Reconstructed Color Table Update via Corrective Data
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Solution Overview
Problem
Color management systems face memory constraints due to the increasing size of color tables required for finer sampling and larger bit depths, particularly in devices like printers that need to support multiple color spaces and print media, leading to inefficiencies in firmware memory usage.
Innovation Solution
A method to update a reconstructed color table using corrective data without modifying the underlying Printer Functional Data (PFD) or Bit Assignment Table (BAT), by generating a key from the table, comparing it to a key repository, and applying delta values to correct errors, thus optimizing memory usage without creating multiple versions of firmware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color tables are increased in size for finer sampling and larger bit depths, then color accuracy and device compatibility are improved, but firmware memory usage increases
Solution Approach 1:
The color management system is segmented into multiple components: a base color table stored in firmware, device-specific corrective data stored in non-volatile memory, and a reconstruction process that combines them. This segmentation allows the firmware to remain small while achieving high color accuracy through the combination of base tables and corrective data.
Solution Approach 2:
The system performs preliminary action by pre-calculating and storing corrective data in non-volatile memory before runtime. The corrective data is prepared in advance based on device measurements, allowing the runtime system to simply apply these pre-computed corrections without performing complex calculations, thus reducing firmware requirements while maintaining accuracy.
2Adaptability or versatility
If multiple versions of firmware are created to support different color tables, then device compatibility across different print media is improved, but firmware complexity and update requirements increase
Solution Approach 1:
The base color table in the firmware is designed to be universal and device-independent, working correctly for all devices. Device-specific adaptations are achieved through the corrective data mechanism rather than requiring different firmware versions. This allows a single firmware version to serve multiple device types while maintaining compatibility across different print media.
Solution Approach 2:
Instead of creating multiple firmware versions, the system creates a single base firmware copy and generates device-specific corrective data copies stored in non-volatile memory. Each device receives its corrective data copy tailored to its specific characteristics, eliminating the need for multiple firmware versions while maintaining device compatibility.
3Measurement precision
If color tables are optimized for specific devices, then color accuracy for that device is improved, but the system loses adaptability to other devices and print media
Solution Approach 1:
The base color table acts as an intermediary between device-independent color spaces and device-specific color characteristics. It provides a common reference framework that works for all devices, while the corrective data serves as another intermediary layer that adapts this common framework to specific device characteristics, thus maintaining both accuracy and adaptability.
Solution Approach 2:
The system applies local quality by using a universal base color table with globally applicable color management principles, then overlays device-specific corrective data that addresses local characteristics of individual devices. This allows the majority of the color management to remain general and adaptable while applying specific corrections only where needed for each device.
Data Source
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AI summary
The present application includes devices and methods for using corrective data for a reconstructed table. In some examples, a computing device can generate a key from a reconstructed table, determine corrective data for the reconstructed table based on the generated key, and implement the corrective data to the reconstructed table to generate an updated table.