Camera Sensor Color Correction Using Interpolated Reference Images
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Solution Overview
Problem
Existing color correction methods for camera sensors require specific hardware information and measurements, and are inefficient in providing color correction that accurately mimics human perception, especially in real-time applications.
Innovation Solution
A method involving color interpolation, area of interest determination, average color calculation, and generation of a 3×3 color correction matrix using non-integer equation solvers like APOPT and IPOPT to minimize color differences, enabling real-time color correction for specific camera sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If quantum efficiency spectra measurements and fitting algorithms are used to generate color correction matrix, then color accuracy is improved, but measurement precision and device complexity increase
Solution Approach 1:
The patent pre-defines multiple color correction matrices for different lighting conditions (daylight, incandescent, fluorescent, etc.) and stores them in lookup tables. During real-time operation, the system simply selects and applies the appropriate pre-computed matrix based on detected lighting conditions, avoiding the need for complex real-time measurements and fitting algorithms.
Solution Approach 2:
The patent creates simplified representations of complex color correction data by generating lookup tables that store pre-computed color correction matrices. These lookup tables serve as simplified copies that can be quickly accessed and applied without performing complex calculations, thereby reducing real-time computational complexity while maintaining color accuracy.
2Productivity
If real-time color correction is implemented, then processing speed is improved, but computational complexity increases
Solution Approach 1:
The system pre-computes and stores color correction matrices for various lighting conditions in lookup tables before runtime. During real-time image processing, the system only needs to retrieve the appropriate pre-computed matrix and apply it to the image data, which is computationally efficient and enables real-time processing without complex calculations.
Solution Approach 2:
The patent introduces lookup tables as an intermediary data structure that bridges the gap between complex color correction algorithms and real-time processing requirements. The lookup tables store pre-computed correction data that can be quickly accessed and applied, acting as a mediator that enables real-time performance without requiring complex real-time computations.
3Measurement precision
If camera-specific color correction is implemented, then color accuracy for specific sensors is improved, but adaptability to different camera models decreases
Solution Approach 1:
The patent segments the color correction solution into camera-specific lookup tables, where each camera model has its own dedicated set of pre-computed correction matrices. This segmentation allows each camera model to receive optimized color correction while maintaining a uniform approach across different models. The system can store multiple camera-specific lookup tables and select the appropriate one based on the camera model being used.
Data Source
AI summary
A method for providing color correction for a specific camera sensor includes (i) providing a reference image, wherein the reference image results from a capture of the specific camera sensor, (ii) performing a color interpolation of the reference image to provide an interpolated image, (iii) determining at least one respective area of interest for the colors red, green and blue in the interpolated image, (iv) forming an average of color values in each determined area of interest to obtain a respective resulting average color, (v) assigning a respective reference color to each resulting average color, wherein the reference colors comprise at least the colors red, green and blue, (vi) generating a color correction matrix based on color values of the reference image, (vii) calculating a respective intermediate variable for the colors red, green and blue based on the generated color correction matrix, and (viii) minimizing a respective difference for the colors red, green and blue between the color values of the reference image and the respective intermediate variable calculated to provide the color correction for the specific camera sensor. Further disclosed are a computer program, a device, and a storage medium for this purpose.