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awesome-holography
A curated list of resources on holographic displays.
https://github.com/bchao1/awesome-holography
Last synced: 3 days ago
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Background, Theory, and Survey
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Survey Papers
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Toward the next-generation VR/AR optics: a review of holographic near-eye displays from a human-centric perspective
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Toward the next-generation VR/AR optics: a review of holographic near-eye displays from a human-centric perspective
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
- Deep learning in holography and coherent imaging
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Background and Theory
- Introduction to Fourier Optics
- Numerical simulation of optical wave propagation: With examples in MATLAB - gritty details of implementing optial wave propagation.
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Computer Generated Holography (CGH) Algorithms
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Learned Hologram Synthesis Methods
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Towards real-time photorealistic 3D holography with deep neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- DeepCGH: 3D computer-generated holography using deep learning
- Deep neural network for multi-depth hologram generation and its training strategy
- Deep-learning-generated holography
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- DeepCGH: 3D computer-generated holography using deep learning
- Deep neural network for multi-depth hologram generation and its training strategy
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- End-to-end Learning of 3D Phase-only Holograms for Holographic Display
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Diffraction-engineered holography: Beyond the depth representation limit of holographic displays
- Phase recovery and holographic image reconstruction using deep learning in neural networks
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Traditional Heuristic Methods
- Computer-generated double-phase holograms - only components to generate holograms using a single phase-only SLM.
- Holographic Near-Eye Displays for Virtual and Augmented Reality - eye display system based on the double phase encoding scheme.
- Monocular 3D see-through head-mounted display via complex amplitude modulation
- Near-eye Light Field Holographic Rendering with Spherical Waves for Wide Field of View Interactive 3D Computer Graphics - source illumination rather than plane-wave illumination to improve the FOV of holograhic displays.
- Computer-generated holograms of 3-D objects composed of tilted planar segments
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms for three-dimensional surface objects with shade and texture
- Extremely high-definition full-parallax computer-generated hologram created by the polygon-based method
- Silhouette method for hidden surface removal in computer holography and its acceleration using the switch-back technique
- Computer generated holograms from three dimensional meshes using an analytic light transport model
- Fast and effective occlusion culling for 3D holographic displays by inverse orthographic projection with low angular sampling
- Computer-generated hologram with occlusion effect using layer-based processing
- Accurate calculation of computer-generated holograms using angular-spectrum layer-oriented method
- Improved layer-based method for rapid hologram generation and real-time interactive holographic display applications
- Computer generated hologram with geometric occlusion using GPU-accelerated depth buffer rasterization for three-dimensional display
- Holographic near-eye displays based on overlap-add stereograms
- Layered holographic stereogram based on inverse Fresnel diffraction
- Fully computed holographic stereogram based algorithm for computer-generated holograms with accurate depth cues
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Monocular 3D see-through head-mounted display via complex amplitude modulation
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Extremely high-definition full-parallax computer-generated hologram created by the polygon-based method
- Silhouette method for hidden surface removal in computer holography and its acceleration using the switch-back technique
- Accurate calculation of computer-generated holograms using angular-spectrum layer-oriented method
- Improved layer-based method for rapid hologram generation and real-time interactive holographic display applications
- Fully computed holographic stereogram based algorithm for computer-generated holograms with accurate depth cues
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
- Computer-generated holograms of tilted planes by a spatial frequency approach
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Iterative Methods
- A practical algorithm for the determination of phase from image and diffraction plane pictures - Saxton (GS) Algorithm**
- Mix-and-Match Holography - retrieval method built upon GS
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Accommodative Holography: Improving Accommodation Response for Perceptually Realistic Holographic Displays - based regularization loss that promotes better accomodation cues.
- Realistic Defocus Blur for Multiplane Computer-Generated Holography - descent) and non-iterative (double phase encoding) methods.
- Gaze-Contingent Retinal Speckle Suppression for Perceptually-Matched Foveated Holographic Displays
- Optimization of computer-generated holograms featuring phase randomness control - bandwidth product of the display system.
- Multi-depth hologram generation using stochastic gradient descent algorithm with complex loss function
- Wirtinger Holography for Near-Eye Displays - only SLM pattern using closed-form Wirtinger complex derivatives in gradient descent.
- 3D computer-generated holography by non-convex optimization
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Metameric Varifocal Holograms - inspired, gaze-contingent loss function that can be easily integrated into CGH optimization. The loss enforces the defocus image regions to only statistically match the defocus target image regions rather than pixel-wise reconstruction. This increases the degrees of freedom for the hologram to distribute light (compared to fitting a focal stack), thus reducing speckle artifacts.
