Hologram Depth Modulation for Hardware-Specific 3D Display Accuracy
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Solution Overview
Problem
Existing holographic displays suffer from depth distortion due to differences between assumed and actual hardware specifications, which cannot be corrected when hologram data is generated without original RGB-D input.
Innovation Solution
A method and apparatus using a neural network to modulate hologram depth information based on the actual hardware specification of the display, correcting depth distortion by determining a scale factor and training the neural network to adjust the depth information accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If hologram data is generated based on assumed hardware specifications, then the hologram can be displayed on any device, but depth distortion occurs when the actual hardware differs from the assumed specifications
Solution Approach 1:
The patent modulates depth parameters of the hologram data based on the ratio between actual and assumed hardware specifications. By changing the depth parameter scaling factor, the system adapts pre-generated hologram data to different hardware configurations while maintaining accurate depth perception.
Solution Approach 2:
The patent introduces an intermediary processing step that receives both the hologram data and hardware specification information, then generates corrected hologram data by applying depth modulation based on the hardware ratio. This intermediary process acts as a bridge between fixed hologram data and variable hardware specifications.
2Manufacturing precision
If the hologram depth is adjusted to fit different hardware specifications, then accurate depth display is achieved, but additional processing steps are required
Solution Approach 1:
The patent performs depth modulation as a preliminary processing step before hologram display. By pre-calculating the depth adjustment factor based on hardware specifications and applying it to the hologram data in advance, the system simplifies the overall processing pipeline and avoids complex real-time adjustments during display.
3Manufacturing precision
If multiple pre-trained neural networks are used for different scale factors, then depth correction accuracy is improved, but memory requirements and processing time increase
Solution Approach 1:
The patent employs a single universal neural network that can handle multiple scale factors through pre-training on diverse datasets. This multi-functional approach allows the same network model to correct depth distortions across different hardware configurations without requiring separate specialized networks for each scale factor.
Data Source
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AI summary
A method of modulating a depth of a hologram, the method includes: obtaining hologram data; determining a scale factor based on a hardware specification of a holographic display to display a three-dimensional (3D) hologram image in a space by using the hologram data; and modulating depth information of the hologram data based on the scale factor.