Multi-Camera Color Matching Master-Slave Gain Adjustment
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Solution Overview
Problem
In multiple-camera surround view systems for vehicles, existing technologies face challenges in accurately matching colors and brightness across different cameras, leading to distracting and ineffective video displays when stitching images together, due to variations in camera configurations and environmental conditions.
Innovation Solution
A method and system for color and brightness matching in multiple-camera systems, where one camera is designated as a 'Master' to adjust the other cameras' settings based on overlapping regions of interest, using RGB color model analysis and iterative gain factor calculations to minimize color errors, ensuring consistent image presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple cameras with different configurations are used to capture surround view images, then the field of view and coverage are improved, but color and brightness matching between cameras deteriorates
Solution Approach 1:
The system changes parameters (gain factors for RGB channels) of slave cameras to match the master camera's color and brightness characteristics. By iteratively adjusting these parameters based on overlapping region comparisons, the system resolves the color/brightness mismatch caused by using multiple cameras with different configurations.
Solution Approach 2:
The system copies the color and brightness characteristics of the master camera to the slave cameras. By designating one camera as master and adjusting others to match its properties, the system creates visual consistency across all camera feeds while maintaining the benefits of multiple camera perspectives.
2Measurement precision
If cameras are adjusted to match colors using traditional methods, then color accuracy in non-overlapping regions may be improved, but the overall homogeneity of the stitched image deteriorates
Solution Approach 1:
The system applies different adjustment strategies to different regions: in overlapping regions, it prioritizes matching the slave camera to the master camera to ensure homogeneity; in non-overlapping regions, it maintains the original camera characteristics. This local differentiation resolves the contradiction between color accuracy and overall image homogeneity.
3Manufacturing precision
If iterative gain factor calculations are performed for all cameras, then color matching precision is improved, but processing time and computational complexity increase
Solution Approach 1:
The system segments the camera network into a master camera and multiple slave cameras. Only slave cameras undergo iterative gain factor calculations to match the master, reducing the computational burden compared to adjusting all cameras. This segmentation maintains color matching precision while significantly reducing processing time.
Solution Approach 2:
The system performs partial adjustment by only modifying slave cameras to match the master, rather than adjusting all cameras equally. This partial action achieves sufficient color matching precision for the surround view application without the excessive computational cost of adjusting every camera in the system.
Data Source
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AI summary
Systems and methods for adjusting color and brightness in multi-camera systems are disclosed. The system uses four cameras, having overlapping fields of view, mounted on the four sides of a vehicle. Color errors are determined for areas where the images from the rear and side cameras' fields of view overlap. Color gain factors are determined and applied for each of the side cameras (using the rear camera as "master") to match the colors of the video outputs from the side cameras and the rear camera. The gains for the front view camera are then adjusted using gain factors based on the matched video outputs from the side view cameras using the side cameras as the "master" to the front camera "slave." In this way, the rear camera indirectly acts as the master for the front camera and all cameras are ultimately color-matched to the rear camera.