Image Sensor Calibration Using Inverse White Balance
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Solution Overview
Problem
The existing image sensor calibration methods are inefficient, leading to increased manufacturing time and costs due to excessive calibration delays, particularly when converting non-Bayer signals into Bayer signals for image sensors.
Innovation Solution
The proposed method involves performing a white balance operation and an inverse white balance operation using processing circuitry to convert non-Bayer image data into Bayer image data more quickly, reducing the calibration time by generating third image data corresponding to a Bayer pattern based on a second-type array pattern.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional calibration methods are used to convert non-Bayer signals into Bayer signals, then calibration accuracy can be achieved, but calibration time increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing conversion matrices for different color temperature conditions in advance. During actual calibration, the system only needs to select and apply the pre-computed matrix corresponding to the detected color temperature, rather than performing complex iterative calculations in real-time. This significantly reduces calibration time while maintaining accuracy.
Solution Approach 2:
The patent replaces the conventional iterative mechanical adjustment process with a mathematical matrix transformation approach. By using pre-computed conversion matrices that directly transform non-Bayer signals to Bayer signals based on color temperature characteristics, the system eliminates time-consuming iterative adjustments while preserving calibration precision.
2Reliability
If conventional calibration methods are used, then image sensor performance meets design specifications, but manufacturing costs increase due to extended calibration delays
Solution Approach 1:
The patent pre-computes and stores conversion matrices for various color temperature scenarios before production. During manufacturing calibration, the system rapidly identifies the appropriate pre-computed matrix and applies it, dramatically reducing calibration time and enabling higher production throughput, which directly lowers manufacturing costs while ensuring performance compliance.
Solution Approach 2:
The patent changes the calibration approach from iterative parameter adjustment to direct matrix transformation based on color temperature parameters. By detecting color temperature and selecting the corresponding pre-computed matrix, the system achieves rapid calibration that meets performance specifications while reducing manufacturing time and costs.
3Manufacturing precision
If detailed calibration procedures are performed to ensure image quality, then image sensor performance is optimized, but calibration complexity increases
Solution Approach 1:
The patent pre-calculates conversion matrices for different color temperature conditions and stores them in lookup tables. During calibration, the system simply detects the color temperature and retrieves the corresponding pre-computed matrix, avoiding complex real-time calculations. This maintains image quality optimization while significantly simplifying the calibration procedure.
Solution Approach 2:
The patent replaces complex iterative optimization algorithms with straightforward matrix multiplication operations based on color temperature detection. This substitution maintains manufacturing precision for image quality while dramatically reducing calibration complexity and computational burden.
Data Source
AI summary
A method of calibrating an image sensor including a color filter array having a first-type array pattern, the method includes capturing a target using the image sensor to generate first image data, performing a white balance operation on the first image data to generate second image data, performing an inverse white balance operation on the second image data based on a second-type array pattern to generate third image data, the second-type array pattern being different from the first-type array pattern, and calibrating the image sensor based on the third image data.