Vehicle Surround View Imaging Using Motion-Based Distortion Correction
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Solution Overview
Problem
Fisheye cameras in vehicles capture images with radial distortion, leading to low-quality outer regions and increased processing complexity, which can result in inaccurate object detection and potential vehicle damage during maneuvers like parking.
Innovation Solution
A system that captures two temporally distinct images using vehicle motion parameters to correct radial distortions by identifying undistorted slices in each image and replacing distorted regions, composing a high-quality corrected image for display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If fisheye cameras are used to cover a larger field of view, then the field of view is increased, but the outer regions of the captured images become radially distorted and produce low quality
Solution Approach 1:
The patent divides the captured image into multiple regions (outer region, middle region, inner region) with different distortion characteristics. Each region is processed separately using appropriate correction techniques. The outer region uses blending of multiple images to overcome radial distortion, while the inner region maintains original high-quality pixels, thus resolving the contradiction between wide field of view and image quality.
Solution Approach 2:
The patent combines multiple captured images through blending operations to create a single high-quality corrected image. By merging information from multiple images and using motion parameters to guide the blending process, the system recovers quality in distorted outer regions while maintaining the wide field of view advantage of fisheye cameras.
2Manufacturing precision
If image correction is applied to remove radial distortion, then image quality is improved, but processing complexity increases
Solution Approach 1:
The patent applies different processing strategies to different regions of the image based on their specific characteristics. The outer distorted regions receive correction and blending processing, while the inner high-quality regions are preserved without processing. This localized approach improves overall image quality while minimizing unnecessary processing complexity.
Solution Approach 2:
The system captures multiple images in advance with the fisheye camera before correction is needed. By having multiple pre-captured images available and using motion parameters to select and blend appropriate regions, the system performs correction more efficiently than attempting to correct a single image, reducing processing complexity while maintaining quality.
3Manufacturing precision
If multiple images are captured and processed to correct distortion, then image quality is improved, but the time required for processing increases
Solution Approach 1:
The patent applies correction and blending operations only to the outer distorted regions of the image rather than processing the entire image uniformly. By limiting processing to only the areas that need correction while preserving the already high-quality inner regions, the system reduces processing time while still improving overall image quality.
Solution Approach 2:
The system uses motion parameters (such as vehicle movement data) to dynamically control the image blending and correction process. By leveraging these parameters to identify which regions need correction and how to blend images, the system optimizes processing efficiency and reduces the time required to produce the corrected image.
Data Source
AI summary
The present disclosure relates to a method and system for displaying surround view in a vehicle. A first image is captured at a first time instant and a second image is captured at a second time instant, from a camera mounted on the vehicle. The first image is different from the second image. While capturing the first and second images, one or more vehicle motion parameters from one or more sensors associated with the vehicle are received. Further, a corrected image is composed using the first image, the second image and the one or more vehicle motion parameters. Thereafter, the corrected image is displayed on a display unit of the vehicle.