Bayer Color Filter Array Phase Alignment Detection
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Solution Overview
Problem
Current image sensors with color filter arrays face challenges in determining phase alignment, leading to potential color distortion due to misalignment, which requires manual input and calculation every time the sensor changes or cropping parameters are adjusted.
Innovation Solution
A method to automatically determine the phase alignment of a Bayer color filter array using spatial and spectral analysis, identifying quincunx and rectangular lattices within the array to accurately interpolate color components without manual specification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual phase alignment specification is used, then color distortion can be avoided, but device complexity and operational burden increase
Solution Approach 1:
The system automatically determines CFA phase alignment by analyzing the input image data itself, eliminating the need for manual specification. The processor identifies phase alignment by examining patterns in the sensor array data and automatically configures demosaicking parameters, allowing the system to self-calibrate without user intervention.
Solution Approach 2:
The phase alignment determination is performed before the actual image processing begins. The system analyzes a portion of the input data to establish alignment parameters in advance, which then guide the subsequent demosaicking and color image generation processes, ensuring proper alignment is established beforehand.
2Reliability
If phase alignment is recalculated every time sensor changes or cropping parameters are adjusted, then color accuracy is maintained, but processing time and computational load increase
Solution Approach 1:
The system performs phase alignment determination as a preliminary step before image processing, analyzing input data to establish alignment parameters in advance. This preliminary analysis enables the system to maintain color accuracy while reducing the need for repeated calculations during subsequent processing operations.
Solution Approach 2:
The system uses the input image data as feedback to automatically determine and verify phase alignment. By analyzing patterns in the actual sensor data and comparing them against expected CFA patterns, the system can confirm alignment status and adjust processing parameters accordingly, maintaining accuracy without redundant calculations.
3Ease of manufacture
If CFA is shifted to incorrect phase, then manufacturing tolerance is achieved, but image quality deteriorates due to color distortion
Solution Approach 1:
The system analyzes input image data to detect the actual phase alignment state of the CFA and uses this feedback to automatically adjust processing parameters. By examining patterns in the sensor array and comparing them against expected distributions, the system can identify misalignment and compensate for it through automated parameter adjustment.
Solution Approach 2:
The system automatically modifies processing parameters based on detected phase alignment conditions. By changing demosaicking parameters and color space transformation settings according to the actual CFA phase, the system can compensate for manufacturing variations and maintain image quality despite tolerances in CFA placement.
Data Source
AI summary
In one embodiment of the present invention, a method for determining a phase alignment of a Bayer color filter array is provided. A quincunx lattice of the color filter array corresponding to a first color component is determined from an input frame of image data. Elements of the color filter array corresponding to first and second rectangular lattices of the color filter array are selected. Second and third color components corresponding to elements of the first and second rectangular lattices are determined from the sample values in an input frame of image data.