Point-to-Point Whiteboard Correction for Hyperspectral Imaging
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Solution Overview
Problem
The industry lacks a simple and highly accurate point-to-point whiteboard parameter ratio correction method for each pixel in hyperspectral data, which is essential for maintaining high analysis accuracy, especially for samples with high transmittance like jade or crystal.
Innovation Solution
A method and system for performing point-to-point whiteboard parameter ratio correction of hyperspectral images, involving steps such as capturing hyperspectral data of a test sample and a standard reference whiteboard, selecting an unobstructed area, calculating spectral averages, and applying a whiteboard parameter ratio correction coefficient to correct the hyperspectral data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If two shots are taken to perform whiteboard parameter ratio correction (one for whiteboard, one for sample), then the correction accuracy is improved, but the process complexity and time consumption increase
Solution Approach 1:
The patent combines the whiteboard reference area and sample measurement area into a single shot. The whiteboard contains both a reference area (for calibration) and a sample placement area, allowing simultaneous capture of reference data and sample data in one hyperspectral image, eliminating the need for separate shots while maintaining correction accuracy
Solution Approach 2:
The whiteboard reference area is pre-prepared with known spectral characteristics before sample measurement. The system captures the reference area data first within the same shot, uses it to calculate correction coefficients, then applies these coefficients to the sample data, enabling accurate correction without requiring a separate preliminary whiteboard shot
2Ease of operation
If a single whiteboard shot is taken to simplify the process, then the operation simplicity is improved, but the measurement precision deteriorates due to ignoring pixel-level light source non-uniformity
Solution Approach 1:
The patent segments the whiteboard into multiple regions: a reference area with uniform spectral characteristics and a sample placement area. By capturing both regions in a single shot and processing them differently (reference area for correction coefficient calculation, sample area for analysis), the system achieves both operational simplicity and measurement precision
Solution Approach 2:
The patent applies different processing strategies to different regions of the whiteboard. The reference area undergoes spectral averaging to create correction coefficients, while the sample area uses these coefficients for reflectance calculation. This localized quality approach ensures accurate correction without requiring multiple shots
3Ease of operation
If the whiteboard area for placing samples is contaminated, then the ease of operation is maintained, but the measurement precision and reliability deteriorate
Solution Approach 1:
The patent extracts the reference area from the sample placement area on the whiteboard. The reference area is positioned separately and protected from sample contamination. Even when the sample area is contaminated, the clean reference area provides reliable data for calculating correction coefficients, ensuring measurement reliability while maintaining ease of operation
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 method simplifies the hyperspectral analysis process, increases the accuracy of reflection spectrum calculation, and improves the reliability and repeatability of measurements by avoiding errors caused by equipment stability and contamination.
Implementation Method 1
The spectral analysis ability of hyperspectral imaging technology comes from the spectral information obtained by recording the interaction between light and matter at different wavelengths, which corresponds to the physical and chemical composition of the object
Implementation Method 2
when the incident light falls on a substance, the composition of the substance will absorb, reflect, and scatter the light, thus changing the spectral shape of the reflected (or transmitted) light
Data Source
AI summary
A method for performing point-to-point whiteboard parameter ratio correction on a hyperspectral image includes: capturing hyperspectral data of a standard reference whiteboard in advance as white(x,y,w), and storing the records, then captures hyperspectral data of a sample as sample(x,y,w); then selecting an unobstructed and unshaded whiteboard area within a certain range of the hyperspectral data sample(x,y,w) of the test sample, and labeling the area as Area A; calculating a spectral average of the ROI on the sample image as SA(w); calculating a spectral average of whiteboard data in the same position as the ROI as WA(w); dividing the two spectral averages, and obtaining a correction coefficient alpha(w)=WA(w)./SA(w); multiplying the whiteboard parameter ratio correction coefficient alpha(w) by a sample reflectance image matrix after whiteboard parameter ratio correction to obtain a final hyperspectral reflectance image matrix REFL(x,y,w)=alpha(w).*sample(x,y,w)./white(x,y,w).