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

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

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.

Compact reconstruction of a Fourier hologram for a 3D object by scaling compensation

The Fourier holographic projection method is compact and computationally fast. However, since the magnification of the displayed image increases with the diffraction distance, this method cannot be used directly to display multi-plane three-dimensional (3D) scenes. We propose a holographic 3D projection method of Fourier holograms by scaling compensation to offset the magnification during optical reconstruction. To achieve a compact system, the proposed method is also used to reconstruct 3D virtual images with Fourier holograms. Different from traditional Fourier holographic displays, images are reconstructed behind a spatial light modulator (SLM) so that the observation position can be placed close to the SLM. The effectiveness of the method and the flexibility of combining it with other methods are confirmed by simulations and experiments. Therefore, our method could have potential applications in the augmented reality (AR) and virtual reality (VR) fields.

Deep hologram converter from low-precision to middle-precision holograms

We propose a deep hologram converter based on deep learning to convert low-precision holograms into middle-precision holograms. The low-precision holograms were calculated using a shorter bit width. It can increase the amount of data packing for single instruction/multiple data in the software approach and the number of calculation circuits in the hardware approach. One small and one large deep neural network (DNN) are investigated. The large DNN exhibited better image quality, whereas the smaller DNN exhibited a faster inference time. Although the study demonstrated the effectiveness of point-cloud hologram calculations, this scheme could be extended to various other hologram calculation algorithms.

Wavefront recording plane-like method for polygon-based holograms

The wavefront recording plane (WRP) method is an algorithm for computer-generated holograms, which has significantly promoted the accelerated computation of point-based holograms. Similarly, in this paper, we propose a WRP-like method for polygon-based holograms. A WRP is placed near the object, and the diffracted fields of all polygons are aggregated in the WRP so that the fields propagating from the polygonal mesh affect only a small region of the plane rather than the full region. Unlike the conventional WRP method used in point-based holograms, the proposed WRP-like method utilizes sparse sampling in the frequency domain to significantly reduce the practical computational kernel size. The proposed WRP-like method and the analytical shading model are used to generate polygon-based holograms of multiple three-dimensional (3D) objects, which are then reproduced to confirm 3D perception. The results indicate that the proposed WRP-like method based on an analytical algorithm is hundreds of times faster than the reference full region sampling case; a hologram with tens of thousands of triangles can be computed in seconds even on a CPU, whereas previous methods required a graphics processing unit to achieve these speeds.

Review of computer-generated hologram algorithms for color dynamic holographic three-dimensional display

Holographic three-dimensional display is an important display technique because it can provide all depth information of a real or virtual scene without any special eyewear. In recent years, with the development of computer and optoelectronic technology, computer-generated holograms have attracted extensive attention and developed as the most promising method to realize holographic display. However, some bottlenecks still restrict the development of computer-generated holograms, such as heavy computation burden, low image quality, and the complicated system of color holographic display. To overcome these problems, numerous algorithms have been investigated with the aim of color dynamic holographic three-dimensional display. In this review, we will explain the essence of various computer-generated hologram algorithms and provide some insights for future research.

Real-valued layer-based hologram calculation

Layer-based hologram calculations generate holograms from RGB and depth images by repeating diffraction calculations using complex Fourier transforms (FTs). Holograms generated as such are suitable for near-eye display and can be easily reconstructed with good image quality, but they are computationally expensive because of multiple complex-valued operations, including complex FTs. In this study, we propose an acceleration method for layer-based hologram calculations by reducing time-consuming complex-valued operations using the real-valued FT and Hartley transform as real linear transformations. Real linear transformations transform real input data to real output data; thus, the proposed method generates amplitude holograms. Thus, we also propose a technique to convert holograms generated by real linear transformations into phase-only holograms using the half-zone plate process and digitalized single-sideband method while maintaining the calculation acceleration. The proposed method can speed up hologram calculations by a factor of around three while maintaining the same image quality as the conventional method.

Three-dimensional deeply generated holography [Invited]

In this paper, we present a noniterative method for 3D computer-generated holography based on deep learning. A convolutional neural network is adapted for directly generating a hologram to reproduce a 3D intensity pattern in a given class. We experimentally demonstrated the proposed method with optical reproductions of multiple layers based on phase-only Fourier holography. Our method is noniterative, but it achieves a reproduction quality comparable with that of iterative methods for a given class.

