Abstract
Computer-Generated Holography (CGH) algorithms simulate numerical diffraction, being applied in particular for holographic display technology. Due to the wave-based nature of diffraction, CGH is highly computationally intensive, making it especially challenging for driving high-resolution displays in real-time. To this end, we propose a technique for efficiently calculating holograms of 3D line segments. We express the solutions analytically and devise an efficiently computable approximation suitable for massively parallel computing architectures. The algorithms are implemented on a GPU (with CUDA), and we obtain a 70-fold speedup over the reference point-wise algorithm with almost imperceptible quality loss. We report real-time frame rates for CGH of complex 3D line-drawn objects, and validate the algorithm in both a simulation environment as well as on a holographic display setup.
Highlights
C OMPUTER generated holography (CGH) tackles the problem of efficiently calculating numerical diffraction patterns for various applications in holography
This challenge is intensified for holographic video displays, as they require real-time CGH at video rates
We investigate the problem of computing holograms of objects consisting of 3D line segments, i.e. where the endpoints can have arbitrary coordinates
Summary
C OMPUTER generated holography (CGH) tackles the problem of efficiently calculating numerical diffraction patterns for various applications in holography. The primary challenge in CGH is tied to the wave-based nature of holography: every virtual scene element emits light waves that can potentially affect all hologram pixels This manyto-many mapping makes CGH significantly more calculation intensive than conventional ray-based image rendering, where pixels conceptually correspond to a single ray of light. Volumetric or even multi-view displays, holograms can simultaneously provide continuous motion parallax, accurate eye-focusing without accommodation-vergence conflicts, as well as all occlusion and shading cues This makes them promising candidates for augmented and virtual reality applications, since they do not suffer from the drawbacks of head-mounted displays with conventional screens. This paper primarily targets holographic display systems, such as near-eye displays, heads-up displays (HUD) [28], navigation systems in cars and aircraft, and larger scale holographic tabletop systems; this work can benefit applications in pure diffraction theory needing the efficient computation of arbitrary line-shaped apertures in general
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