Color Temperature Adaptive Pixel Interpolation
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Solution Overview
Problem
Current methods for interpolating pixel colors from color and panchromatic channels do not account for the color temperature of a scene, resulting in suboptimal image quality.
Innovation Solution
A method and apparatus that detect the color temperature of a scene and use this information to interpolate pixel colors from Red, Green, Blue, and Clear (RGBC) channels to RGB channels, by converting chromatic and panchromatic pixel values in a specific color space, applying white balance gains, and calculating ratios to scale chrominance channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If color interpolation is performed without considering color temperature, then the processing complexity is reduced, but the image quality deteriorates
Solution Approach 1:
The patent applies preliminary action by detecting the color temperature of the scene before performing color interpolation. The system determines white balance gains based on the detected color temperature and applies these gains to the RGB channels prior to interpolation. This preliminary adjustment ensures that the subsequent interpolation process operates on color-corrected data, thereby improving image quality without significantly increasing processing complexity during the interpolation step itself.
2Manufacturing precision
If color temperature detection and adjustment is implemented, then image quality is improved, but the processing complexity increases
Solution Approach 1:
The patent applies parameter changes by adjusting the white balance gains (R_gain, G_gain, B_gain) based on the detected color temperature. The system calculates specific gain values for each RGB channel according to the color temperature characteristics, then applies these gains to transform the color parameters of the image data. This approach improves image quality by adapting to different lighting conditions while maintaining manageable processing complexity through formula-based parameter adjustment rather than complex iterative optimization.
Data Source
AI summary
Panchromatic pixels and chromatic pixels are interpolated into color channels per pixel of an output image. First, panchromatic pixels and chromatic pixels are used to generate an intermediate image with panchromatic channel, and color channels per pixel. At least three color channels of a first color space can be converted to a first panchromatic light intensity channel in a second color space and at least two first chrominance channels in the second color space based on a detected correlated color temperature. A ratio per pixel between the first panchromatic light intensity channel in the second color space and a second panchromatic light intensity channel in the second color space can be calculated, where the second panchromatic light intensity channel can be based on a panchromatic value per pixel. The ratio can be applied to the at least two first chrominance channels per pixel to determine pixel values in at least two second chrominance channels of the second color space. Channels per pixel can be converted from the second color space including the at least two second chrominance channels and the second panchromatic light intensity channel to a color space.