Speckle reduction in holographic display with partially spatial coherent illumination

Author(s):

Zhao, Zijie; Duan, Junyi & Liu, Juan

Abstract:

“A method of holographic reconstruction under partially spatial coherent illumination with different degree of coherence is proposed to suppress speckle noise based on theoretical analysis. The core factor of speckle reduction based on partially spatial coherent light is convolution operation in CGH reconstruction process. Numerical simulations and optical experiments are both performed to verify the proposed theory. The results reconstructed by proposed and traditional method are compared, and the speckle contrasts can be reduced to 0.05 and 0.08 at most in Fresnel and Fraunhofer zone respectively. The image quality is obviously improved. This method can provide further applications for three-dimensional holographic display, beam shaping and coherence degree modulation techniques.”

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Publication: Optics Communications
Issue/Year: Optics Communications, Volume 507; Pages 127604; 2022
DOI: 10.1016/j.optcom.2021.127604

Dual-task convolutional neural network based on the combination of the U-Net and a diffraction propagation model for phase hologram design with suppressed speckle noise

Author(s):

Sun, Xiuhui; Mu, Xingyu; Xu, Cheng; Pang, Hui; Deng, Qiling; Zhang, Ke; Jiang, Haibo; Du, Jinglei; Yin, Shaoyun & Du, Chunlei

Abstract:

“In this paper, a dual-task convolutional neural network based on the combination of the U-Net and a diffraction propagation model is proposed for the design of phase holograms to suppress speckle noise of the reconstructed images. By introducing a Fresnel transmission layer, based on angular spectrum diffraction theory, as the diffraction propagation model and incorporating it into U-Net as the output layer, the proposed neural network model can describe the actual physical process of holographic imaging, and the distributions of both the light amplitude and phase can be generated. Afterwards, by respectively using the Pearson correlation coefficient (PCC) as the loss function to modulate the distribution of the amplitude, and a proposed target-weighted standard deviation (TWSD) as the loss function to limit the randomness and arbitrariness of the reconstructed phase distribution, the dual tasks of the amplitude reconstruction and phase smoothing are jointly solved, and thus the phase hologram that can produce high quality image without speckle is obtained. Both simulations and optical experiments are carried out to confirm the feasibility and effectiveness of the proposed method. Furthermore, the depth of field (DOF) of the image using the proposed method is much larger than that of using the traditional Gerchberg-Saxton (GS) algorithm due to the smoothness of the reconstructed phase distribution, which is also verified in the experiments. This study provides a new phase hologram design approach and shows the potential of neural networks in the field of the holographic imaging and more.”

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Publication: Optics Express
Issue/Year: Optics Express, Volume 30; Number 2; Pages 2646; 2022
DOI: 10.1364/oe.440956

Polygon-based computer-generated holography: a review of fundamentals and recent progress [Invited]

Author(s):

Zhang, Yaping; Fan, Houxin; Wang, Fan; Gu, Xianfeng; Qian, Xiaofan & Poon, Ting-Chung

Abstract:

“In this review paper, we first provide comprehensive tutorials on two classical methods of polygon-based computer-

generated holography: the traditional method (also called the fast-Fourier-transform-based method) and the

analytical method. Indeed, other modern polygon-based methods build on the idea of the two methods. We will

then present some selective methods with recent developments and progress and compare their computational

reconstructions in terms of calculation speed and image quality, among other things. Finally, we discuss and pro-

pose a fast analytical method called the fast 3D affine transformation method, and based on the method, we present

a numerical reconstruction of a computer-generated hologram (CGH) of a 3D surface consisting of 49,272 pro-

cessed polygons of the face of a real person without the use of graphic processing units; to the best of our knowledge,

this represents a state-of-the-art numerical result in polygon-based computed-generated holography. Finally, we

also show optical reconstructions of such a CGH and another CGH of the Stanford bunny of 59,996 polygons with

31,724 processed polygons after back-face culling. We hope that this paper will bring out some of the essence of

polygon-based computer-generated holography and provide some insights for future research.”

