Hologram conversion for speckle free reconstruction using light field extraction and deep learning

Area of Science:

• Optics and Photonics
• Digital Holography
• Computational Imaging

Background:

• Speckle noise is a significant challenge in holographic reconstructions, often necessitating specialized holograms.
• Existing speckle-less reconstruction methods have limited applicability due to requirements for specific hologram formats.
• General pre-existing holograms cannot be directly used with many advanced reconstruction techniques.

Purpose of the Study:

• To propose a novel hologram conversion technique for enabling speckle-less reconstruction from general, pre-existing holograms.
• To adapt existing holograms with random phase distributions into new formats suitable for advanced speckle-less reconstruction.
• To broaden the application scope of speckle-less reconstruction methods to a wider range of holographic data.

Main Methods:

• Extraction of orthographic views from an existing hologram.
• Speckle noise removal from extracted views using a convolutional neural network (CNN).
• Synthesis of new holograms with desired carrier waves using a non-hogel based computer-generated hologram (CGH) technique.

Main Results:

• Successfully demonstrated the conversion of general holograms for speckle-less reconstruction.
• Validated the technique with two distinct speckle-less reconstruction methods: temporal speckle averaging and time-multiplexing of interleaved angular spectrums.
• The proposed method effectively transforms holograms, enabling compatibility with advanced speckle-less reconstruction algorithms.

Conclusions:

• The developed hologram conversion technique significantly enhances the utility of general holograms for speckle-less reconstruction.
• This approach overcomes the limitations of specialized hologram requirements, making advanced reconstruction techniques more accessible.
• The method provides a versatile solution for applying speckle-less reconstruction to diverse holographic datasets.