we extracted high-resolution complex field information from four high-resolution phase-shifted interference patterns predicted by our network directly at the hologram plane. Extracting the object’s complex field directly at the hologram plane rather than the object’s plane, our method eliminates the dependency on numerical propagation during dataset acquisition, enabling reconstruction of objects at various depths without DC and conjugate noise. By training the network with real-valued interference patterns and using only a single pair of low- and high-resolution input and ground truth interference patterns, we simplify computational complexity and improve efficiency. Our simulations demonstrate the network’s robustness to variations in random phase distributions and transverse shifts in the input patterns. The effectiveness of the proposed method is demonstrated through numerical simulations, showing an average improvement of over 4 dB in peak-signal-to-noise ratio and 25% in intensity normalized cross-correlation metrics for object reconstruction quality.https://www.mdpi.com/2304-6732/11/12/1172deep learningcomplex field extractionpolarized image sensorphase-shifting holographyimage super-resolution |
| spellingShingle | Askari Mehdi Yongjun Lim Kwan-Jung Oh Jae-Hyeung Park U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization Camera Photonics deep learning complex field extraction polarized image sensor phase-shifting holography image super-resolution |
| title | U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization Camera |
| title_full | U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization Camera |
| title_fullStr | U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization Camera |
| title_full_unstemmed | U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization Camera |
| title_short | U-Net Driven High-Resolution Complex Field Information Prediction in Single-Shot Four-Step Phase-Shifted Digital Holography Using Polarization Camera |
| title_sort | u net driven high resolution complex field information prediction in single shot four step phase shifted digital holography using polarization camera |
| topic | deep learning complex field extraction polarized image sensor phase-shifting holography image super-resolution |
| url | https://www.mdpi.com/2304-6732/11/12/1172 |
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