Digital Image Subdivision for 3D Modeling Memory Reduction
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Solution Overview
Problem
Existing digital image processing methods face challenges in efficiently processing high-resolution images for 3D modeling due to memory constraints, leading to either reduced image quality or computationally expensive processing.
Innovation Solution
The method involves subdividing digital images into smaller sub-images while maintaining the original spatial resolution, and associating each sub-image with a synthesized recapture camera having synthesized intrinsic and extrinsic parameters. This allows for distortion correction and efficient processing of sub-images, reducing the computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution digital images are used for 3D modeling, then the re-creation accuracy of the 3D model is improved, but the memory consumption and computational cost increase
Solution Approach 1:
The patent divides a high-resolution digital image into multiple lower-resolution sub-images, allowing the original high spatial resolution to be maintained while reducing the memory footprint. Each sub-image contains a portion of the original image data, enabling processing of high-resolution content in manageable segments that fit within available memory constraints.
2Measurement precision
If high-resolution digital images are used for 3D modeling, then the re-creation accuracy of the 3D model is improved, but the computational cost increases
Solution Approach 1:
By segmenting the high-resolution image into multiple sub-images, the patent reduces the computational burden on individual processing units. Each sub-image can be processed independently or in parallel, distributing the computational workload and reducing the peak power requirements while maintaining the ability to reconstruct the full high-resolution 3D model.
Solution Approach 2:
The patent introduces an additional processing dimension by creating multiple sub-images from a single high-resolution image. This dimensional transformation allows the system to process high-resolution data through multiple lower-resolution passes, reducing computational complexity while preserving the information needed for accurate 3D reconstruction.
3Quantity of substance
If digital images are sub-divided into sub-images, then the memory consumption is reduced, but the processing efficiency may be affected
Solution Approach 1:
The patent segments the original image into multiple sub-images that can be processed in parallel, potentially improving overall processing efficiency despite the increased number of processing units. The segmentation enables distributed processing while maintaining manageable memory requirements for each processing unit.
Data Source
AI summary
Digital image processing methods performed by a computer are disclosed. In one example, a digital image captured by a real camera having intrinsic and extrinsic parameters is received. One or more distortion correction transformations are applied to the digital image to generate a distortion-corrected digital image. The distortion-corrected digital image is sub-divided into a plurality of distortion-corrected sub-images. For each distortion-corrected sub-image of the plurality of distortion-corrected sub-images, the distortion-corrected sub-image is associated with a synthesized recapture camera having synthesized intrinsic and extrinsic parameters mapped from the intrinsic and extrinsic parameters of the real camera.