Time-frequency domain based transforms and temporal prediction for coding of dynamic holograms

Holography is a discipline of science that measures or reconstructs the wavefield of light by means of interference. The wavefield encodes three-dimensional information and thus has many applications in metrology. Moreover, planar holograms can recreate the wavefield of a 3D object, thereby reproducing all depth cues for all viewpoints, unlike current stereoscopic 3D displays. At high quality, the appearance of a rendered hologram would be indistinguishable from a real object.

High-quality holograms need large volumes of data to be represented, approaching resolutions of billions of pixels. For holographic videos, the data rates needed for transmitting and encoding of the raw holograms quickly become unfeasible with currently available hardware. Efficient coding of holograms will be of utmost importance for future holographic displays.

The properties and statistics of holographic signals, who consist of complicated interference patterns, differ substantially from natural photographic imagery. That is why novel mathematical transforms and algorithms tailored to holographic data should be designed to solve the problem of compressing and transmitting digital holograms.

The main goal of this research proposal is to develop novel representations and algorithms for encoding dynamic holographic signals, and to integrate them in a video codec. This research will impact the computational and energy efficiency with which digital holograms can be generated, compressed and rendered