Ray-Based Gamut Mapping for ICC Profile Retrieval
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Solution Overview
Problem
Current color management systems face challenges in accurately reproducing out-of-gamut colors across different devices due to the lack of a standardized gamut mapping strategy that can simultaneously satisfy requirements of color, contrast, lightness, chroma, hue, and hue shifts, leading to inconsistencies in image quality and computational time.
Innovation Solution
A novel system and method that uses a ray-based model derived from a seed profile or device to retrieve gamut mapping, optimizing runtime ICC profile creation for performance and computational efficiency by mapping out-of-gamut colors to the host device's gamut, ensuring accurate color reproduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single unique gamut mapping strategy is applied to all color spaces, then device complexity is reduced, but color accuracy and image quality deteriorate because no single strategy can simultaneously satisfy all color requirements across different devices
Solution Approach 1:
The patent implements dynamic gamut mapping by creating device-specific profiles that adapt the mapping strategy to each target device's characteristics. Rather than using a static universal strategy, the system dynamically selects and applies appropriate mapping algorithms based on the specific device being targeted, allowing optimization for each device's color space while maintaining manageable complexity through modular profile creation.
Solution Approach 2:
The patent applies different gamut mapping strategies to different regions of the color space. By creating device-specific profiles that tailor the mapping approach to local color space characteristics and device capabilities, the system achieves high color accuracy for each device without requiring a single complex universal strategy. Each device receives a customized mapping approach suited to its specific requirements.
2Manufacturing precision
If proprietary gamut mapping algorithms are used in customer profiling code, then color performance is optimized for specific devices, but adaptability to new devices and profiles deteriorates
Solution Approach 1:
The patent creates a universal profile creation framework that can generate device-specific profiles for multiple different target devices. The system maintains a library of device profiles and mapping algorithms that can be selectively applied to any device, allowing the same profiling infrastructure to serve multiple devices with different color spaces and capabilities. This universal approach enables both optimized color performance and broad device compatibility.
Solution Approach 2:
The patent pre-creates and stores device profiles and gamut mapping algorithms in a profile database before runtime. By preparing device-specific mapping strategies in advance and storing them as reusable profiles, the system achieves optimized color performance for each device while maintaining adaptability through the pre-prepared profile library. When a new device is encountered, the system can retrieve or generate an appropriate profile without requiring proprietary custom code.
3Manufacturing precision
If gamut mapping is performed during profile creation, then color accuracy is improved, but computational time increases
Solution Approach 1:
The patent performs computationally intensive gamut mapping operations during profile creation rather than at runtime. By pre-calculating and storing the mapping results in device profiles during an offline profiling phase, the system achieves high color accuracy while minimizing runtime computational overhead. The heavy lifting is done in advance when computational resources are more readily available, and the results are cached for rapid retrieval during actual image processing.
Solution Approach 2:
The patent separates the color management process into distinct phases: an offline profile creation phase where complex gamut mapping calculations are performed, and an online runtime phase where pre-computed profiles are applied. This segmentation allows computationally intensive operations to be performed when time is less critical, while runtime operations focus on efficient application of pre-processed data, achieving both color accuracy and speed.
Data Source
AI summary
What is disclosed is a novel system and method for retrieving a gamut mapping for a color device. A ray-based model is derived from a system estimation of either a seed profile or a seed device. The model is hard coded inside a run-time ICC profile creation algorithm. The runtime profile generation code can be optimized for a variety of gamut mapping scenarios. The generated profile is provided to an imaging system wherein out-of-gamut colors are mapped to the color gamut of the host device. The present method provides an accurate way to reproduce colors of images by retrieving the gamut mapping from profiles or from the color device that use destination profiles for rendering images.