Clearing key barriers to mass adoption of augmented reality with computer-generated holography

Widjanarko, Taufiq; Guendy, Miguel El; Spiess, Alden O.; Sullivan, Darryl; Durrant, T. J.; Tastemur, O. A.; Newman, Alfred; Milne, Darran F.; Kaczorowski, Andrzej

doi:10.1117/12.2544979

Cited by 4 publications

(4 citation statements)

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“…Computer-generated holography allows the user to digitally generate these interference patterns without previously recording the object onto a photographic plate [2]. The evolution of computer controlled spatial light modulators (SLMs) allowed these devices to be incorporated in optical tweezing [3] and telecommunications [4] as well as digital holographic imaging in the form of augmented reality and virtual reality systems (AR and VR respectively) [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Cimmino simultaneously iterative holographic projection

et al. 2022

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The Cimmino algorithm is an iterative algorithm used for solving linear equations (Ax = b) and is part of a wider family of algebraic reconstruction algorithms. Despite being used in computed tomography and digital signal processing, we present an approach for using it in holographic projections in the Fraunhofer region. Following the work carried out by our group on Kaczmarz holography, an earlier algebraic linear equation solver, we compare the performance and speed of Cimmino against this algorithm. Three versions of the Cimmino algorithm, Cimmino full, Cimmino eye, and Cimmino FFT, are evaluated and compared to both Kaczmarz and Gerchberg-Saxton. Interestingly, the derivation and simplification of Kaczmarz and Cimmino leads to the input-output algorithm originally derived by Fienup and while the solution is well-known, the link between these algorithms is not and despite being around since the 1930s, it was originally used to solve linear equations and not phase retrieval. While the Cimmino full and Cimmino eye reflect fairly poorly against Cimmino FFT and Kaczmarz in terms of image quality and speed, the Cimmino FFT delivers better results in terms of image quality than all algorithms considered. It is significantly faster than Kaczmarz, being only a few milliseconds slower than Gerchberg-Saxton.

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Section: Introductionmentioning

confidence: 99%

Cimmino simultaneously iterative holographic projection

et al. 2022

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“…The development of these technologies has contributed towards the use of SLMs in augmented and virtual reality (AR and VR) systems. [4][5][6][7] SLMs are capable of projecting three-dimensional images with appropriate depth cues that do not exhibit what is known as vergence-accommodation conflict (VAC). [8][9][10] This paper focuses on projecting two-dimensional holographic images in the Fraunhofer region, also known as the far-field or replay field.…”

Section: Introductionmentioning

confidence: 99%

Kaczmarz holography: holographic projection in the Fraunhofer region

et al. 2021

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The Kaczmarz algorithm is an iterative method for solving linear equations in the form of Ax = b. It is widely used in computed tomography (CT) and digital signal processing (DSP) but has yet to be adopted in computer-generated holography (CGH). Phase retrieval algorithms such as Gerchberg-Saxton or Fienup are significantly more popular in this field, however, in this paper we propose a unique and alternative approach to projecting a replay field through Discrete Fourier Transform (DFT) matrices and have shown that there are legitimate benefits to implementing this approach. The gradient descent iteration mechanism adopted by Kaczmarz, for instance, provides finer granularity control over the individual pixels in the replay field. We consequently demonstrate the quality of the image is significantly improved when compared to Gerchberg-Saxton.

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“…Recently, holography has received significant attention from industrial and academic communities, with neural holography [Peng et al 2020] [Shi et al 2021] and numerous other techniques [Sahin et al 2020]. Applications of holography include Augmented/Virtual Reality [Widjanarko et al 2020], Head-Up Displays, and larger display devices ]. In the real world, objects can be viewed in reflections (such as mirrors) and through refractions (such as glass or water); the depth at which these objects focus is defined by the focal power of the material.…”

Section: Introductionmentioning

confidence: 99%