Color Space Mapping via Triangular Segmentation
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Solution Overview
Problem
The determination of mappings between different color spaces in printing systems is complex and time-consuming, especially when dealing with large dimensionality of Neugebauer Primary area coverage (NPac) spaces, making manual pre-calculation of lookup tables impractical for printing systems with multiple colorants.
Innovation Solution
A method involving a print controller that selects output color space nodes based on colorimetry and target attributes, using a set of candidate output color space nodes to derive halftone parameters and populate a lookup table, allowing for computational mapping between input and output color spaces, thereby controlling color transitions and attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual pre-calculation of lookup tables is used for color space mapping, then accuracy of color mapping can be ensured, but the process becomes impractical for printing systems with multiple colorants due to complexity and time consumption
Solution Approach 1:
The patent segments the complex color space mapping problem into multiple triangular regions within the color space. By dividing the mapping domain into smaller manageable segments (triangles formed by reference color space nodes), the system can calculate lookup tables for each segment independently, reducing overall computational complexity while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary calculation of lookup tables for triangular regions during system initialization or calibration phase. By pre-calculating the mapping relationships for all possible triangular segments before actual printing operations, the system avoids complex real-time calculations during printing, making the process practical for multi-colorant systems.
2Productivity
If computational mapping methods are used instead of manual pre-calculation, then the process becomes practical for multi-colorant systems, but control over color transitions and visual quality attributes becomes coarser
Solution Approach 1:
The patent applies different mapping strategies to different regions of the color space. By identifying triangular regions with specific characteristics (such as regions containing colorants that should not be overprinted together), the system can apply localized control rules to preserve visual quality attributes in critical areas while maintaining computational efficiency elsewhere.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system evaluates the results of computational mapping and adjusts parameters to maintain color transition quality. By monitoring visual quality attributes and iteratively refining the mapping calculations, the system achieves both computational practicality and precise color control.
3Measurement precision
If reference color space nodes are densely distributed to improve color mapping accuracy, then the mapping precision improves, but the number of nodes and computational burden increases significantly
Solution Approach 1:
The patent uses a relatively small number of reference color space nodes and creates multiple triangular segments by connecting these nodes. This segmentation approach allows the system to achieve comprehensive color space coverage and high mapping precision without requiring a dense distribution of individual nodes, thus reducing the total number of nodes needed.
Solution Approach 2:
The patent transforms the problem from selecting individual color space nodes to selecting triangular regions formed by combinations of nodes. By working with triangular segments (adding a combinatorial dimension), the system achieves more comprehensive color space coverage with fewer base nodes, as each triangle covers a specific volumetric region in the color space.
Data Source
AI summary
Certain examples described herein relate to mapping between an input color space and an output color space. In some cases, data representing a set of candidate output color values in the output color space is obtained for a transition region between two input color values in the input color space. A sub-region of the transition region is defined, the sub-region being associated with a target colorimetry and a target value of a metric. An output color value is selected from the set of candidate output color values. The output value has an associated value of the metric and an associated colorimetry. The selecting is based on the associated colorimetry and the target colorimetry, and the value of the metric and the target value of the metric. In some cases, mapping data is generated by assigning the selected output color value to the sub-region.