Image Sensor Crosstalk Correction via Multi-Light Modeling
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Solution Overview
Problem
Crosstalk between pixels in image sensors, caused by changes in spectral characteristics, leads to deteriorated image quality due to the influence of adjacent pixel signals, particularly in high-integration and auto-focusing image sensors with non-uniform pixel arrays.
Innovation Solution
A method and device for calibrating image sensors by obtaining correction coefficients through multi-light source images, generating modeling data to calculate color-specific correction coefficients, and applying these coefficients to single light source images to correct crosstalk, thereby improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple light sources are used during calibration to obtain accurate color-specific correction coefficients, then crosstalk correction precision is improved, but calibration time and processing complexity increase
Solution Approach 1:
The patent pre-calibrates multiple image sensor modules using multiple light sources to generate comprehensive modeling data that captures crosstalk characteristics across different colors and conditions. This preliminary calibration creates a reusable correction coefficient function that can be applied during actual imaging operations, eliminating the need to repeat multi-light-source calibration for each imaging task.
Solution Approach 2:
The patent creates a mathematical model (copy) of the crosstalk behavior through modeling data generated from multi-light-source calibration. This model represents the complex relationships between light sources, pixels, and crosstalk effects, allowing the system to simulate and correct crosstalk using simplified single-light-source imaging without losing correction accuracy.
2Manufacturing precision
If pixel array integration is increased to improve image sensor performance, then image quality is improved, but crosstalk between adjacent pixels increases
Solution Approach 1:
The patent applies different correction coefficients to different pixels based on their specific locations and characteristics in the pixel array. By generating pixel-specific correction coefficient functions through modeling data, the system tailors the crosstalk correction to each pixel's local environment, accounting for variations in adjacent pixel influences while maintaining overall image quality.
Solution Approach 2:
The patent dynamically adjusts correction coefficients based on detected crosstalk levels and imaging conditions. The system modifies the correction parameters in real-time according to the actual crosstalk situation, allowing optimal correction performance across different scenarios while maintaining high image quality from integrated pixel arrays.
3Reliability
If comprehensive modeling data is collected from multiple image sensor modules to improve correction accuracy, then crosstalk correction reliability is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent creates universal modeling data and correction coefficient functions that can be applied across multiple image sensor modules with the same pixel array configuration. The comprehensive calibration performed on multiple modules generates a generalized model that works for all modules in the system, eliminating the need for separate complex calibration systems for each module while maintaining high correction reliability.
Data Source
AI summary
A method of calibrating an image sensor includes obtaining a plurality of multi-light source images generated from a plurality of image sensor modules, wherein each of the plurality of image sensor modules generates at least three multi-light source images; obtaining, based on the plurality of multi-light source images, a plurality of crosstalk levels and a plurality of color-specific correction coefficients; generating modeling data based on a relationship between a crosstalk level for a first color and the plurality of color-specific correction coefficients; and obtaining, based on a single light source image captured by a first image sensor module and the modeling data, a color-specific correction coefficient for a target pixel of an image sensor, the image sensor being provided in the first image sensor module, and the color-specific correction coefficient being usable for correcting a crosstalk of the target pixel.