Non-Overlapping Camera View Harmonization for Trailer Imaging
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Solution Overview
Problem
Multi-camera automotive vision systems face challenges in harmonizing images from cameras with non-overlapping fields of view, such as those between a vehicle and its trailer, leading to brightness and color disparities in merged views, which affect the visual quality for the driver.
Innovation Solution
The method involves sampling regions of interest from images captured by cameras at different times as the vehicle travels, using monitored distance to ensure that the same road portion is included in both images, allowing for the determination of correction parameters to harmonize brightness and color, even when cameras do not share an overlapping field of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If images from multiple cameras with non-overlapping fields of view are merged to provide a comprehensive view, then the coverage area is improved, but brightness and color disparities occur between different camera regions
Solution Approach 1:
The system performs preliminary harmonization of brightness and color parameters for each camera's field of view before merging the images. Correction parameters are calculated and applied in advance to each camera's image data, ensuring that when the images are combined, they exhibit uniform appearance characteristics across all regions without requiring overlapping areas for calibration.
Solution Approach 2:
The system dynamically adjusts brightness and color parameters (such as gain, exposure, white balance) for each camera based on calculated correction factors. These parameter changes are applied individually to each camera's image stream, allowing the merged view to maintain consistent visual characteristics across all camera fields of view, regardless of whether they overlap.
2Area of stationary object
If cameras are positioned to cover different areas of the vehicle environment, then the field of view coverage is improved, but the ability to find common reference regions for harmonization deteriorates
Solution Approach 1:
The system extracts and processes each camera's image data independently, calculating harmonization parameters for each camera's specific field of view without requiring identification of common reference regions between cameras. This extraction approach allows each camera to be calibrated and corrected based on its own characteristics, eliminating the need for overlapping areas or common reference detection.
Solution Approach 2:
The harmonization system is designed to work universally with any camera configuration, whether cameras have overlapping or non-overlapping fields of view. The method applies the same correction principle to each camera independently, making the system adaptable to various camera placements and orientations without requiring specific geometric relationships between cameras.
3Device complexity
If each camera operates independently with its own image signal processing chain, then the camera system complexity is reduced, but brightness and color uniformity across merged views deteriorates
Solution Approach 1:
The system implements a feedback mechanism where correction parameters are calculated based on the actual image characteristics from each camera and applied back to adjust the image signal processing. This feedback loop allows independently operating cameras to produce uniformly appearing images in the merged view, as each camera's output is continuously adjusted based on its measured performance.
Solution Approach 2:
The system introduces an intermediary harmonization processing stage between the individual camera image processing chains and the final image merging. This intermediary layer calculates and applies correction parameters to each camera's image data, acting as a mediator that reconciles the differences between independently operating cameras and produces a uniform combined output.
Data Source
AI summary
An image processing method for harmonizing images acquired by a first camera and a second camera connected to a vehicle and arranged in such a way as their fields of view cover a same road space at different times as the vehicle travels along a travel direction is disclosed. The method includes: acquiring by a selected camera, a first image at a first time; selecting a first region of interest bounding a road portion from the first image; sampling the first region of interest; acquiring by the other camera, a second image in such a way that the road portion is included in a second region of interest; sampling the second region of interest; and determining one or more correction parameters for harmonizing images acquired by the first and second cameras, based on a comparison between the image content of the first and second regions of interest.