Digital holographic stereograms have met expectations in various fields since their introduction. Traditionally, recording large outdoor physical models has required time-consuming and complex processes involving professional tools and technical expertise. This study, however, aims to streamline the process by utilizing simple equipment, such as an iPhone, basic tools, free phone applications, and free software. Four successful experiments were conducted and evaluated using the digital CHIMERA holographic stereogram-printing technique combined with photogrammetry, Gaussian splatting, light detection and ranging (LiDAR), and image interpolation. This approach records large-scale outdoor content more efficiently and effectively. The selected method allows the development and large-scale dissemination of realistic outdoor content holograms to the public. This study demonstrates the feasibility of creating ultra-realistic outdoor holograms using accessible tools and methods, offering potential applications in various fields such as art, education, and entertainment.

Recent advancements in communication technology have catalyzed the widespread adoption of realistic content, with augmented reality (AR) emerging as a pivotal tool for seamlessly inte-grating virtual elements into real-world environments. In construction, architecture, and urban design, the integration of mixed reality (MR) technology enables rapid interior spatial mapping, providing clients with immersive experiences to envision their desires. The rapid advancement of MR devices, or devices that integrate MR capabilities, offers users numerous opportunities for enhanced entertainment experiences. However, to support designers at a high level of expertise, it is crucial to ensure the accuracy and reliability of the data provided by these devices. This study explores the potential of utilizing spatial mapping within various methodologies for surveying architectural interiors. The objective is to identify optimized spatial mapping procedures and determine the most effective applications for their use. Experiments were conducted to evaluate the interior survey performance, using HoloLens 2, iPhone 13 Pro for spatial mapping, and photogrammetry. The findings indicate that HoloLens 2 is most well-suited for the tasks exam-ined in the scope of experiments. Nonetheless, based on the acquired parameters, the author also proposes approaches to apply the other technologies in specific real-world scenarios.

Traditional holographic printing techniques prove inadequate when only input data are available. Therefore, this paper proposes a new artificial-intelligence-based process for generating digital holographic stereograms from a single black-and-white photograph. This method eliminates the need for stereo cameras, photogrammetry, or 3D models. In this approach, a convolutional neural network and deep convolutional neural field model are used for image colorization and a depth-map estimation, respectively. Subsequently, the colored image and depth map are used to generate the multiview images required for creating holographic stereograms. This method efficiently preserves the visual characteristics of the original black-and-white images in the final digital holographic portraits. This provides a new and accessible method for holographic reconstruction using limited data, enabling the generation of 3D holographic content from existing images. Experiments were conducted using black-and-photographs of two historical figures, and highly realistic holograms were obtained successfully. This study has significant implications for cultural preservation, personal archiving, and the generation of life-like holographic images with minimal input data. By bridging the gap between historical photographic sources and modern holographic techniques, our approach opens up new possibilities for memory preservation and visual storytelling.

Traditional holographic printing techniques prove inadequate when only input data is available. Therefore, this paper proposes a new artificial-intelligence-based process for generating digital holographic stereograms from a single black-and-white photograph. This method eliminates the need for stereo cameras, photogrammetry, or 3D models. In this approach, a convolutional neural network and deep convolutional neural field model are used for image colorization and a depth-map estimation, respectively. Subsequently, the colored image and depth map are used to generate the multi-view images required for creating holographic stereograms. This method efficiently preserves the visual characteristics of the original black-and-white images in the final digital holographic portraits. This provides a new and accessible method for holographic reconstruction using limited data, enabling the generation of 3D holographic content from existing images. Experiments were conducted using black-and-photographs of two historical figures and highly realistic holograms were obtained successfully. This study has significant implications for cultural preservation, personal archiving, and the generation of life-like holographic images with minimal input data. By bridging the gap between historical photographic sources and modern holographic techniques, our approach opens up new possibilities for memory preservation and visual storytelling.

This study examines the development of hologram maps that provide a precise, intuitive depiction of underwater topography in a genuine three-dimensional format. It integrates sophisticated holographic methodologies with bathymetric datasets to address the challenges of visualizing intricate marine environments. Most traditional bathymetric mapping techniques rely on two-dimensional representations, which require users to mentally infer depth and spatial relationships. This cognitive burden can lead to misinterpretation, particularly when analyzing complex seafloor structures with subtle variations. Data from the General Bathymetric Chart of the Oceans was used to construct and enhance three-dimensional terrain models within Blender. Holographic representations were generated utilizing the Digital Holographic Stereogram Printing method, which produced two holograms representing the underwater morphology of Monterey Canyon and its terrestrial features. These holograms enhance accuracy and depth perception, fostering a deeper understanding of the canyon’s geological complexities. This pioneering methodology provides a robust technique for scientific studies and suggests novel approaches for public engagement and educational outreach. By integrating bathymetric data with holographic visualization, this study highlights the importance of precise and accessible three-dimensional mapping in advancing oceanographic research, enhancing underwater analysis, and supporting marine science.