Computer-generated holography at high resolutions is a computationally intensive task. Efficient algorithms are needed to generate holograms at acceptable speeds, especially for real-time and interactive applications such as holographic displays. We propose a novel technique to generate holograms using a sparse basis representation in the short-time Fourier space combined with a wavefront-recording plane placed in the middle of the 3D object. By computing the point spread functions in the transform domain, we update only a small subset of the precomputed largest-magnitude coefficients to significantly accelerate the algorithm over conventional look-up table methods. We implement the algorithm on a GPU, and report a speedup factor of over 30. We show that this transform is superior over wavelet-based approaches, and show quantitative and qualitative improvements over the state-of-the-art WASABI method; we report accuracy gains of 2dB PSNR, as well improved view preservation.
Blinder, D & Schelkens, P 2018, 'Accelerated computer generated holography using sparse bases in the STFT domain', Optics Express, vol. 26, no. 2, pp. 1461-1473. https://doi.org/10.1364/OE.26.001461
Blinder, D., & Schelkens, P. (2018). Accelerated computer generated holography using sparse bases in the STFT domain. Optics Express, 26(2), 1461-1473. https://doi.org/10.1364/OE.26.001461
@article{d4dee709a8204d1aaf0b47889645c109,
title = "Accelerated computer generated holography using sparse bases in the STFT domain",
abstract = "Computer-generated holography at high resolutions is a computationally intensive task. Efficient algorithms are needed to generate holograms at acceptable speeds, especially for real-time and interactive applications such as holographic displays. We propose a novel technique to generate holograms using a sparse basis representation in the short-time Fourier space combined with a wavefront-recording plane placed in the middle of the 3D object. By computing the point spread functions in the transform domain, we update only a small subset of the precomputed largest-magnitude coefficients to significantly accelerate the algorithm over conventional look-up table methods. We implement the algorithm on a GPU, and report a speedup factor of over 30. We show that this transform is superior over wavelet-based approaches, and show quantitative and qualitative improvements over the state-of-the-art WASABI method; we report accuracy gains of 2dB PSNR, as well improved view preservation.",
author = "David Blinder and Peter Schelkens",
year = "2018",
month = jan,
day = "22",
doi = "10.1364/OE.26.001461",
language = "English",
volume = "26",
pages = "1461--1473",
journal = "Optics Express",
issn = "1094-4087",
publisher = "The Optical Society",
number = "2",
}