Hologram Calculation Research Articles

Full-color computer-generated holographic near-eye display based on white light illumination.

We propose a full color computer generated holographic near-eye display (NED) based on white light illumination. The method inspired from color rainbow holography is used for calculation of 2D and 3D color holograms. The parameters of the color hologram calculation are designed based on the parameters of the spatial light modulator (SLM) with 4K resolution. A slit type spatial filter is designed in frequency domain to extract red, green and blue frequency components for full color display. A NED system including a white light source, an achromatic collimating lens, a 4K SLM, a 4f optical filtering system, and an achromatic lens as eyepiece is designed and developed. The main contribution of this paper is the first time to apply the rainbow holography concept to the dynamic full color NED with a compact display system. The optical experiments prove the feasibility of the proposed method.

Efficient Computation of Binary-Weighted Computer-Generated Hologram for Gradation Representable Electroholography

Efficient Computation of Binary-Weighted Computer-Generated Hologram for Gradation Representable Electroholography

Efficient Computation of Binary-Weighted Computer-Generated Hologram for Gradation Representable Electroholography

Efficient Computation of Binary-Weighted Computer-Generated Hologram for Gradation Representable Electroholography

Hologram Calculation of Light-in-flight Recording by Holography based on Numerical Simulation Model with FDTD Method

Hologram Calculation of Light-in-flight Recording by Holography based on Numerical Simulation Model with FDTD Method

Hologram Calculation of Light-in-flight Recording by Holography based on Numerical Simulation Model with FDTD Method

Hologram Calculation of Light-in-flight Recording by Holography based on Numerical Simulation Model with FDTD Method

Reducing the memory usage of computer-generated hologram calculation using accurate high-compressed look-up-table method in color 3D holographic display.

In this paper, we propose an accurate high-compressed look-up-table method that uses less memory to generate the hologram. In precomputation, we separate the longitudinal modulation factors and only calculate the basic horizontal and vertical factors. Therefore, we obtain other horizontal and vertical modulation factors of object points by simply shifting the basic horizontal and vertical modulation factors while computing holograms. We perform numerical simulations and optical experiments to verify the proposed method. Numerical simulation results show that the proposed method has the least memory usage, the fastest computation time and no distortion. The optical experimental results are in accord with the numerical simulation results. The proposed method is simple and effective to calculate computer-generated holograms for color dynamic holographic display with high speed, less memory usage and high accuracy that could be applied in the holographic field in the future.

Improving holographic search algorithms using sorted pixel selection.

Traditional search algorithms for computer hologram generation such as Direct Search and Simulated Annealing offer some of the best hologram qualities at convergence when compared to rival approaches. Their slow generation times and high processing power requirements mean, however, that they see little use in performance critical applications. This paper presents the novel sorted pixel selection (SPS) modification for holographic search algorithms that offers mean square error reductions in the range of 14.7-19.2% for the test images used. SPS operates by substituting a weighted search selection procedure for traditional random pixel selection processes. While small, the improvements seen are observed consistently across a wide range of test cases and require limited overhead for implementation.

Foveated computer-generated hologram and its progressive update using triangular mesh scene model for near-eye displays.

We propose a computer-generated hologram technique that reduces latency caused by hologram calculations in holographic near-to-eye displays. The proposed method applies a foveated rendering technique to a triangular mesh-based computer-generated hologram to reduce the computational load while maintaining the perceived image quality. Progressive update from low resolution to high resolution is achieved with minimal computational load by overlaying a new high-resolution occluding mesh patch on a low-resolution mesh model of the scene. The reduced latency for the first hologram generation with low reconstruction resolution and its smooth update to the high-resolution reconstructions using the proposed method was verified by numerical simulations and optical experiments.

Direct calculation of computer-generated holograms in sparse bases.

Computer-generated holography is computationally intensive, making it especially challenging for holographic displays where high-resolutions and video rates are needed. To this end, we propose a technique for directly calculating short-time Fourier transform coefficients without the need for a look-up table. Because point spread functions are sparse in this transform domain, only a small fraction of the coefficients need to be updated, enabling significant speed gains. Twenty-fold accelerations are reported over the reference implementation. This approach generalizes the notion of the phase-added stereogram, allowing for the calculatiion of an arbitrary number of Fourier coefficients per block, enabling high calculation speed with holograms of good visual quality, targeting minimal memory requirements.

