Color Coordinate Conversion Using Intermediate PCS and Inverse Matrix
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Solution Overview
Problem
Existing image processing technologies face challenges in performing high-speed, low-storage-capacity color coordinate conversions with high precision, especially for output devices like LCDs with complex optical characteristics, as they require large LUTs and complex processing, which are impractical for devices like printers and displays.
Innovation Solution
An image processing apparatus and method that includes a storage section, predicted output value calculating section, error calculating section, differential coefficient matrix creating section, inverse matrix calculating section, primary-color intensity correction section, and primary-color intensity correction section, allowing for high-precision color coordinate conversion without the need for large-capacity LUTs or complex processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a full-size LUT is used for color coordinate conversion, then conversion precision is improved, but storage capacity requirement increases significantly (to about 50 Mbytes)
Solution Approach 1:
The patent divides the color coordinate conversion process into multiple stages: first converting to a standard color space (PCS), then converting to the target color space. This segmentation allows using smaller lookup tables for each stage rather than one large LUT, reducing total storage requirements while maintaining precision.
Solution Approach 2:
The patent introduces a standard color space (PCS) as an intermediary between the source and target color spaces. This intermediate representation allows using smaller, more manageable lookup tables for each conversion step rather than requiring a single large LUT for the complete transformation.
2Measurement precision
If LUT processing is used for coordinate conversion, then conversion precision is improved, but processing speed decreases due to increased computational complexity
Solution Approach 1:
By segmenting the conversion process into multiple simpler steps through the intermediate PCS space, each step can use faster, less complex lookup tables rather than one large complex LUT, improving overall processing speed while maintaining precision.
Solution Approach 2:
The patent changes the parameter space by introducing the standard color space as an intermediate representation. This parameter transformation allows using smaller lookup tables with simpler conversion algorithms, reducing computational complexity and improving processing speed.
3Measurement precision
If γ-curve or LUT techniques are used for LCD with different γ-values for every RGB, then color accuracy is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal conversion approach using the standard color space (PCS) that can handle different γ-curves for each RGB channel. The same PCS intermediate representation and conversion framework works for all LCD types with different characteristics, simplifying the overall system architecture while maintaining color accuracy.
Solution Approach 2:
The standard color space acts as an intermediary that mediates between different LCD characteristics with different γ-curves. This intermediate representation allows each LCD type to be handled through a unified conversion process, reducing the complexity of dealing with multiple different conversion algorithms.
Data Source
AI summary
The present invention is provided with a storage section that holds characteristic data, a predicted output value calculating section that calculates predicted PCS values (XP, YP, ZP) in a predetermined designated color space, an error calculating section that calculates an error from the difference between the PCS values (X, Y, Z) and the predicted PCS values, a differential coefficient matrix creating section that creates a differential coefficient matrix, an inverse matrix calculating section, a primary-color intensity correction amount calculating section that calculates a corrected primary-color intensity by performing a primary conversion to the difference between the PCS values and the predicted PCS values with an inverse matrix defined as a conversion matrix, and a primary-color intensity correction section that calculates the output primary-color intensity by adding or subtracting to or from a temporal primary-color intensity (IR, IG, IB) the corrected primary-color intensity calculated at the primary-color intensity corrected amount calculating section.