Imager Calibration via Importance-Weighted Color Modeling
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Solution Overview
Problem
Digital imaging devices face challenges in accurately capturing colors due to manufacturing variations and differences in color output signals, requiring costly and labor-intensive calibration processes that are not easily automatable, especially in limited resource environments.
Innovation Solution
A digital imaging device and method that uses a precharacterized 'golden' imager for calibration, modeling responses to predefined color samples with importance weightings, and applying a multilinear Taylor series expansion to compute a target imager calibration efficiently, eliminating the need for specialized calibration targets or spectrophotometers and enabling automatic implementation within the device's hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods using spectrophotometers and physical color samples are used, then color measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses a virtual color space model (copy of color relationships) instead of physical color samples and spectrophotometers. The system creates a mathematical representation of color space that can be transformed and applied to calibration, eliminating the need for expensive physical measurement devices while maintaining color accuracy.
Solution Approach 2:
The patent replaces the mechanical/physical calibration system (spectrophotometers, physical color charts) with a computational/mathematical system. Using color space transformations and algorithms, the system performs calibration through software calculations rather than physical measurement devices, reducing hardware complexity.
2Measurement precision
If traditional manual calibration processes are used, then color accuracy is improved, but productivity and automation capability worsen
Solution Approach 1:
The calibration system performs self-calibration automatically using its own imager and computational algorithms. The system doesn't require external manual intervention or specialized equipment - it uses internal resources to calibrate itself, enabling automated operation and improving productivity while maintaining accuracy.
Solution Approach 2:
The patent pre-calculates and stores transformation matrices and color space parameters in advance. These pre-computed data structures enable rapid automated calibration without requiring manual measurement during the actual calibration process, significantly improving productivity while preserving color accuracy.
3Measurement precision
If computationally intensive calibration algorithms are used, then color accuracy is improved, but use of energy and processing resources worsen
Solution Approach 1:
The patent applies partial action by using pre-computed transformation matrices for common color spaces and only performing full computational calibration when necessary. The system uses lookup tables and pre-calculated parameters for routine operations, reducing energy consumption while maintaining color accuracy through selective application of computational intensity.
Data Source
AI summary
Calibration of a target imager. Responses of the target imager and a reference imager to predetermined importance-weighted color sample data are modeled using a predetermined target and reference imaging attributes. A calibration for the target imager is determined using the modeled responses and a predetermined calibration for the reference imager.