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.
Highlights
Digital holography is a technology that allows for recording and reconstructing both the amplitude and phase of electromagnetic wave fields
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 Peak Signal-to-Noise Ratio (PSNR), as well improved view preservation
Albeit often not expressed in these terms, many Computer-Generated Holography (CGH) methods leverage the sparsity of the holographic signal in some bases where only a fraction of the coefficients need to be updated; in doing so, they substantially accelerate the generation of holograms
Summary
Digital holography is a technology that allows for recording and reconstructing both the amplitude and phase of electromagnetic wave fields It can account for all visual cues, such as continuous parallax, depicts no accommodation-vergence conflict and supports resolutions up to the diffraction limit of the wavelength. Acquiring digital holograms with an optical setup for visualization purposes poses several practical limitations: the need for a specialized optical setup, restrictions on camera resolution, pixel pitch and object sizes, contaminations with aberrations and/or speckle noise and the need of a physical object for recording These problems are not present Computer-Generated Holography (CGH), where holograms are numerically computed by simulating the diffraction of light. Albeit often not expressed in these terms, many CGH methods leverage the sparsity of the holographic signal in some bases where only a fraction of the coefficients need to be updated; in doing so, they substantially accelerate the generation of holograms.
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