In-line hologram segmentation for volumetric samples

We propose a fast, noniterative method to segment an in-line hologram of a volumetric sample into in-line subholograms according to its constituent objects. In contrast to the phase retrieval or twin image elimination algorithms, we do not aim or require to reconstruct the complex wave field of all the objects, which would be a more complex task, but only provide a good estimate about the contribution of the particular objects to the original hologram quickly. The introduced hologram segmentation algorithm exploits the special inner structure of the in-line holograms and applies only the estimated supports and reconstruction distances of the corresponding objects as parameters. The performance of the proposed method is demonstrated and analyzed experimentally both on synthetic and measured holograms. We discussed how the proposed algorithm can be efficiently applied for object reconstruction and phase retrieval tasks.