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Publication: Applied Optics
Issue/Year: Applied Optics, Volume 61; Number 5; Pages B363; 2022
DOI: 10.1364/ao.444973

Lensless Optical Encryption of Multilevel Digital Data Containers Using Spatially Incoherent Illumination

Author(s):

Cheremkhin, Pavel; Evtikhiev, Nikolay; Krasnov, Vitaly; Ryabcev, Ilya; Shifrina, Anna & Starikov, Rostislav

Abstract:

“The necessity of the correction of errors emerging during the optical encryption process ledto the extensive use of data containers such as QR codes. However, due to specifics of optical encryp-tion, QR codes are not very well suited for the task, which results in low error correction capabilitiesin optical experiments mainly due to easily breakable QR code’s service elements and byte datastructure. In this paper, we present optical implementation of information optical encryption systemutilizing new multilevel customizable digital data containers with high data density. The results ofoptical experiments demonstrate efficient error correction capabilities of the new data container.”

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Publication: Applied Sciences
Issue/Year: Applied Sciences, Volume 12; Number 1; Pages 406; 2021
DOI: 10.3390/app12010406

Neural 3D holography

Author(s):

Choi, Suyeon; Gopakumar, Manu; Peng, Yifan; Kim, Jonghyun & Wetzstein, Gordon

Abstract:

“Holographic near-eye displays promise unprecedented capabilities for virtual and augmented reality (VR/AR) systems. The image quality achieved by current holographic displays, however, is limited by the wave propagation models used to simulate the physical optics. We propose a neural network-parameterized plane-to-multiplane wave propagation model that closes the gap between physics and simulation. Our model is automatically trained using camera feedback and it outperforms related techniques in 2D plane-to-plane settings by a large margin. Moreover, it is the first network-parameterized model to naturally extend to 3D settings, enabling high-quality 3D computer-generated holography using a novel phase regularization strategy of the complex-valued wave field. The efficacy of our approach is demonstrated through extensive experimental evaluation with both VR and optical see-through AR display prototypes.”

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Publication: ACM Transactions on Graphics
Issue/Year: ACM Transactions on Graphics, Volume 40; Number 6; Pages 1–12; 2021
DOI: 10.1145/3478513.3480542

Fast 3D Content Update for Wide-Angle Holographic Near-Eye Display

Author(s):

Rafał Kukołowicz; Chlipala, Maksymilian; Martinez-Carranza, Juan; Idicula, Moncy Sajeev & Kozacki, Tomasz

Abstract:

“Near-eye holographic displays are the holy grail of wear-on 3D display devices because they are intended to project realistic wide-angle virtual scenes with parameters matching human vision. One of the key features of a realistic perspective is the ability to move freely around the virtual scene. This can be achieved by addressing the display with wide-angle computer-generated holograms (CGHs) that enable continuous viewpoint change. However, to the best of our knowledge there is no technique able to generate these types of content. Thus, in this work we propose an accurate and non-paraxial hologram update method for wide-angle CGHs that supports continuous viewpoint change around the scene. This method is based on the assumption that with a small change in perspective, two consecutive holograms share overlapping data. This enables reusing the corresponding part of the information from the previous view, eliminating the need to generate an entirely new hologram. Holographic information for the next viewpoint is calculated in two steps: first, a tool approximating the Angular Spectrum Propagation is proposed to generate the hologram data from previous viewpoint; and second, the efficient Phase Added Stereogram algorithm is utilized for generating the missing hologram content. This methodology offers fast and accurate calculations at the same time. Numerical and optical experiments are carried out to support the results of the proposed method.”

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Publication: Applied Sciences
Issue/Year: Applied Sciences, Volume 12; Number 1; Pages 293; 2021
DOI: 10.3390/app12010293

Faster generation of holographic video of 3-D scenes with a Fourier spectrum-based NLUT method

Author(s):

Cao, Hongkun; Jin, Xin; Ai, Lingyu & Kim, Eun-Soo

Abstract:

“In this article, a new type of Fourier spectrum-based novel look-up table (FS-NLUT) method is proposed for the faster generation of holographic video of three-dimensional (3-D) scenes. This proposed FS-NLUT method consists of principal frequency spectrums (PFSs) which are much smaller in size than the principal fringe patterns (PFPs) found in the conventional NLUT-based methods. This difference in size allows for the number of basic algebraic operations in the hologram generation process to be reduced significantly. In addition, the fully one-dimensional (1-D) calculation framework of the proposed method also allows for a significant reduction of overall hologram calculation time. In the experiments, the total number of basic algebraic operations needed for the proposed FS-NLUT method were found to be reduced by 81.23% when compared with that of the conventional 1-D NLUT method. In addition, the hologram calculation times of the proposed method, when implemented in the CPU and the GPU, were also found to be 60% and 66% faster than that of the conventional 1-D NLUT method, respectively. It was also confirmed that the proposed method implemented with two GPUs can generate a holographic video of a test 3-D scene in real-time (>24f/s).”

