Polynomial Smoothing for Device-Dependent Color Space Gamut Preservation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing colorimetric data correction methods in device-dependent color spaces, such as RGB or CMYK, often reduce the color reproduction range and alter the shape of the gamut surface, leading to degraded gradation and accuracy in color prediction due to variations in colorimeters and patch colors.
Innovation Solution
A smoothing method that calculates polynomial approximation coefficients to smooth color values of multiple grid points in a device-dependent color space, using these coefficients in a polynomial approximation equation to reduce variations and maintain the shape of the gamut surface, enabling smooth gradation expression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If colorimetric data correction is executed using averaging methods, then gradation smoothness is improved, but color reproduction range is reduced and gamut surface shape is altered
Solution Approach 1:
The patent changes the correction parameter from simple averaging to polynomial approximation of order n≥2. This parameter change allows the correction to consider higher-order relationships between grid points, maintaining gradation smoothness while preserving the gamut surface shape and color reproduction range by fitting a polynomial curve that better represents the underlying color data distribution.
Solution Approach 2:
The patent introduces dynamic adaptation by calculating polynomial approximation coefficients specific to each grid point's local neighborhood. Instead of applying a static averaging correction, the system dynamically adjusts the correction based on the local color data characteristics, allowing different regions of the color space to be corrected with appropriate polynomial orders that preserve their specific gamut features.
2Manufacturing precision
If colorimetric data correction is executed using averaging methods, then gradation smoothness is improved, but gamut surface shape is altered
Solution Approach 1:
The patent changes the correction parameter from simple averaging to polynomial approximation of order n≥2. This parameter change allows the correction to consider higher-order relationships between grid points, maintaining gradation smoothness while preserving the gamut surface shape by fitting a polynomial curve that better represents the underlying color data distribution and its spatial variations.
Solution Approach 2:
The patent applies local quality by performing polynomial approximation on a local neighborhood around each grid point rather than applying a global averaging correction. This allows the correction to adapt to local variations in the gamut surface shape, preserving local geometric features while still achieving gradation smoothness through the polynomial fitting process.
3Manufacturing precision
If polynomial approximation coefficients are calculated for surface grid points, then gradation smoothness is maintained, but computational complexity increases
Solution Approach 1:
The patent segments the color space correction task by applying polynomial approximation separately to different directions (first processing direction and second processing direction) and to different grid point locations (surface grid points versus internal grid points). This segmentation allows the complex 4D color space correction to be broken down into manageable sequential steps, reducing the computational complexity of each individual polynomial calculation while maintaining overall gradation smoothness.
Solution Approach 2:
The patent introduces dynamic adaptation by calculating polynomial approximation coefficients specific to each grid point's local neighborhood and processing direction. Instead of applying a static global correction, the system dynamically adjusts the polynomial parameters based on local color data characteristics, allowing different regions to be corrected with appropriate polynomial orders that balance accuracy and computational efficiency.
Data Source
AI summary
A smoothing method of smoothing color values associated with a plurality of grid points that are arranged in a device-dependent color space and include a plurality of surface grid points arranged on a surface of a grid point region in which the plurality of grid points is arranged in the device-dependent color space includes calculating polynomial approximation coefficients to be used in a polynomial approximation equation for calculating approximate values of color values corresponding to positions in a first processing direction in the device-dependent color space for a plurality of first target grid points that are among the surface grid points and arranged in the first processing direction in the device-dependent color space, and smoothing color values associated with the first target grid points using the polynomial approximation equation when the color values associated with the first target grid points are to be smoothed.