Wide-Area Image Acquisition via Global Reference Alignment
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Solution Overview
Problem
Existing methods for acquiring wide-area images, such as using multiple high-definition cameras to capture partial high-definition images and splice processing, result in low precision due to deviations from the actual image and alignment issues between partial images.
Innovation Solution
A method and apparatus that capture a global image and at least two partial images within a preset wide-area visual area, where the global image covers an overlap portion of the partial images' view ranges, and determine the positions of the partial images' edges based on same shot objects to perform splice processing, adjusting pixel quantities and using feature point matching and interpolation calculations to align and correct the images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple high-definition cameras are used to capture partial images for wide-area imaging, then the coverage area is increased, but the image precision and alignment accuracy deteriorate due to deviations from actual images
Solution Approach 1:
The patent divides the wide-area imaging task into multiple partial images captured by different cameras, each covering a specific sub-area. This segmentation allows the system to maintain high definition in each partial image while collectively covering a large area, resolving the contradiction between area coverage and image precision.
Solution Approach 2:
The patent introduces a reference image as an intermediary to facilitate accurate alignment and splicing of partial images. The reference image provides a common coordinate system and visual reference that enables precise positioning of each partial image, thereby maintaining high image precision across the entire wide-area composite image.
2Area of stationary object
If splice processing is performed on multiple partial images, then the wide-area image is constructed, but visual differences and alignment deviations occur between the spliced images
Solution Approach 1:
The patent employs feedback mechanisms in the form of reference images and alignment algorithms that continuously adjust the positioning and orientation of partial images during splicing. This feedback ensures that visual differences between adjacent partial images are minimized, maintaining composition stability and visual consistency across the entire wide-area image.
Solution Approach 2:
The patent performs preliminary alignment and coordinate transformation of partial images before final splicing, using reference images to pre-establish the correct geometric relationships. This preliminary action prevents visual discontinuities and alignment deviations in the final composite image, ensuring visual consistency.
3Measurement precision
If feature point matching and interpolation calculations are used to align partial images, then the alignment precision is improved, but the processing complexity increases
Solution Approach 1:
The patent extracts key feature points from images and uses them as control points for alignment and interpolation. By focusing only on critical feature points rather than processing entire images, the system achieves high alignment precision while significantly reducing computational complexity and processing requirements.
Data Source
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AI summary
A wide-area image acquiring method and apparatus are disclosed. The method includes: capturing a global image in a preset wide-area visual area; and capturing at least two partial images whose definition is preset and that are in the preset wide-area visual area, where the global image covers at least an overlap portion of view ranges of the partial images in the preset wide-area visual area, and a sum of the view ranges of the at least two partial images is greater than or equal to a view range of the global image (101); and determining, in the global image, positions that are of edges of the partial images, based on same shot objects that are in the partial images and also in the global image, and performing splice processing on the at least two partial images according to the positions that are of the edges of the partial images and that are in the global image, to obtain a composite wide-area image of the wide-area visual area (102). The method increases a precision of a spliced wide-area image.