Subspace Color Transformation Tables for High Throughput
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Solution Overview
Problem
Current color transformation methods face challenges in achieving high throughput and accuracy when converting data from a source color space to a target color space, especially with multi-color printing processes, where the size of transformation tables increases exponentially with the number of inks, leading to coarser gradations and reduced accuracy.
Innovation Solution
The method involves creating and using subspace transformation tables for non-zero color combinations, reducing the number of stored entries by storing redundant subspace tables for each combination, allowing for efficient interpolation and minimizing memory requirements, while ensuring consistency and accuracy across color ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transformation tables are created for all color combinations with the highest possible accuracy, then measurement precision is improved, but device complexity increases exponentially
Solution Approach 1:
The patent divides the complete color transformation table into multiple subspace tables, each handling a specific subset of color combinations. Instead of creating one large table containing all possible color combinations, the system segments the color space into manageable subspaces based on which colors are actually used in each layout object, reducing overall complexity while maintaining accuracy.
Solution Approach 2:
The patent applies different transformation approaches to different regions of color space based on local characteristics. By identifying which colors are non-zero in each layout object and creating subspace tables tailored to those specific color combinations, the system optimizes transformation accuracy for each local region rather than using a uniform approach for all color spaces.
2Device complexity
If transformation tables are reduced to manage size, then device complexity is decreased, but measurement precision deteriorates
Solution Approach 1:
The patent implements a dynamic table selection mechanism that adapts to the specific color combinations present in each layout object. The system determines which subspace table to apply based on the actual non-zero color components in each object, allowing the transformation to dynamically adjust to local requirements rather than using a static fixed table, thereby maintaining precision without requiring the complete table.
Solution Approach 2:
The patent applies partial transformation tables only to the extent necessary for each specific color combination. Instead of always using the complete transformation table, the system uses only the relevant subspace table for the actual colors present in each layout object, reducing complexity while providing sufficient accuracy for the specific task at hand.
3Device complexity
If conventional transformation methods are used, then device complexity is reduced, but productivity decreases due to coarse gradations
Solution Approach 1:
The patent pre-calculates and stores subspace tables for common color combinations during system setup. By preparing these transformation tables in advance for various color scenarios, the system eliminates the need for complex real-time calculations during actual color transformation operations, significantly improving processing speed and throughput while maintaining accuracy.
Data Source
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AI summary
To improve a method for performing color space transformations in such a way as to achieve high throughput in color transformations with the highest possible accuracy despite the use of regular multidimensional tables, while simultaneously maintaining full control over the transformation in each color area, the invention proposes a method for the computer-aided execution of color data transformations for a project from a source color space to a target color space using transformation tables based on a transformation rule. In these tables, a multitude of input color data from the source color space are each assigned unique output values of the target color space. The source color space comprises n colors and the target color space comprises m values. For all input color data of the project, values for the target color space are generated using the transformation tables and provided in a data set.by extracting the corresponding output values from the transformation tables for input color data, characterized by the following features: e) Determining all color combinations of the n colors of the source color space whose color components are not zero; f) Generating and storing a subspace transformation table for each of these color combinations; g) Constructing all proper subsets, including the null set, for each subspace transformation table and generating and storing these as separate, redundant subspace transformation tables; Using the stored subspace transformation tables for the transformation by assigning the corresponding subspace table to each input with its color components of the n colors based on those color components that are not zero.