Gamut Boundary Triangles Filtering for Color Accuracy
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Solution Overview
Problem
Existing gamut boundary descriptors (GBDs) for color devices, represented as closed surfaces in 3D color space, often lead to inaccurate results due to non-convex gamut shapes and overestimation of features, particularly in devices like CRTs and printers, where convex hull representations fail to accurately depict the gamut boundaries.
Innovation Solution
The approach involves determining boundary line elements by filtering gamut boundary triangles that are unlikely to yield useful results based on the type of gamut operation and color input value, using techniques such as filtering triangles that do not intersect an upward ray or lie within specific half-spaces, and calculating intersection points with geometrical consistency using integer values and dot products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If convex hull representation is used for gamut boundary, then geometric depiction matches intuitive visualization and provides unique intersection point, but accuracy deteriorates for non-convex gamuts and overestimates features
Solution Approach 1:
The gamut boundary is segmented into multiple triangular facets instead of using a single convex hull surface. Each triangle represents a local planar approximation of the gamut boundary, allowing the overall surface to accurately represent non-convex shapes while maintaining simple intersection calculations for each individual triangle.
Solution Approach 2:
Different regions of the gamut boundary are represented with locally appropriate triangular facets that capture the specific geometric characteristics of each region. This allows accurate representation of non-convex features in certain areas while maintaining computational efficiency through localized planar intersections.
2Reliability
If all gamut boundary triangles are processed for every operation, then completeness is ensured, but computational efficiency deteriorates
Solution Approach 1:
Triangles are pre-filtered based on their spatial relationship to the query point and operation type before detailed processing. Triangles that cannot possibly contribute to the result (e.g., those not intersecting the relevant ray or plane) are identified and excluded in advance, ensuring only necessary triangles are processed while maintaining completeness.
Solution Approach 2:
The method processes only the subset of triangles that are relevant to the specific operation and input value, rather than processing all triangles. This partial action approach maintains reliability by including all potentially relevant triangles while excluding those that cannot contribute, thereby improving efficiency without sacrificing completeness.
Data Source
AI summary
The present invention provides for a performing a type of gamut operation for a color device given a color input value, the color device being characterized by a gamut boundary comprising a collection of gamut boundary triangles. Boundary line elements are determined that correspond to a subset of the collection of gamut boundary triangles. The subset of the collection of gamut boundary triangles does not include gamut boundary triangles which are unlikely to yield useful results based on the type of gamut operation and the color input value. Each boundary line element represents a line segment defined by an intersection of one of the gamut boundary triangles within the subset of the collection of gamut boundary triangles with a hue plane, and the hue plane is within the gamut boundary and based on the color input value. In addition, a result is determined for the gamut operation using one or more of the determined boundary line elements. Accordingly, a type of gamut operation is performed using a descriptor which represents the gamut boundary of the color device.