Vehicle Surround View Rendering With Edge Region Super-Resolution
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Solution Overview
Problem
Existing methods for displaying a virtual view of a vehicle's surroundings often result in unsharpness and differences in resolution, particularly in edge regions, which can lead to a less clear and realistic view for the user.
Innovation Solution
A method that captures camera images using wide-angle lenses, geometrically corrects them, and increases the resolution in specific partial regions using deep neural networks, thereby reducing unsharpness and enhancing contrast in the displayed virtual view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a wide-angle lens is used to capture the surrounding area, then the field of view is improved, but the resolution and sharpness in edge regions deteriorate
Solution Approach 1:
The patent applies different processing strategies to different regions of the image. Edge regions that suffer from resolution loss due to wide-angle distortion are selectively identified and processed using super-resolution algorithms, while central regions maintain their original quality. This local quality approach ensures that resolution enhancement is applied precisely where needed without unnecessarily processing the entire image.
Solution Approach 2:
The patent performs geometric correction and resolution enhancement as preliminary processing steps before generating the final virtual view. By pre-processing the camera images to correct geometric distortions and enhance resolution in edge regions beforehand, the system prepares optimized input data for the virtual view generation, thereby improving overall image quality without adding complexity to the final rendering process.
2Shape
If geometric correction is applied to the captured camera image, then the distortion is reduced, but the resolution in edge regions decreases
Solution Approach 1:
The patent converts the harmful effect of resolution loss during geometric correction into a beneficial outcome by applying super-resolution algorithms specifically to the affected edge regions. The geometric correction process, which normally causes resolution degradation, is followed by an enhancement step that recovers and improves the resolution in those same regions, effectively turning the distortion correction process into an opportunity for targeted resolution enhancement.
3Area of stationary object
If multiple camera images are captured from different perspectives, then the coverage area is improved, but the complexity of processing and harmonizing resolution differences increases
Solution Approach 1:
The patent segments the processing task by dividing the image into different regions (central and edge regions) and applying appropriate processing to each. This segmentation allows the system to handle multiple camera images more efficiently by focusing computational resources on the problematic edge regions rather than uniformly processing the entire image, thereby reducing overall processing complexity while maintaining comprehensive surroundings coverage.
Data Source
AI summary
A method for displaying a virtual view of the area surrounding a vehicle, in particular a surround view or panoramic view. The method comprises: capturing a camera image of a part of the surroundings using a camera having a wide-angle lens; ascertaining an item of image information dependent on the captured camera image, the captured camera image being geometrically corrected; and displaying the virtual view by projecting the ascertained item of image information onto a virtual projection plane. When ascertaining the item of image information, the resolution of the geometrically corrected camera image is increased in a first partial region.