AbstractSignificant research efforts have been invested in attempting to reliably capture and visualize holograms since their inception in 1962. However, less attention has been given to the digital representation of the recorded holograms, which differ considerably from digitally recorded photographs. Holography enables us to faithfully reproduce a wavefront of a given scene, both in amplitude as well as in phase. This property is particularly useful for 3D visualization applications. In this thesis, we studied the properties of digitally captured holograms and investigated how to compress digital holographic data such that it can be stored and transported over bandwidth-limited channels whilst guaranteeing minimal quality or maximum distortion constraints. Two types of recorded holograms have been examined: off-axis holograms and the direct reconstruction of the wavefront.
Multiple existing and new methods have been investigated and compared for holographic compression. Results show significantly improved PSNR performance of over 18% when combining the direction-adaptive discrete wavelet transform with non-standard decomposition schemes for off-axis recordings. The recordings containing the complete wavefront on the other hand are observed to be better compressible when deploying newly introduced “modulo wavelets” on the phase data followed by a wavelet-based amplitude-weighting method on the phase wavelet coefficients.
The findings in this thesis will contribute to a reduction of the storage space needs and communication bandwidth for holographic recordings.
|Date of Award||2013|
- image coding