Deep learning extends imaging depth and speeds up hologram reconstruction
https://phys.org/news/2018-05-deep-imaging-depth-hologram-reconstruction.html
This research was led by Dr. Aydogan Ozcan, the Chancellor's Professor of electrical and computer engineering at UCLA and an HHMI Professor with the Howard Hughes Medical Institute, along with Yichen Wu, a graduate student, and Dr. Yair Rivenson, a postdoctoral scholar, both at the UCLA electrical and computer engineering department.
The authors validated this deep learning based approach by successfully reconstructing holograms of aerosols and human tissue samples. Overall, this approach significantly boosts the computational efficiency and the reconstruction speed of high-resolution holographic imaging by simultaneously performing autofocusing and phase recovery, which also increases the robustness of the image reconstruction process to potential misalignments in the optical setup by extending the depth of the reconstructed images.