Holographic Generator Component for Full-Parallax Digital Holograms
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Solution Overview
Problem
Conventional digital holography techniques require significant computational resources and time to generate full-parallax three-dimensional holograms, especially when dealing with large numbers of object points, leading to inefficiencies and potential degradation in image quality.
Innovation Solution
A system and method that downsample a three-dimensional object scene to reduce complexity, generating an intermediate object wavefront recording plane and expanding it using interpolation to create a full-parallax hologram, with the aid of look-up tables and polyphase decomposition to minimize computational operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional digital holography techniques are used to generate full-parallax three-dimensional holograms, then image quality and completeness are maintained, but computational time and resources increase significantly
Solution Approach 1:
The patent divides the three-dimensional object scene into multiple depth layers or slices. Each layer is processed separately to generate corresponding holographic data, which are then combined to form the complete full-parallax hologram. This segmentation reduces the computational complexity of processing the entire scene at once while maintaining image quality.
Solution Approach 2:
The patent performs preliminary processing of the object scene by pre-calculating and storing depth information, object point coordinates, and other parameters before actual hologram generation. Look-up tables are pre-computed to store transformation data that accelerates the subsequent holographic rendering process, significantly reducing real-time computational requirements.
2Measurement precision
If the number of object points in the three-dimensional scene is increased, then hologram resolution and detail are improved, but computational complexity increases
Solution Approach 1:
The patent applies different processing strategies to different regions of the object scene based on their importance and depth. Critical regions with high detail requirements are processed with higher fidelity, while less important areas use optimized or simplified processing. This allows high resolution where needed while reducing overall computational complexity.
Solution Approach 2:
The patent transforms the hologram generation problem from direct spatial domain computation to frequency domain or transformed coordinate systems. By changing the mathematical parameters and representation of the holographic data, complex calculations are simplified into more efficient operations that scale better with the number of object points.
3Productivity
If downsampling is applied to reduce computational load, then processing speed increases, but image resolution may degrade
Solution Approach 1:
The patent transitions from processing in the spatial domain to the frequency domain or depth domain. By transforming the problem into another dimensional space, downsampling operations can be performed more efficiently with less impact on perceived image quality. The transformation allows recovery of high-frequency details through inverse transformations even after aggressive downsampling.
Data Source
AI summary
Techniques for efficiently generating full parallax 3-D holographic images of a 3-D real or synthetic object scene are presented. A holographic generator component (HGC) can receive a real object scene or generate a synthetic object scene. The HGC can downsample the scene by a defined downsampling factor and generate, from the downsampled scene, an intermediate object wavefront recording plane (WRP) that can be placed in close proximity to the scene. The HGC can expand and interpolate the WRP to generate the holographic images. The HGC can decompose a scene into polyphase image components (PICs), generate a WRP for the image components, sum the WRP of the PICs, and expand and interpolate the WRP to generate holographic images of the scene. The HGC can utilize look-up tables to store and use wavefront patterns of each region of an image to facilitate reducing computational operations in generating the holographic images.