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A Python library to numerically recover the complex wavefield information of samples from Digital Holographic Microscopy (DHM) recordings. Phase compensation, phase-shifting methods, and numerical propagators for different configurations and types of recordings in DHM are provided.
This robust tool automates the simulation of the recording process, facilitating mass production of holograms and enhancing the development and training of deep learning models in DHM autofocusing applications.
The proposed hybrid model aims to deliver both aberration-free in-focus amplitude and phase reconstructions, while accurately predicting in-focus distances, from out-of-focus holograms. The tasks were handled independently with the aim of later merging them.