Enhanced direct binary search algorithm for binary computer-generated Fresnel holograms

The direct binary search (DBS) algorithm was originally invented for the synthesis of a binary Fourier hologram, and was applied for the generation of a binary Fresnel hologram recently. DBS performs quality evaluation on every pixel. Therefore, both the quality and diffraction efficiency of the generated binary hologram are better among various algorithms of the binary hologram. However, DBS is a time-consuming algorithm and thus is impractical for the generation of high-definition computer-generated holograms. In this paper, we proposed an enhanced DBS (E-DBS) method to speed up the hologram computation. E-DBS is based on the same pixelwise evaluation strategy of DBS, but the diffraction field of a single pixel is precomputed as a lookup table. In evaluating any pixel value, only a small area in the region of interest affected by the diffraction field of single pixel is calculated. In addition, it is also found that qualified results can be obtained by using only 4% of the area of the diffraction field. As a result, the computing complexity of E-DBS can be reduced by at least 2 orders of magnitude in contrast to conventional DBS.

High accuracy beam splitting using spatial light modulator combined with machine learning algorithms

Phase-only spatial light modulators are ideal for the generation of beam splitter profiles to parallelize a variety of laser processes. A novel approach for the calculation of phase holograms is proposed to achieve a highly accurate power distribution over all spots. The Iterative Fourier Transform Algorithm (IFTA) is extended by the use of different machine learning methods, which are trained in an open camera-feedback loop. After the training phase, improvement of the beam splitting accuracy is then validated experimentally. The advantage of the presented approach is shown by comparing it to the standard IFTA algorithm. Finally, use of the approach is demonstrated through metal marking with an ultrashort pulse laser.

Full-scale one-dimensional NLUT method for accelerated generation of holographic videos with the least memory capacity.

A full-scale one-dimensional novel-look-up-table (1-D NLUT) method enabling faster generation of holographic videos with the minimum memory capacity is proposed. Only a pair of half-sized 1-D baseline and depth-compensating principal-fringe-patterns (PFPs) is pre-calculated and stored based on the concentric-symmetry property of the PFP, and from which a set of half-sized 1-D PFPs for all depth planes are generated based on its thin-lens property, which enables minimization of the required memory size down to a few KB regardless of the number of depth planes. Moreover, all those hologram calculations are fully one-dimensionally performed with a set of half-sized 1-D PFPs based on its shift invariance property, which also allows minimization of its overall hologram calculation time. From experiments with test videos, the proposed method has been found to have the shortest hologram calculation time even with the least memory in comparison with several modified versions of the conventional NLUT and LUT methods, which confirms its feasibility.

Special-purpose computer for electroholography in embedded systems

Electroholography is attracting attention as an ideal 3D image presentation method. Developing such methods involves significant computational complexity; thus, they are difficult to realize. Typically, large cluster systems with a control PC and a field-programmable gate array (FPGA) acceleration board are used to reduce hologram calculation time. However such systems cannot be used for embedded 3D systems, such as a head-mounted display. In this study, we developed a compact holographic computer using a Xilinx Zynq UltraScale+ MPSoC with an ARM CPU and an FPGA on a single chip. The proposed system can reproduce a 3D video at 15 frames per second for a spatial light modulator of 1,920 $\times$× 1,080 pixels from an object represented by 6,500 point cloud sources. The proposed system can be embedded in various systems, e.g., head-mounted displays and 3D televisions.

Image quality enhancement via gradient-limited random phase addition in holographic display

The addition of a random phase is widely utilised to diffuse object information in computer-generated hologram calculations. However, different object regions have nonuniform initial information diffusion abilities. The conventional random phase addition method always causes the excessive diffusion of information, especially for high frequency regions, which influences the reconstructed quality. In this paper, a gradient-limited random phase addition method is developed to avoid excessively diffusing object information. Herein, an image is segmented into two regions according to its frequency characteristics. Correspondingly, wide and narrow optimum ranges of a limited random phase are provided for low and high frequency regions, respectively. The numerical simulation results show that the peak signal-to-noise ratio and structural similarity index of reconstructed images increase by approximately 10% and 13%, respectively. The resolution of the reconstructed test image is improved by approximately 2 line pairs. Additionally, using in time-average method reduces the superposition number. Optical experiments are also performed to verify its feasibility.

