Color Transform for Concave Device Gamuts
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Solution Overview
Problem
Color imaging devices with concave gamut surfaces face challenges in maintaining color accuracy and preventing artifacts during gamut mapping, as existing methods can distort in-gamut colors and fail to effectively handle out-of-gamut colors, leading to contour artifacts.
Innovation Solution
A method that forms a convex hull of the device color gamut to create an expanded device model, allowing for the transformation of input device-independent color values into device control signals that fill the convex gamut, thereby reducing the likelihood of image degradations like contouring artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional gamut-mapping methods are used for devices with concave gamut surfaces, then out-of-gamut colors can be mapped, but contour artifacts and image degradations occur
Solution Approach 1:
The color gamut mapping process is segmented into two distinct stages: first mapping to an intermediate convex gamut space, then mapping to the final target gamut. This segmentation allows the harmful concave regions to be eliminated in the intermediate stage, preventing artifact formation while preserving color accuracy in the final stage.
Solution Approach 2:
A convex intermediate gamut is introduced as a mediator between the source and target gamuts. This intermediate convex space serves as a buffer that eliminates the problematic concave regions, allowing smooth color transitions and preventing contour artifacts while maintaining accurate color representation.
2Stability of the object's composition
If hue-preserving gamut mapping is applied to concave gamut regions, then color transitions may be distorted, but maintaining hue is prioritized
Solution Approach 1:
The mapping process is divided into two stages: the first stage to convex gamut handles geometric normalization without strict hue constraints, while the second stage to target gamut optimizes hue preservation. This segmentation allows both smooth transitions and hue consistency to be achieved in their respective optimal stages.
Solution Approach 2:
The mapping parameters are changed between stages: the first stage uses parameters optimized for geometric transformation to convex space, while the second stage uses parameters optimized for hue preservation and color accuracy. This parameter transformation allows both smooth transitions and hue consistency.
Data Source
AI summary
Method for building color transforms for color imaging devices having concave color gamut regions, including forming a device model that relates device control signals for a color imaging device to corresponding device-independent color values in a device-independent color space; forming a device color gamut representing the set of colors in the device-independent color space that are producible by the color imaging device; and forming a convex color gamut by fitting a convex hull to the device color gamut. The method further includes forming an expanded device model that relates device control signals for the color imaging device to expanded device-independent color values in the device-independent color space, such that the expanded device-independent color values fill the convex color gamut; and building a color transform that relates input device-independent color values to corresponding device control signals for the color imaging device using the expanded device model.