Computer Generated Hologram Hogel Processing
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Solution Overview
Problem
Current computer-generated hologram (CGH) techniques, such as coherent ray tracing and Diffraction Specific algorithms, face high computational loads that hinder the production of rapidly updateable 3D images with adequate resolution, making them unsuitable for dynamic 3D image production using acceptable computing power.
Innovation Solution
A method that divides the CGH into hogels, using a pre-computed diffraction look-up table with phase entries for each image point, reducing the computational load by allowing depth quantization and parallel processing, and employing sparse Fast Fourier Transforms to minimize the size and complexity of the look-up table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If coherent ray tracing (CRT) techniques are used to calculate CGH, then image resolution and field of view are improved, but computational load increases extremely high
Solution Approach 1:
The patent divides the CGH into one or more hogels (holographic elements), where each hogel can be processed independently. This segmentation allows parallel processing and reduces the computational burden on each processing unit while maintaining overall image resolution.
Solution Approach 2:
The patent employs pre-computed diffraction look-up tables that store diffraction phase information for various image points. By pre-calculating and storing this information, the system avoids performing complex diffraction calculations in real-time, significantly reducing computational load during CGH generation.
2Loss of time
If Diffraction Specific (DS) algorithm is used to calculate CGH, then processing time is reduced compared to CRT, but computational load remains too high for dynamic 3D image production
Solution Approach 1:
The patent pre-computes diffraction phase information and stores it in look-up tables, eliminating the need for complex real-time diffraction calculations. This preliminary action reduces both processing time and computational load, enabling dynamic 3D image production.
Solution Approach 2:
The patent extracts only the essential diffraction phase information needed for CGH generation and stores it in compact look-up tables. By taking out only the necessary information rather than performing complete diffraction calculations, the system reduces computational load while maintaining image quality.
3Measurement precision
If more nodes are stored in the diffraction look up table to improve image resolution, then image quality is improved, but computing power requirements increase
Solution Approach 1:
The patent applies different levels of detail to different regions of the hologram by dividing it into hogels. Each hogel can be optimized independently, allowing high resolution where needed while using fewer resources in less critical areas, thus balancing image quality with computational resource requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces the computational load, enabling faster generation of CGHs with smaller look-up tables, allowing for more flexible and efficient dynamic 3D image production while maintaining image quality, and reducing the need for extensive computational resources.
Implementation Method 1
calculating diffraction fringe information for at least one of the hogels
Implementation Method 2
employing sparse Fast Fourier Transforms to minimize the size and complexity of the look-up table
Data Source
Figure 1~2B
Figure 3~4
Figure 5~6
AI summary
A three dimensional display apparatus includes a diffraction panel for displaying a computer generated hologram and a look-up table. The look-up table includes a plurality of phase entries corresponding to a plurality of image points within a three dimensional image replay volume of the computer generated hologram. The apparatus further includes one or more processors configured to notionally divide the computer generated hologram into one or more hogels and to calculate diffraction fringe information for at least one of the hogels based on a selection of the phase entries.