An approach for holographic projection with higher image quality and fast convergence rate

Tingting, 翟婷婷 Zhai; Song, Qiang; Liao, Engle; Tam, Alwin Ming Wai; Zhu, Jun‐Yan

doi:10.1016/j.ijleo.2018.01.055

Cited by 9 publications

(3 citation statements)

References 14 publications

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“…With the development of modern science and technology, the construction of places has become simpler and simpler. Nowadays, many visual artists actively respond to the drastic changes taking place in today's society, build a communication bridge between real places and virtual places, and use holographic image technology to organically integrate them with each other [1]. We are increasingly shuttling through the network of unbounded space.…”

Section: Introductionmentioning

confidence: 99%

Construction of Holographic Immersion Chamber Based on Multisource Information Fusion and Interactive Virtual Reality Technology

Wang

Liu²

2022

Journal of Function Spaces

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Nowadays, many visual artists actively respond to the drastic changes taking place in today’s society, build a communication bridge between real places and virtual places, and use holographic image technology to organically integrate them with each other. We are increasingly shuttling through the network of unbounded space. These spaces have no fixed geographical location. With the help of modern science and technology, they often fall into the field of vision of the viewer. With the development of the times, virtual reality technology is a computer simulation system that can create and experience the virtual world. It mainly uses computers to generate a simulated environment. It is a multisource information fusion interactive virtual reality technology to help users immerse themselves in the virtual environment. This paper studies the holographic immersion chamber based on multisource information fusion interactive virtual reality technology. The approximation index of the transformation matrix calculated by the registration algorithm based on SIFT+MSA is 1.7073, which is less than 4.0017 obtained by SIFT matching algorithm. It can be seen that the error of CCD image registration parameters calculated by this algorithm is smaller. In the process of the development of multisource information fusion interactive virtual reality technology, the technical feature of virtual reality is gradually integrated into the user and application object, becoming more closely connected and finally causing the user of the technology the feeling of “immersion” in the use experience.

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Section: Introductionmentioning

confidence: 99%

Construction of Holographic Immersion Chamber Based on Multisource Information Fusion and Interactive Virtual Reality Technology

Wang

Liu²

2022

Journal of Function Spaces

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“…The image after zero-padding is called the target image, as shown in Figure 4. The purpose of zero-padding is to move the background noise from the signal region to the non-signal region for a high Signal-to-Noise Ratio (SNR) in the reconstructed image [31].…”

Section: Hybrid Methods Of Aw-pgdmentioning

confidence: 99%

A Hybrid Iterative Algorithm of Amplitude Weighting and Phase Gradient Descent for Generating Phase-Only Fourier Hologram

Min¹,

Yang²,

Du³

et al. 2022

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Reconstruction of target images from phase-only hologram (POH) has the advantages of high diffraction efficiency and no conjugate terms. The Gerchberg-Saxton (GS) algorithm is a classical algorithm applied to recover the phase, but it most likely stagnantes after a few iterations. This paper proposes a hybrid iterative algorithm of Amplitude Weighting and Phase Gradient Descent (AW-PGD) to generate a higher-quality POH. Firstly, the quadratic phase is used as the initial phase, zero-pads the periphery of the target image, and then multiplies the two to form the complex amplitude as the iterative initial value. During iteration, the amplitude of the reconstructed image is constrained by an adaptive dynamic exponential term in the signal region to improve the reconstruction accuracy, the constraint in the non-signal region is relaxed to reduce the computational effort at the same time; and the phase gradient descent technology is used to increase the iteration step and speed up the convergence. Finally, the target image amplitude is reconstructed based on the generated POH. The numerical simulation results show that the algorithm does not have a significant increase in time cost with better reconstruction quality than the GS, Weighted GS (WGS) and Adaptive Weighted GS (AWGS) algorithm.

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“…Thus, some modifications applied to optimization algorithms are also studied. Since the complex distributions on both the object plane and the hologram plane are calculated in iterations, the framework of the alternating projections possesses the flexibility to include manipulations on the object phase 111 , Gaussian illumination 112 , weighting factors 113 , internal processing in the loop 114 , partitioned optimization 115 , 116 and multi-loop optimization 117 . With highly promoted reconstructing accuracy and computation stability enabled by accumulated improvements on alternating projection algorithms, alternating projection algorithms occupy an indispensable part in optimizations of CGH, especially for the synthesis of holograms encoded on static holographic media, like DOEs 118 , 119 and metasurfaces 120 – 122 .…”

Section: Frameworkmentioning

confidence: 99%

Non-convex optimization for inverse problem solving in computer-generated holography

Sui,

He,

Chu

et al. 2024

Light Sci Appl

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Computer-generated holography is a promising technique that modulates user-defined wavefronts with digital holograms. Computing appropriate holograms with faithful reconstructions is not only a problem closely related to the fundamental basis of holography but also a long-standing challenge for researchers in general fields of optics. Finding the exact solution of a desired hologram to reconstruct an accurate target object constitutes an ill-posed inverse problem. The general practice of single-diffraction computation for synthesizing holograms can only provide an approximate answer, which is subject to limitations in numerical implementation. Various non-convex optimization algorithms are thus designed to seek an optimal solution by introducing different constraints, frameworks, and initializations. Herein, we overview the optimization algorithms applied to computer-generated holography, incorporating principles of hologram synthesis based on alternative projections and gradient descent methods. This is aimed to provide an underlying basis for optimized hologram generation, as well as insights into the cutting-edge developments of this rapidly evolving field for potential applications in virtual reality, augmented reality, head-up display, data encryption, laser fabrication, and metasurface design.

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An approach for holographic projection with higher image quality and fast convergence rate

Cited by 9 publications

References 14 publications

Construction of Holographic Immersion Chamber Based on Multisource Information Fusion and Interactive Virtual Reality Technology

Construction of Holographic Immersion Chamber Based on Multisource Information Fusion and Interactive Virtual Reality Technology

A Hybrid Iterative Algorithm of Amplitude Weighting and Phase Gradient Descent for Generating Phase-Only Fourier Hologram

Non-convex optimization for inverse problem solving in computer-generated holography

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