Color Processing Apparatus Chromaticity Lookup Table Precision
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Solution Overview
Problem
Current color transformation methods, such as those using matrix operations or lookup tables, face challenges in achieving high precision for device-dependent RGB values conversion to device-independent XYZ values, particularly in maintaining color accuracy across the visible light spectrum.
Innovation Solution
A color processing apparatus and method that calculates first chromaticity data from device-dependent RGB values, transforms it using a lookup table to obtain second chromaticity data, and then calculates device-independent XYZ values by referencing a correction coefficient derived from spectral sensitivity characteristics, ensuring accurate color reproducibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a matrix operation is used to transform device RGB values to XYZ values, then the transformation process is simple and fast, but the color transformation precision particularly for high chroma colors is not achieved
Solution Approach 1:
The invention segments the color transformation process into two distinct stages: first transforming device RGB values to chromaticity values (using a simplified matrix operation for speed), then transforming chromaticity values to XYZ values (using a correction coefficient for precision). This segmentation allows each stage to be optimized independently, resolving the contradiction between speed and precision.
Solution Approach 2:
The invention introduces chromaticity values as an intermediary between device RGB values and XYZ values. This intermediate representation enables the use of a correction coefficient that accounts for spectral sensitivity characteristics, thereby improving precision while maintaining computational efficiency through the two-stage transformation process.
2Measurement precision
If a lookup table computation is used to transform device RGB values to XYZ values, then high precision color transformation is achieved, but the calculation complexity and processing time increase
Solution Approach 1:
The lookup table approach is segmented into two parts: a chromaticity lookup table for rapid RGB-to-chromaticity transformation, and a separate correction coefficient application for chromaticity-to-XYZ transformation. This reduces the overall complexity compared to a single comprehensive lookup table while maintaining high precision.
Solution Approach 2:
The invention changes the transformation parameters by using chromaticity values (which are normalized and bounded) as an intermediate step. This parameter transformation allows for more efficient lookup table design and reduces the complexity of the overall transformation process while maintaining accuracy.
3Ease of manufacture
If the spectral sensitivity characteristics of the image input device do not match visual spectral characteristics, then the device RGB values are easy to obtain, but the color accuracy and reproducibility deteriorate
Solution Approach 1:
The invention uses chromaticity values as an intermediary that decouples the device-specific RGB measurements from the standard XYZ color space. The correction coefficient, derived from spectral sensitivity characteristics, acts as a mediator that compensates for mismatches between device characteristics and visual spectral characteristics, thereby maintaining color accuracy.
Solution Approach 2:
The invention transforms the RGB values through chromaticity parameters before converting to XYZ values. This parameter transformation allows the system to account for spectral sensitivity mismatches through the correction coefficient, improving color accuracy while preserving the ease of obtaining device RGB values.
Data Source
AI summary
An input chromaticity data calculation unit 113 calculates input chromaticity data rg from device-dependent color data RGB. A chromaticity data transformation unit 114 transforms the input chromaticity data rg into output chromaticity data xy by referring to an LUT stored by an LUT storage unit 13. A total amount calculation unit 115 refers to the LUT of the LUT storage unit 13 to calculate a total amount Σ′XYZ of the device-independent color data XYZ from the color data RGB. An output color data calculation unit 116 uses the total amount Σ′XYZ to calculate color data XYZ from the output chromaticity data xy.