Enlarging field of view by a two-step method in a near-eye 3D holographic display

Complex amplitude modulated holographic display system based on polarization grating

We propose a holographic display system for complex amplitude modulation (CAM) using a phase-only spatial light modulator (SLM) and two polarization gratings (PG). The two sub-holograms of the complex-amplitude computed generated hologram (CGH) are loaded in different regions of SLM. Two diffractive components couple in space after longitudinal migration from the double PGs, and finally interfered through the line polarizer. The influence of the system error on the reconstructed image quality is analyzed, which provides a theoretical assessment for adding pre-compensation to CGH to compensate the system error. Moreover, on the base of the proposed system, a large depth of field and enlarged display area display is realized and the real-time display can be achieved because of the analytical complex-amplitude computed generated hologram. The optical experimental results show that the proposed system has high energy efficiency, and can provide high-quality holographic display with a large depth of field and enlarged display area.

LED near-eye holographic display with a large non-paraxial hologram generation

In this paper, two solutions are proposed to improve the quality of a large image that is reconstructed in front of the observer in a near-eye holographic display. One of the proposed techniques, to the best of our knowledge, is the first wide-angle solution that successfully uses a non-coherent LED source. It is shown that the resulting image when employing these types of sources has less speckle noise but a resolution comparable to that obtained with coherent light. These results are explained by the developed theory, which also shows that the coherence effect is angle varying. Furthermore, for the used pupil forming display architecture, it is necessary to compute a large virtual nonparaxial hologram. We demonstrate that for this hologram there exists a small support region that has a frequency range capable of encoding information generated by a single point of the object. This small support region is beneficial since it enables to propose a wide-angle rigorous CGH computational method, which allows processing very dense cloud of points that represents three-dimensional objects. This is our second proposed key development. To determine the corresponding support region, the concept of local wavefront spatial curvature is introduced, which is proportional to the tangent line to the local spatial frequency of the spherical wavefront. The proposed analytical solution shows that the size of this area strongly depends on the transverse and longitudinal coordinate of the corresponding object point.

Uniformity improvement of a reconstructed-holographic image in a near-eye display system using off-axis HOE

When a near-eye display (NED) device reproduces an image at a location close to the eye, the virtual image is implemented at a large angle. The uniformity of the image is unbalanced due to the change in diffraction efficiency by the hologram recording angle and angular selectivity. This study proposes a method for implementing an optimal uniform image by analyzing the diffraction efficiency and the reconstructed image was analyzed using angular selectivity generated while reproducing the source point of the diffused image as an intermediate element by holographic optical element (HOE). This research provides practical results for displaying high diffraction efficiency and immersive holographic images in the NED system with HOE as uniformed intermediate elements.

Adjustable and continuous eyebox replication for a holographic Maxwellian near-eye display

A Maxwellian display presents always-focused images to the viewer, alleviating the vergence-accommodation conflict (VAC) in near-eye displays (NEDs). Recently, many methods of improving its limited eyebox have been proposed, among which viewpoint replication has attracted a lot of attention. However, double-image, blind-area, and image-shift effects always happen in typical eyebox-replication Maxwellian NEDs when the eye moves between the replicated viewpoints, which prevents these NEDs from being applied more widely. In this Letter, we propose a method for designing a holographic Maxwellian NED system with continuous eyebox replication as well as flexible interval adjustment by changing the projection angles of the reconstructed images. Thus, holograms corresponding to the positions of different viewpoints are calculated to match the interval of the replicated viewpoints with the human pupil diameter, making it possible to eliminate or alleviate double-image or blind-area effects. Also, seamless viewpoint conversion in the eyebox is achieved by aligning the images of adjacent viewpoints on the retina via hologram pre-processing independently. These effects are verified successfully in optical experiments and have the potential to be applied in near-eye three-dimensional displays without VAC.

Phase dual-resolution networks for a computer-generated hologram

The computer-generated hologram (CGH) is a method for calculating arbitrary optical field interference patterns. Iterative algorithms for CGHs require a built-in trade-off between computation speed and accuracy of the hologram, which restricts the performance of applications. Although the non-iterative algorithm for CGHs is quicker, the hologram accuracy does not meet expectations. We propose a phase dual-resolution network (PDRNet) based on deep learning for generating phase-only holograms with fixed computational complexity. There are no ground-truth holograms employed in the training; instead, the differentiability of the angular spectrum method is used to realize unsupervised training of the convolutional neural network. In the PDRNet algorithm, we optimized the dual-resolution network as the prototype of the hologram generator to enhance the mapping capability. The combination of multi-scale structural similarity (MS-SSIM) and mean square error (MSE) is used as the loss function to generate a high-fidelity hologram. The simulation indicates that the proposed PDRNet can generate high-fidelity 1080P resolution holograms in 57 ms. Experiments in the holographic display show fewer speckles in the reconstructed image.

Holographic near-eye display based on complex amplitude modulation with band-limited zone plates

A holographic near-eye display (NED) system based on complex amplitude modulation (CAM) with band-limited zone plates is proposed. The whole system mainly consists of a phase-only spatial light modulator (SLM), an Abbe-Porter filter system, an eyepiece, and an image combiner. The point source method based on band limited zone plates is used to accurately control the bandwidth of the target complex amplitude. The effects of intensity modulation coefficient γ in the frequency-filtering method on the intensity and the quality of reconstructed images are analyzed, which provide a judgment basis for selecting the appropriate value of γ. We also derive the expressions of the field of view (FOV) and exit pupil of the NED system. Since the holographic image is magnified in two steps in this system, the large FOV can be obtained. The optical experimental results show that the proposed system can provide a dynamic holographic three-dimensional (3D) augmented reality (AR) display with a 23.5° horizontal FOV.

Extending eyebox with tunable viewpoints for see-through near-eye display

The Maxwellian display presents always-focused images to the viewer, alleviating the vergence-accommodation conflict (VAC) in near-eye displays (NEDs). However, the limited eyebox of the typical Maxwellian display prevents it from wider applications. We propose a Maxwellian see-through NED based on a multiplexed holographic optical element (HOE) and polarization gratings (PGs) to extend the eyebox by viewpoint multiplication. The multiplexed HOE functions as multiple convex lenses to form multiple viewpoints, which are copied to different locations by PGs. To mitigate the imaging problem that multiple viewpoints or no viewpoints enter the eye pupil, the viewpoints can be tuned by mechanically moving a PG. We implement our method in a proof-of-concept system. The optical experiments confirm that the proposed display system provides always in-focus images within a 12 mm eyebox in the horizontal direction with a 32.7° diagonal field of view (FOV) and a 16.5 mm eye relief (ERF), and its viewpoints are tunable to match the actual eye pupil size. Compared with other techniques to extend the eyebox of Maxwellian displays, the proposed method shows competitive performances of a large eyebox, adaptability to the eye pupil size, and focus cues within a large depth range.

Aberration correction based on a pre-correction convolutional neural network for light-field displays

Lens aberrations degrade the image quality and limit the viewing angle of light-field displays. In the present study, an approach to aberration reduction based on a pre-correction convolutional neural network (CNN) is demonstrated. The pre-correction CNN is employed to transform the elemental image array (EIA) generated by a virtual camera array into a pre-corrected EIA (PEIA). The pre-correction CNN is built and trained based on the aberrations of the lens array. The resulting PEIA, rather than the EIA, is presented on the liquid crystal display. Via the optical transformation of the lens array, higher quality 3D images are obtained. The validity of the proposed method is confirmed through simulations and optical experiments. A 70-degree viewing angle light field display with the improved image quality is demonstrated.