Probing shallower: perceptual loss trained Phase Extraction Neural Network (PLT-PhENN) for artifact-free reconstruction at low photon budget
Deep neural networks (DNNs) are efficient solvers for ill-posed problems and have been shown to outperform classical optimization techniques in several computational imaging problems. In supervised mode, DNNs are trained by minimizing a measure of the difference between their actual output and their...
| Main Authors: | , , , , |
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| Other Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
The Optical Society,
2020-07-22T20:34:18Z.
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| Subjects: | |
| Online Access: | Get fulltext |