Computer-Generated Hologram Processing Using Region of Interest Sub-images
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Solution Overview
Problem
Existing methods for processing computer-generated holograms (CGHs) face challenges in efficiently calculating interference patterns across multiple depth layers, leading to high computational complexity and resource utilization.
Innovation Solution
The method involves dividing depth images into sub-images, identifying regions of interest (ROI) based on object data thresholds, and performing Fourier transforms only on ROI sub-images to generate interference patterns for CGH patches, thereby reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If Fourier transform is performed on all sub-images to generate interference patterns, then complete CGH coverage is achieved, but computational complexity increases significantly
Solution Approach 1:
The patent divides the depth image into multiple sub-images and further identifies ROI regions within each sub-image. This segmentation allows the system to process only relevant portions (ROI) rather than entire sub-images, reducing computational complexity while maintaining CGH generation completeness through selective processing of regions containing object data.
Solution Approach 2:
The patent applies different processing strategies to different regions: ROI regions containing object data undergo Fourier transform processing, while non-ROI regions are skipped. This local quality approach ensures computational resources are concentrated on areas that contribute to CGH generation, resolving the contradiction between completeness and complexity.
2Manufacturing precision
If Fourier transform is performed on all sub-images, then all regions are processed, but resource utilization increases unnecessarily
Solution Approach 1:
The patent extracts and processes only the essential components (ROI regions containing object data) while discarding unnecessary processing of empty or non-informative regions. This extraction principle reduces resource utilization by eliminating redundant Fourier transform operations on sub-images or regions that do not contribute to CGH generation, while maintaining processing completeness for relevant areas.
3Productivity
If ROI determination with threshold is applied, then processing efficiency improves, but some regions with low object data values may be missed
Solution Approach 1:
The patent uses a threshold-based ROI determination that processes only regions exceeding the threshold value, accepting partial processing of low-value regions as a trade-off. This partial action approach improves processing efficiency by avoiding computation on clearly irrelevant regions, while the threshold is set to balance between efficiency gains and maintaining sufficient object data coverage for acceptable CGH quality.
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 computational complexity and resource utilization by focusing processing efforts on regions with object data, enabling more efficient generation of CGHs.
Implementation Method 1
obtaining a plurality of interference patterns of a plurality of computer-generated hologram (CGH) patches in a CGH plane, each CGH patch from among the plurality of CGH patches corresponding to at least one respective sub-image from among the predetermined number of sub-images, by performing a Fourier transform on object data included in the respective sub-image to calculate an interference pattern in the CGH plane corresponding to the respective sub-image
Data Source
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AI summary
A method for processing a three-dimensional holographic image includes obtaining depth images from depth data of a three-dimensional object, dividing each of the depth images into a predetermined number of sub-images, obtaining interference patterns of computer-generated hologram (CGH) patches corresponding to each of the sub-images by performing a Fourier transform to calculate an interference pattern in a CGH plane for object data included in each of the sub-images, and generating a CGH for the three-dimensional object using the obtained interference patterns of the CGH patches.