We propose a high-quality, three-dimensional display system based on a simplified light field image acquisition method, and a custom-trained full-connected deep neural network is proposed. The ultimate goal of the proposed system is to acquire and reconstruct the light field images with possibly the most elevated quality from the real-world objects in a general environment. A simplified light field image acquisition method acquires the three-dimensional information of natural objects in a simple way, with high-resolution/high-quality like multicamera-based methods. We trained a full-connected deep neural network model to output desired viewpoints of the object with the same quality. The custom-trained instant neural graphics primitives model with hash encoding output the overall desired viewpoints of the object within the acquired viewing angle in the same quality, based on the input perspectives, according to the pixel density of a display device and lens array specifications within the significantly short processing time. Finally, the elemental image array was rendered through the pixel re-arrangement from the entire viewpoints to visualize the entire field-of-view and re-constructed as a high-quality three-dimensional visualization on the integral imaging display. The system was implemented successfully, and the displayed visualizations and corresponding evaluated results confirmed that the proposed system offers a simple and effective way to acquire light field images from real objects with high-resolution and present high-quality three-dimensional visualization on the integral imaging display system.

We present a novel augmented reality (AR) display system utilizing a holographic optical element (HOE)-based approach, featuring seamless switching between three-dimensional (3D) and two-dimensional (2D) modes through a liquid-crystalline microlens array (LC-MLA). The proposed system aims to capture and present comprehensive spatial information on real-world objects. The LC-MLA is customized to suit the purpose of the proposed system, and its functionality seamlessly switches via an electrical polarizer, allowing users to effortlessly toggle between modes by simply pressing a switch button. An integrated control system automates corresponding tasks based on the selected mode. In 2D mode, the captured image is directly displayed, while in 3D mode, an elemental image array (EIA) is generated and reconstructed into a 3D image, through the LC-MLA. To ensure optimal performance for the proposed system, a custom-fabricated LC-MLA, and full-color HOE combiner have been developed. Additionally, we designed and implemented a bespoke integrated control system that synchronizes and interconnects the main devices seamlessly.

We propose a light-field microscopy display system that provides improved image quality and realistic three-dimensional (3D) measurement information. Our approach acquires both high-resolution two-dimensional (2D) and light-field images of the specimen sequentially. We put forward a matting Laplacian-based depth estimation algorithm to obtain nearly realistic 3D surface data, allowing the calculation of depth data, which is relatively close to the actual surface, and measurement information from the light-field images of specimens. High-reliability area data of the focus measure map and spatial affinity information of the matting Laplacian are used to estimate nearly realistic depths. This process represents a reference value for the light-field microscopy depth range that was not previously available. A 3D model is regenerated by combining the depth data and the high-resolution 2D image. The element image array is rendered through a simplified direction-reversal calculation method, which depends on user interaction from the 3D model and is displayed on the 3D display device. We confirm that the proposed system increases the accuracy of depth estimation and measurement and improves the quality of visualization and 3D display images.

A design and implementation of full-parallax holographic stereogram printer is presented. The holographic stereogram is synthesized using 2D perspective images of the 3D object that are rendered from multiple directions. The perspective images of the 3D scene are firstly captured by a virtual camera and transformed to two-dimensional holographic elements called hogels. The hogels are exposed using the perspective images to form the whole holographic stereogram. After all the hogels are exposed successively, a holographic stereogram can be achieved. Numerical simulation and optical reconstructions are implemented.