Imaging Distortion Correction via Location-Based Signal Intensity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Scanning imaging systems face significant challenges in correcting image distortion due to various errors introduced by factors like electromagnetic fields, mechanical imperfections, and environmental changes, which become more pronounced at higher resolutions and when aligning images of different sizes and resolutions, leading to inaccuracies in mosaicking and 3D modeling.
Innovation Solution
The implementation of a method and system that automatically corrects image distortion by determining a correction factor based on the intended location, using a beam emitter and signal detector to associate signal intensity with a corrected substrate location, allowing for the generation of distortion-corrected images. This involves measuring signal intensity at intended locations, determining the actual location, and applying a correction factor to align images accurately across different regions and resolutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scanning imaging systems operate at higher resolutions, then image quality and detail are improved, but image distortion and location accuracy deteriorate due to error accumulation
Solution Approach 1:
The system performs preliminary characterization of distortion patterns by scanning a substrate with known features before actual imaging. Correction factors are pre-calculated for each pixel location based on the measured deviations between intended and actual beam positions. During subsequent high-resolution imaging, these pre-computed correction factors are applied to compensate for distortion, enabling both high resolution and high location accuracy without the errors accumulating at higher magnifications.
2Area of stationary object
If multiple images are mosaicked to cover larger substrate areas, then coverage is improved, but alignment accuracy deteriorates due to distortion variations across different regions
Solution Approach 1:
The system applies different correction factors to different regions of the substrate. Each pixel location has its own specific correction factor derived from local distortion measurements. When mosaicking multiple images, the distortion correction is applied locally to each image based on its specific region, ensuring that alignment accuracy is maintained across the entire large-area substrate coverage rather than using a single global correction.
3Measurement precision
If distortion correction is applied to align images, then alignment accuracy is improved, but system complexity increases due to the need for correction factors and processing
Solution Approach 1:
The system creates a digital model (copy) of the distortion pattern by scanning a substrate with known features. This distortion map is stored as correction factors for each pixel location. During actual imaging, instead of implementing complex real-time mechanical or optical correction mechanisms, the system simply applies the pre-stored correction factors to the image data, achieving high alignment accuracy through straightforward computational processing rather than complex physical systems.
Data Source
Figure 1
Figure 2~3
Figure 4~5
AI summary
Devices, systems and methods relating to a distortion-correcting imaging for collecting image-related data of a substrate are disclosed, comprising: a beam emitter for directing an emission at an intended location on the substrate, and a signal detector for determining a signal intensity value associated with the emission; wherein the signal intensity value is associated with a corrected substrate location, said corrected substrate location determined from the intended substrate location and a correction factor, said correction factor being a function of said intended substrate location.