- 3D computer-generated holography by non-convex optimization
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Multi-depth hologram generation using stochastic gradient descent algorithm with complex loss function
- Optimization of computer-generated holograms featuring phase randomness control - bandwidth product of the display system.
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Hogel-free Holography
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
- Fresnel ping-pong algorithm for two-plane computer-generated hologram display
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Learned Propagation Model Methods
- Neural 3D Holography: Learning Accurate Wave Propagation Models for 3D Holographic Virtual and Augmented Reality Displays - linearities, and etc, at the input plane and **multiple** target planes. The usage of two CNNs introduces more degrees of freedom than that of the parameterized propagation model proposed in Peng et al. 2020, such that higher quality 3D holograms can be achieved.
- Time-multiplexed Neural Holography: A Flexible Framework for Holographic Near-eye Displays with Fast Heavily-quantized Spatial Light Modulators - multiplexed quantized SLM patterns to synthesize high quality defocus blur.
- Learned holographic light transport
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Topics in Holographic Display Systems
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Speckle Noise Reduction
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- DCGH: Dynamic Computer Generated Holography for Speckle-Free, High Fidelity 3D Displays - Saxton (GS) algorithm and time-averages them to reduce speckle noise.
- Speckle-free holography with partially coherent light sources and camera-in-the-loop calibration - in-the-loop optimization to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Holographic head-mounted display with RGB light emitting diode light source
- Optimizing image quality for holographic near-eye displays with Michelson Holography - SLM settings. A CITL procedure is also deployed to simultaneously optimize 2 SLM patterns.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Holographic head-mounted display with RGB light emitting diode light source
- Optimizing image quality for holographic near-eye displays with Michelson Holography - SLM settings. A CITL procedure is also deployed to simultaneously optimize 2 SLM patterns.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- DCGH: Dynamic Computer Generated Holography for Speckle-Free, High Fidelity 3D Displays - Saxton (GS) algorithm and time-averages them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- DCGH: Dynamic Computer Generated Holography for Speckle-Free, High Fidelity 3D Displays - Saxton (GS) algorithm and time-averages them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- DCGH: Dynamic Computer Generated Holography for Speckle-Free, High Fidelity 3D Displays - Saxton (GS) algorithm and time-averages them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- DCGH: Dynamic Computer Generated Holography for Speckle-Free, High Fidelity 3D Displays - Saxton (GS) algorithm and time-averages them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Light source optimization for partially coherent holographic displays with consideration of speckle contrast, resolution, and depth of field
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
- Strategies for reducing speckle noise in digital holography
- High‐contrast, speckle‐free, true 3D holography via binary CGH optimization - averaged them to reduce speckle noise.
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Etendue Expansion
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Holographic Optical Elements (HOEs)
- Design and Fabrication of Freeform Holographic Optical Elements
- Holographic display for see-through augmented reality using mirror-lens holographic optical element
- 3D holographic head mounted display using holographic optical elements with astigmatism aberration compensation
- 3D holographic head mounted display using holographic optical elements with astigmatism aberration compensation
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Small Form-factor Displays
- Holographic Glasses for Virtual Reality - like form factor. An optical stack of 2.5mm is achieved by combining pupil-replicating waveguide, SLMs, and geometric phase lenses.
- Holographic pancake optics for thin and lightweight optical see-through augmented reality
- Holographic Optics for Thin and Lightweight Virtual Reality
- Holographic pancake optics for thin and lightweight optical see-through augmented reality
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Compression
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Zero or Higher Diffraction Orders Optimization
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Labs and Researchers
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Zero or Higher Diffraction Orders Optimization
- Computational Imaging Lab, Stanford University
- Computational Imaging Lab, Princeton University
- Computational Biophotonics Laboratory, UNC Chapel Hill
- Graphics and Virtual Reality Group, UNC Chapel Hill
- Computational Light Laboratory, University College London
- Computational Imaging Group, KAUST
- Optical Engineering and Quantum Electronics Lab, Seoul National University
- NVIDIA Research
- Optical Engineering and Quantum Electronics Lab, Seoul National University
- Computational Imaging Lab, Stanford University
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Talks, Lectures, and Tutorials
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Zero or Higher Diffraction Orders Optimization
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Disclaimer
Programming Languages
Categories
Sub Categories
Speckle Noise Reduction
146
Learned Hologram Synthesis Methods
109
Survey Papers
69
Traditional Heuristic Methods
55
Iterative Methods
36
Zero or Higher Diffraction Orders Optimization
13
Holographic Optical Elements (HOEs)
4
Small Form-factor Displays
4
Learned Propagation Model Methods
3
Compression
2
Etendue Expansion
2
Background and Theory
2