Abstract
Digital video holography faces two main problems: 1) computer-generation of holograms is computationally very costly, even more when dynamic content is considered; 2) the transmission of many high-resolution holograms requires large bandwidths. Motion compensation algorithms leverage temporal redundancies and can be used to address both issues by predicting future frames from preceding ones. Unfortunately, existing holographic motion compensation methods can only model uniform motions of entire 3D scenes. We address this limitation by proposing both a segmentation scheme for multi-object holograms based on Gabor masks and derive a Gabor mask-based multi-object motion compensation (GMMC) method for the compensation of independently moving objects within a single hologram. The utilized Gabor masks are defined in 4D space-frequency domain (also known as time-frequency domain or optical phase-space). GMMC can segment holograms containing an arbitrary number of mutually occluding objects by means of a coarse triangulation of the scene as side information. We demonstrate high segmentation quality (down to ≤ 0.01% normalized mean-squared error) with Gabor masks for scenes with spatial occlusions. The support of holographic motion compensation for arbitrary multi-object scenes can enable faster generation or improved video compression rates for dynamic digital holography.
Highlights
The optical acquisition of digital holograms (DH) outdoors and/or of moving objects is highly impractical because of illumination constraints, detector bandwidths, and setup stability requirements
Existing holographic motion compensation methods can only model uniform motions of entire 3D scenes. We address this limitation by proposing both a segmentation scheme for multi-object holograms based on Gabor masks and derive a Gabor mask-based multi-object motion compensation (GMMC) method for the compensation of independently moving objects within a single hologram
Gabor mask-based motion compensation (GMMC) can segment holograms containing an arbitrary number of mutually occluding objects by means of a coarse triangulation of the scene as side information
Summary
The optical acquisition of digital holograms (DH) outdoors and/or of moving objects is highly impractical because of illumination constraints, detector bandwidths, and setup stability requirements. The most likely source for holographic video content is computer-generated holography based on 3D data representations. The 3D data can be either fully synthetic or acquired from alternative imaging setups, such as a set of cameras recording arbitrary scenes from multiple angles; surface reconstruction and scene stitching can recreate a virtual world from the recorded content [1]. Since much of multimedia content is dynamic, efficient handling of holographic video sequences is an important task. Individual hologram frames with large apertures and viewing angles require resolutions of up to 1012 pixels. Compounding this fact with video frame rates imposes unrealistic bandwidth requirements, if the data is not compressed. Only the modified parts have to be computed and/or signaled rather than the entire frame
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