Two-dimensional angle multiplexing by segmented spherical holography

The crosstalk noise produced in the multiplexing technology of curved computer-generated holograms has caused great damage to reconstructed objects. In order to solve this problem, we propose a method to realize three-dimensional object reconstruction with low crosstalk noise impact. By multiplexing the spherical holograms in the horizontal and vertical directions, the complex amplitudes of the multiple spherical holograms with different curvatures are added to form a composed hologram. The generated hologram records many unrelated scenes of the object. According to the different angles used to generate the hologram, the original object under different viewpoints can be rebuilt, and the multiview multiplexing and reconstruction of three-dimensional objects can be realized. Simulation and optical experiments verify the feasibility of this method.

Three-dimensional visualization of brain tumor progression based accurate segmentation via comparative holographic projection

We propose a new optical method based on comparative holographic projection for visual comparison between two abnormal follow-up magnetic resonance (MR) exams of glioblastoma patients to effectively visualize and assess tumor progression. First, the brain tissue and tumor areas are segmented from the MR exams using the fast marching method (FMM). The FMM approach is implemented on a computed pixel weight matrix based on an automated selection of a set of initialized target points. Thereafter, the associated phase holograms are calculated for the segmented structures based on an adaptive iterative Fourier transform algorithm (AIFTA). Within this approach, a spatial multiplexing is applied to reduce the speckle noise. Furthermore, hologram modulation is performed to represent two different reconstruction schemes. In both schemes, all calculated holograms are superimposed into a single two-dimensional (2D) hologram which is then displayed on a reflective phase-only spatial light modulator (SLM) for optical reconstruction. The optical reconstruction of the first scheme displays a 3D map of the tumor allowing to visualize the volume of the tumor after treatment and at the progression. Whereas, the second scheme displays the follow-up exams in a side-by-side mode highlighting tumor areas, so the assessment of each case can be fast achieved. The proposed system can be used as a valuable tool for interpretation and assessment of the tumor progression with respect to the treatment method providing an improvement in diagnosis and treatment planning.

Improving the quality of full-color holographic three-dimensional displays using depth-related multiple wavefront recording planes with uniform active areas

In this paper, a depth-related uniform multiple wavefront recording plane (UM-WRP) method is proposed for enhancing the image quality of point cloud-based holograms. Conventional multiple WRP methods, based on full-color computer-generated holograms, experience a color uniformity problem caused by intensity distributions. To solve this problem, the proposed method generates depth-related WRPs to enhance color uniformity, thereby accelerating hologram generation using a uniform active area. The aim is to calculate depth-related WRPs with designed active area sizes that then propagate to the hologram. Compared with conventional multiple WRP methods, reconstructed images have significantly improved quality, as confirmed by numerical simulations and optical experiments.

Fast hologram generation using intermediate angular-spectrum method for high-quality compact on-axis holographic display

In the angular-spectrum method-based computer-generated hologram, the zero-padding method is used to convert circular convolution into linear convolution. However, it will increase the calculation time and memory usage significantly. Therefore, a fast and simple method is proposed to solve the issue of the numerical convolution in the process of hologram generation by using the intermediate angular-spectrum method in this paper. Through replacing numerical Fourier transform by optical Fourier transform in the hologram generation, the calculation speed is approximately 6 times faster than that of the zero-padding method. And due to the scaling factors introduced by the Fourier lens and without the cropping operation, the reconstruction quality of the proposed method is improved significantly compared with the zero-padding method. Moreover, the optical reconstruction system is more compact than the 4-f filter system in the on-axis holographic reconstruction. Both numerical simulations and optical experiments have validated the effectiveness of the proposed method.

Novel computer-generated hologram encoding method based on partially temporal coherent light

Partially temporal coherent light (PTCL) has been applied to holographic reconstruction to reduce speckle noise in display systems, while the encoding methods of computer-generated hologram (CGH), based on PTCL, have not been reported. We propose a novel method to encoding CGH, in which a PTCL with a broadband continuous spectrum is used to illuminate the object image. The continuous spectrum is discretized into different wavelengths and a weight value associated with PTCL power spectrum is assigned to each wavelength. The diffractive transmission is based on Fresnel diffraction theory. The phase distribution of the encoded CGH is obtained using the sum of multiplying the different CGH phase distributions of corresponding discrete wavelengths by the corresponding weight values. The modulation results without iteration are performed to verify the feasibility of the proposed method and the iterative algorithm is introduced to improve the quality of the modulation. The reconstructed images from the proposed encoding method exhibit high quality as compared with that obtained from the encoding method based on ideal temporal coherent light. Numerical simulations and optical experiments are good consistent with each other. The proposed method can provide a reference for various wave-front modulations.