Wavelength-Encoded Imager Artifact Reduction via Non-Interpretation Regions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wavelength-encoded imaging systems face challenges in distinguishing objects from artifacts, leading to false detections or missed detections due to artifacts in captured images.
Innovation Solution
A method and system that capture two images using on-axis and off-axis light sources, generate a difference image to highlight the object of interest, and use non-interpretation regions to reduce artifacts, employing a controller to process and analyze images and apply thresholds to distinguish the object from artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wavelength-encoded imaging is used to detect objects, then object detection capability is improved, but artifacts from reflected light off other elements increase causing false detections
Solution Approach 1:
The patent segments the image processing into multiple stages: capturing multiple images at different wavelengths, identifying non-interpretation regions separately, and processing interpretation regions differently. This segmentation allows the system to handle artifacts and actual objects through distinct processing paths, improving detection accuracy while reducing false positives from artifacts.
Solution Approach 2:
The patent introduces non-interpretation regions as an intermediary mechanism to identify and exclude artifact-prone areas from final object detection. By creating this intermediate classification layer, the system can filter out artifacts before they contaminate the final detection results, thereby improving reliability without sacrificing detection capability.
2Measurement precision
If multiple images are captured at different wavelengths, then object detection precision is improved, but system complexity increases
Solution Approach 1:
The patent merges multiple wavelength images into a unified processing framework where non-interpretation regions are identified across all wavelengths and applied consistently. By combining the information from multiple wavelengths and applying a unified artifact reduction approach, the system achieves high detection precision while managing complexity through integrated processing rather than separate analysis of each wavelength.
Solution Approach 2:
The patent performs preliminary identification of non-interpretation regions before final object detection. By pre-identifying artifact-prone areas in the multiple wavelength images, the system prepares the data in advance, reducing the computational burden during final detection and simplifying the overall processing complexity while maintaining high precision.
3Reliability
If non-interpretation regions are used to reduce artifacts, then false detections are reduced, but processing time increases
Solution Approach 1:
The patent applies partial action by focusing artifact reduction efforts specifically on non-interpretation regions rather than processing the entire image uniformly. By concentrating computational resources only on the regions where artifacts are most likely to occur, the system achieves effective false detection reduction while minimizing the overall processing time increase.
Solution Approach 2:
The patent implements local quality by applying different processing strategies to different regions of the image. Non-interpretation regions receive artifact reduction processing, while interpretation regions undergo different handling. This localized approach ensures high detection accuracy in critical areas without unnecessarily increasing processing time across the entire image.
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
Effectively reduces artifacts in images, improving the accuracy of object detection by isolating the object of interest and enhancing the system's ability to differentiate between objects and artifacts.
Implementation Method 1
An imager captures light reflecting off an object of interest and generates two or more images of the object
Data Source
AI summary
An imager captures light reflecting off an object of interest and generates two or more images of the object. A controller identifies one or more non-interpretation regions in one of the captured images and uses the non-interpretation regions to reduce a number of artifacts in a final image.