Gamut Mapping Compressing Out-of-Gamut Areas to In-Gamut
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Solution Overview
Problem
Existing gamut mapping algorithms suffer from overlapping mapping and halo noise when compressing a large gamut area to a small gamut area, leading to loss of detail in the mapped image.
Innovation Solution
A gamut mapping method that acquires the first coordinate value of a target pixel in the Lab color space, determines its hue plane, and maps it to a small gamut area by using reference points and adjusting coefficients to avoid overlapping, transforming coordinates through XYZ tristimulus values and RGB optical values to achieve accurate mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If gamut points outside the small gamut area are mapped to the border of the small gamut area using a minimum chromatic aberration method, then the mapping process is simplified, but overlapping mapping occurs and halo noise phenomenon appears
Solution Approach 1:
The patent segments the gamut mapping process into distinct regions: in-gamut points are mapped directly without compression, while out-of-gamut points are compressed toward the border. This segmentation eliminates overlapping mapping by applying different mapping strategies to different regions, thereby resolving the halo noise phenomenon while maintaining manageable process complexity.
Solution Approach 2:
The patent applies different mapping qualities to different regions: in-gamut points retain their original coordinates with full precision, while out-of-gamut points undergo compression. This local quality approach ensures high mapping precision for visible regions while managing the overall mapping process, preventing both overlapping and halo noise.
2Productivity
If gamut points outside the small gamut area are mapped to the border of the small gamut area, then the gamut compression is achieved, but detail level of the mapped image is lost
Solution Approach 1:
The patent applies partial compression action: only out-of-gamut points are compressed toward the border, while in-gamut points remain unchanged. This partial action achieves necessary gamut compression for display compatibility while preserving image detail information in the in-gamut region, avoiding excessive compression that would cause detail loss and halo noise.
Data Source
AI summary
The present disclosure provides a gamut mapping method including acquiring a first coordinate value of a target pixel point P in a Lab color space according to digital values of the target pixel point P in a large gamut area; determining a hue plane in which the target pixel point P is located, and determining (H, C, L) of the target pixel point P; mapping the target pixel point P to the small gamut area to acquire a second coordinate value of a mapped pixel point P1 in the Lab color space; and acquiring mapped digital values of the mapped pixel point P1 in the small gamut area.


