3D Reconstruction Motion Artifact Detection in Scanning Light Fields
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Solution Overview
Problem
Traditional two-dimensional imaging methods face challenges in achieving high resolution due to camera pixel limitations and optical aberrations, while scanning light field systems introduce motion artifacts when capturing dynamic objects, complicating three-dimensional reconstruction and requiring manual intervention for motion artifact removal, which is inefficient and unstable.
Innovation Solution
A self-adaptive motion artifact detection method using multi-view scanning light field images, involving noise reduction, motion compensation, and block-based energy difference analysis to automatically detect and remove motion artifacts, enabling end-to-end processing without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If scanning light field system is used to improve spatial resolution, then manufacturing precision is improved, but motion artifacts are generated affecting reliability
Solution Approach 1:
The patent applies preliminary action by performing motion artifact detection before three-dimensional reconstruction. The system processes multiple light field images, detects motion artifacts in advance using comparison algorithms, and flags affected regions before the reconstruction process begins, preventing artifact propagation to the final 3D model
Solution Approach 2:
The patent introduces an intermediary detection mechanism between image acquisition and reconstruction. This intermediate step compares multiple light field images to identify motion artifacts, serving as a mediator that separates the high-resolution imaging function from the reconstruction function, allowing artifact detection without compromising the scanning resolution
2Measurement precision
If manual intervention is used for motion artifact removal, then detection accuracy is improved, but productivity decreases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically detect and flag motion artifacts without human intervention. The algorithm compares multiple light field images, identifies motion artifacts through computational analysis, and prepares reconstruction data autonomously, eliminating the need for manual review while maintaining detection accuracy
Solution Approach 2:
The patent replaces the mechanical manual inspection process with an automated computational system. Instead of human operators visually examining images for motion artifacts, the system uses algorithmic comparison and analysis of light field data to detect artifacts automatically, substituting human cognitive processes with computational mechanisms
3Reliability
If processing flow is interrupted for manual motion artifact removal, then detection stability is improved, but loss of time increases
Solution Approach 1:
The patent ensures continuity of useful action by maintaining an uninterrupted processing flow from image acquisition through detection to reconstruction preparation. The automated detection algorithm processes images continuously without pausing for manual intervention, keeping the processing pipeline flowing smoothly while maintaining stable artifact detection through consistent algorithmic application
Data Source
AI summary
A self-adaptive motion artifact detection method, and a three-dimensional reconstruction method using the same are provided. The self-adaptive motion artifact detection method includes: acquiring a multi-view rearranged image, decoupling the multi-view rearranged image to obtain a scanning sub-image sequence; dividing each scanning sub-image in the scanning sub-image sequence into blocks; and determining a reference scanning sub-image, and sequentially performing motion artifact detection on individual sub-blocks in the reference scanning sub-image and the sub-blocks in the remaining scanning sub-images.