Imaging Photometer Color Calibration via Pixel Ratio Matching
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Solution Overview
Problem
Conventional methods for determining color calibration in imaging apparatuses are slow and inefficient, especially when measuring large areas or multiple light sources, and require additional costly components like multiple color filters, which can slow down the measurement process.
Innovation Solution
A method and system that adaptively determine color calibration by creating reference color and luminance scaling calibrations for each color, using a CCD-based imaging photometer with color filters, and calculating pixel ratio values to match reference gray values, allowing for automatic 'on the fly' calibration and conversion of R, G, B values to X, Y, Z values for accurate color measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spot measurements with a spectroradiometer are used to accurately determine color, then measurement precision is improved, but productivity deteriorates due to slow measurement speed
Solution Approach 1:
The patent uses a CCD imaging system to capture an image of the display, creating a visual copy of the entire display area. This image is then processed to extract color information from multiple pixels simultaneously, replacing the need for sequential spot measurements with a single comprehensive image capture that provides color data across the entire display at once.
2Measurement precision
If additional color filters are added to improve camera accuracy, then measurement precision is improved, but device complexity increases and measurement speed decreases
Solution Approach 1:
The patent pre-calculates color calibration matrices using known display characteristics and spectral data before actual measurements are taken. These pre-computed matrices are stored and applied during measurement, eliminating the need for complex real-time filter combinations and allowing accurate color determination with simpler filter configurations.
3Measurement precision
If traditional color calibration methods are used, then color accuracy is improved, but loss of time increases due to sequential measurement requirements
Solution Approach 1:
The patent divides the display into multiple pixels and processes each pixel independently through the color calibration algorithm. This segmentation allows parallel processing of color information from thousands of pixels simultaneously, transforming a sequential calibration process into a parallel operation that maintains accuracy while dramatically reducing total calibration time.
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 approach significantly improves the speed and accuracy of color calibration by using pixel-by-pixel processing with extensive reference color data, reducing the need for additional filters and enhancing measurement efficiency across various spectral light inputs.
Implementation Method 1
A CCD system, for example, can substantially improve the speed and efficiency of testing such displays because a CCD array can include a large number of detectors
Data Source
AI summary
Methods and apparatuses for determining a color calibration for different spectral light inputs in an imaging apparatus measurement are disclosed herein. In one embodiment, for example, a method for determining a color calibration for different spectral light inputs in an imaging apparatus measurement can include creating a reference color calibration and a reference luminance scaling calibration for each of a plurality of colors. The method can also include measuring a reference gray value R, G, B for each color in an image measurement of the light source. The method can further include calculating an R, G, B gray value for a first pixel in each of three filtered image measurements. The method can then include calculating pixel ratio values from each of the three first pixel gray values and comparing the reference gray values to the pixel ratio values to determine which one or more reference gray values are closest to the pixel ratio values. The method further includes calculating X, Y, Z values for the first pixel in the image measurement, and then repeating the steps of the method beginning with calculating an R, G, B gray value for each subsequent pixel in the image measurement.