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Publication: Optics Express
Issue/Year: Optics Express, Volume 29; Number 24; Pages 39738; 2021
DOI: 10.1364/oe.442267

Unfiltered holography: optimizing high diffraction orders without optical filtering for compact holographic displays

Author(s):

Gopakumar, Manu; Kim, Jonghyun; Choi, Suyeon; Peng, Yifan & Wetzstein, Gordon

Abstract:

“Computer-generated holography suffers from high diffraction orders (HDOs) created from pixelated spatial light modulators, which must be optically filtered using bulky optics. Here, we develop an algorithmic framework for optimizing HDOs without optical filtering to enable compact holographic displays. We devise a wave propagation model of HDOs and use it to optimize phase patterns, which allows HDOs to contribute to forming the image instead of creating artifacts. The proposed method significantly outperforms previous algorithms in an unfiltered holographic display prototype.”

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Publication: Optics Letters
Issue/Year: Optics Letters, Volume 46; Number 23; Pages 5822; 2021
DOI: 10.1364/ol.442851

Comparison of state-of-the-art Computer Generated Holography algorithms and a machine learning approach

Author(s):

Madsen, Andreas Erik Gejl; Eriksen, René Lynge & Glückstad, Jesper

Abstract:

“This work studies the use of machine learning and, in particular, a Convolutional Neural Network (CNN) to generate digital holograms and how such a network compares to state-of-the-art iterative methods, both in terms of reconstruction quality and computation time. Since CNNs only require a single pass through the network by a target image to generate a result, and not tens or hundreds of expensive iterations as in the iterative methods, they may be able to accomplish real-time hologram generation; an ability that could open the technology to proper commercial use.

In this work, a CNN built on the UNet architecture, capable of hologram generation, is presented. The network is trained on 4096 images of varying spatial frequencies, both user-generated and from the DIV2K dataset. It is compared to the most common iterative method for hologram generation, namely the Gerchberg–Saxton(GS) algorithm and its modern and improved implementations. In reconstruction quality, the neural network outperforms the original implementation of GS when evaluating Mean Square Error (MSE), geometric error (GE), Structural Similarity Index Measurement (SSIM), and Peak Signal-Noise Ratio (PSNR) of 64 unseen test images. However, on the same test images, the network lacks behind the modern, optimized GS implementations in all error and accuracy measurements. The network does, however, achieve these results at a rate 70–280 times faster than the iterative methods, depending on the particular implementation of the GS algorithm, which corresponds to a possible generation rate of the network of 32 FPS on average.”

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Publication: Optics Communications
Issue/Year: Optics Communications, Pages 127590; 2021
DOI: 10.1016/j.optcom.2021.127590

Acceleration of polygon-based computer-generated holograms using look-up tables and reduction of the table size via principal component analysis

Author(s):

Wang, Fan; Shimobaba, Tomoyoshi; Zhang, Yaping; Kakue, Takashi & Ito, Tomoyoshi

Abstract:

“In this study, we first analyze the fully analytical frequency spectrum solving method based on three-dimensional affine transform. Thus, we establish a new method for combining look-up tables (LUTs) with polygon holography. The proposed method was implemented and proved to be accelerated about twice compared to the existing methods. In addition, principal component analysis was used to compress the LUTs, effectively reducing the required memory without artifacts. Finally, we calculated very complex objects on a graphics processing unit using the proposed method, and the calculation speed was higher than that of existing polygon-based methods.”

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Publication: Optics Express
Issue/Year: Optics Express, Volume 29; Number 22; Pages 35442; 2021
DOI: 10.1364/oe.435966
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