Vehicle Surround View Image Correction for Fisheye Distortion
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Solution Overview
Problem
Fisheye cameras used in vehicle surround view systems produce radially distorted images that are of low quality when corrected and displayed, especially in outer regions, leading to 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 identify undistorted slices in each image, replacing distorted regions to compose a corrected image free of radial distortions, which is then displayed on a vehicle's display unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of moving object
If fisheye cameras are used to cover a larger field of view, then the field of view is improved, but the image quality in outer regions deteriorates due to radial distortion
Solution Approach 1:
The patent divides the captured image into multiple regions (first region with undistorted view and second region with distorted view) and processes each region differently. The undistorted first region is used to generate a first corrected image, while the distorted second region is used to generate a second corrected image through additional correction processing, thereby resolving the contradiction between wide field of view and image quality.
Solution Approach 2:
The patent applies different correction methods to different regions of the image. The first region (undistorted) undergoes standard correction, while the second region (distorted) receives enhanced correction processing. This local differentiation allows the system to maintain high image quality across the entire field of view while preserving the wide coverage capability of fisheye cameras.
2Shape
If radial distortion correction is applied to fisheye camera images, then the distortion is reduced, but the image quality in outer regions deteriorates
Solution Approach 1:
The patent segments the image into undistorted and distorted regions, applying appropriate correction strategies to each. This segmentation allows distortion correction to be performed effectively without degrading overall image quality.
Solution Approach 2:
The system performs preliminary correction on the undistorted first region to generate a first corrected image, then uses this as a reference for correcting the distorted second region. This preliminary action ensures that correction is built on a solid foundation of high-quality undistorted regions.
3Shape
If corrected images are generated from fisheye camera captures, then the distortion is removed, but the quality of corrected images deteriorates especially in outer regions
Solution Approach 1:
The patent merges the first corrected image (from undistorted region) and the second corrected image (from distorted region) to generate a final corrected image. This merging process combines the strengths of both regions, ensuring high overall image quality while maintaining complete distortion removal.
Solution Approach 2:
The system performs preliminary correction on the undistorted first region before using it to guide the correction of the distorted second region. This preliminary correction establishes a high-quality baseline that improves the final merged result.
4Loss of time
If single image correction is performed, then the processing time is reduced, but the image quality deteriorates
Solution Approach 1:
The patent segments the correction process into parallel operations on different image regions. The undistorted first region and distorted second region are processed simultaneously using different methods, then merged. This segmentation enables quality improvement without significant time penalty.
Solution Approach 2:
The system applies partial correction to the undistorted first region and excessive (enhanced) correction to the distorted second region. This differentiated approach ensures high quality where needed while minimizing unnecessary processing elsewhere.
Data Source
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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 (t-1) and a second image is captured at a second time instant (t), 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.