Computational load reduction by avoiding the recalculation of angular redundancy in computer‐generated holograms

A fast hologram calculation approach is proposed to reduce computational load by avoiding the recalculation of redundancy information. In the proposed method, the hologram is divided into several sub-holograms that record and reconstruct different views of 3D objects. The sub-hologram is generated from its adjacent calculated sub-holograms by only adding the holograms of difference images between an adjacent pair of views. The repetitive information of two adjacent views is called angular redundancy. Therefore, avoiding the recalculation of this angular redundancy can considerably reduce the computational load. Experimental results confirm that the proposed method can reduce the computational time for the statue head, rabbits, and car to 4.73%, 6.67%, and 10.4%, respectively, for uniform intensity, and to 56.34%, 57.9%, and 66.24%, respectively, for 256 levels intensity, when compared to conventional methods.

深度学习算法及其在光学的应用

As an important branch of machine learning, deep learning has reached another climax of machine learning since its inception. Deep learning has excellent performance in many fields such as image recognition and classification, semantic segmentation, and intelligent driving and so on. At the same time, deep learning algorithms are widely used in the field of optics such as computational hologram generation and imaging, non-parameter reconstruction of digital holography, and spectral resonance curves prediction due to their abstract feature recognition and extraction characteristics, strong model building and generalization capabilities. This article detailed the basic principles of deep learning and its typical application research in image classification, super-resolution imaging, computer generated hologram and digital holography, prediction of surface plasmonics resonance curves, and structural design of metasurfaces. And future development of deep learning in the physical optical field was worth exploring.

Real-time layer-based computer-generated hologram calculation for the Fourier transform optical system.

With the growing interest for augmented reality devices, holography is often considered as a promising technology to overcome the focus issues of conventional stereoscopic displays. To enlarge the field of view of holographic head-mounted displays, a Fourier transform optical system (FTOS) has been proposed. However, since the scene geometry is distorted by the FTOS, it is necessary to compensate the position of each scene point during the hologram computation, resulting in long calculation times. In this paper, we propose a real-time computer-generated hologram calculation method for the FTOS. Whereas previously proposed methods used a ray-tracing approach to compensate the distortion induced by the FTOS, our proposed method relies on a layer-based approach. Experimental results show that our method is able to compute holograms of resolution (3840×2160) in real time at 24 frames per second, enabling its use in augmented reality applications.

Fast two-step layer-based method for computer generated hologram using sub-sparse 2D fast Fourier transform.

Fast two-step layer-based and sub-sparse two-dimensional Fast Fourier transform (SS-2DFFT) algorithms are proposed to speed up the calculation of computer-generated holograms. In a layer-based method, each layer image may contain large areas in which the pixel values are zero considering the occlusion effect among the different depth layers. By taking advantage of this feature, the two-step layer-based algorithm only calculates the non-zero image areas of each layer. In addition, the SS-2DFFT method implements two one-dimensional fast Fourier transforms (1DFFT) to compute a 2DFFT without calculating the rows or columns in which the image pixels are all zero. Since the size of the active calculation is reduced, the computational speed is considerably improved. Numerical simulations and optical experiments are performed to confirm these methods. The results show that the total computational time can be reduced by 5 times for a three-dimensional (3D) object of a train, 3.4 times for a 3D object of a castle and 10 times for a 3D object of a statue head when compared with a conventional layer-based method if combining the two proposed methods together.

Accelerated synthesis of wide-viewing angle polygon computer-generated holograms using the interocular affine similarity of three-dimensional scenes.

The interocular affine similarity of three-dimensional scenes is investigated and a novel accelerated reconfiguration algorithm for intermediate-view polygon computer-generated holograms based on interocular affine similarity is proposed. We demonstrate by using the numerical simulations of full-color polygon computer-generation holograms that the proposed intermediate view reconfiguration algorithm is particularly useful for the computation of wide-viewing angle polygon computer-generated holograms.

Accelerating computation of CGH using symmetric compressed look-up-table in color holographic display.

The huge computational complexity is a challenge for computer-generated hologram (CGH) calculation in a holographic display. In this paper, we propose a symmetric compressed look-up-table algorithm to accelerate CGH computation based on the Fresnel diffraction theory and compressed look-up-table algorithm. In offline computation, the memory usage of horizontal and vertical modulation factors is reduced to the order of Kilobytes by using translational symmetric compression and wavelength separation. In online computation, we develop a one-time generation of color holograms method which is accelerated by matrix convolution operation. Numerical simulation results show at least 13 times faster than existing algorithms without sacrificing the computation precision. The optical experiments are performed to demonstrate its feasibility. It is believed that the proposed method is an effective algorithm to accelerate the computation of CGH in color holographic display.