Simulation of digital holographic recording and reconstruction using a generalized matrix method

Area of Science:

• Optics and Photonics
• Computational Imaging
• Machine Learning Applications

Background:

• Digital holography offers high-resolution intensity and phase imaging, attracting machine learning interest, particularly in bioengineering.
• Accurate simulation of holographic recording is crucial for advancing these applications.

Purpose of the Study:

• To demonstrate a high-fidelity simulation of holographic recording.
• To generalize holographic recording configurations using a matrix method.
• To validate the simulation through digital phase reconstruction and aberration compensation.

Main Methods:

• Numerical simulation of coherent light propagation through optical elements and objects.
• Predicting optical interference, diffraction, aberrations, and speckle.
• Employing a matrix method for generalized optical transformations.
• Digital phase reconstruction and aberration compensation for off-axis configurations.

Main Results:

• A generalized matrix method for predicting complex fields in arbitrary holographic configurations.
• Validation of the simulation method through reconstruction of simulated holograms.
• Presentation of reconstruction errors for various geometries and objects.

Conclusions:

• The generalized holographic simulation accurately models recording processes.
• This simulation facilitates the creation of databases for training machine learning algorithms.
• The work supports the use of simulated holograms for object classification across diverse holographic setups.