Since its invention in 1948, holography has held the promise to empower full-parallax 3D visualization. Though, only in recent years it has returned to the forefront of 3D visualization technologies. This is due to the steady growth of computational power and significant improvements in nano-electronics, optical hardware and photonics technologies. However, several hardware and signal processing challenges are yet to be addressed in order to facilitate an immersive 3D experience via a complete pipeline for high-quality dynamic holography with full-parallax and wide field of view.

In this regard, one of the core challenges is modeling the perceived visual quality of the rendered holograms, which has a vital impact on steering the other components of the holographic imaging pipeline (e.g.  optimizing holographic compression methods). While the design of highly efficient numerical methods in Computer-Generated Holography (CGH) and efficient encoders for holographic content is gaining momentum, visual quality assessment of holograms has a rather long way to reach its primary milestones due to various open problems along the way. Among others, main issues include presence of speckle noise, lack of comprehensive -perceptually annotated- holographic datasets, complexities regarding fidelity measurements of complex-valued data and perceptual quality prediction of the rendered 3D scene from the heavily noisy fringe patterns of the holographic complex wavefield. Although, some limited experiments have been performed to measure the effect of quantization on the reconstruction quality of holographic signals, little formal information is available on the perception of reconstruction errors by the human visual system. Moreover, knowledge from current 2D and 3D perception research can only be partially extrapolated to a holographic setting.  Additionally, mature rendering devices are missing as well. These complications lead to the conclusion that parameterizing the quality perception of the human visual system will be a very exploratory process and of high risk.

Nonetheless, in this research we will attempt to mitigate the risk by fragmenting the main issues as much as possible and -in combination with educated decisions- construct a suitable model and methodology to address the aforementioned issues for visual quality assessment of the digital holograms. From a global perspective, this research track covers necessary components in support of (1) modelling the behavior of the human visual system based upon psychovisual experiments, (2) subjective quality testing procedures and (3) design of perceptual quality metrics.