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Image matching method with large edge distortion

An image matching and edge technology, applied in image analysis, image enhancement, image data processing and other directions, can solve the problems of strict geometric constraint model gross error elimination, unable to match points, too large search range, etc., to achieve stable matching results, The matching scheme is feasible and the effect of high precision

Active Publication Date: 2020-05-22
CHINA CENT FOR RESOURCES SATELLITE DATA & APPL
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AI Technical Summary

Problems solved by technology

[0004] 1) If large edge distortions are taken into account, too many mismatch points will be caused due to the large search range, and it is impossible to construct a strict geometric constraint model for gross error elimination;
[0005] 2) If the small distortion in the middle is taken into account, due to the small search range, it will cause the problem that points cannot be matched except the central area

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  • Image matching method with large edge distortion
  • Image matching method with large edge distortion
  • Image matching method with large edge distortion

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Embodiment Construction

[0016] It should be understood that the idea of ​​the present invention is to perform high-precision matching of large edge distortion images based on image segmentation and multi-level multi-features. The implementation of the present invention includes rough matching of pyramid images, multi-level multi-feature matching rule grid construction, multi-level multi-feature matching, gross error elimination rule grid construction, cyclic iteration gross error elimination within the grid, overall loop iteration gross error elimination, etc. rough and method.

[0017] In the present invention, the high-precision registration process specifically includes:

[0018] Step 1: Establish pyramid images at all levels for the image to be matched and the reference image for rough matching.

[0019] Step 2, using the rough matching result of step 1, using the overall affine transformation model to construct a geometric model to eliminate parallax;

[0020] Step 3: Segment and block the ima...

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Abstract

The present invention provides an edge large distortion image matching method. The method comprises the steps of: establishing each-level pyramid image for an image to be matched and a reference image, and performing rough matching; employing an integrated radiation transformation model to perform model construction according to a rough matching result so as to eliminate parallax; employing a multi-level and multi-feature mode, performing segmentation and blocking processing of the image to be matched and the reference image according to a multi-level and multi-feature matching rule grid, andperforming multi-level and multi-feature matching for each block obtained after segmentation and blocking processing; performing segmentation and blocking processing of the image to be matched according to a gross error elimination rule grid, and employing the radiation transformation model to perform loop iteration for each grid in the gross error elimination rule grid for gross error elimination; and employing one control point of each grid after gross error elimination, employing an integrated cubic polynomial iteration model for gross error elimination again according to a camera objectivelens radial directional and tangential distortion for theory to obtain high-precision matching points and perform output according to a predetermined format.

Description

technical field [0001] The invention belongs to the field of photogrammetry and computer vision, and relates to a high-precision registration scheme for large edge distortion images based on image segmentation and multi-level multi-features, in particular to a matching method for large edge distortion images, which is used for image segmentation and block segmentation And multi-level multi-feature mode, high-precision automatic matching of control points is performed on large edge distortion images. Background technique [0002] At present, domestic high-resolution optical satellites all use three-mirror coaxial or triple-mirror off-axis optical systems. Due to the influence of radial and tangential distortion of the optical system, the geometric distortion of the edge of the image before the camera’s in-orbit geometric calibration is very large, and the middle The distortion is small. For example, the distortion of the panchromatic / multispectral camera image of the Gaofen-1...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/33
CPCG06T7/337G06T2207/20016G06T2207/20021
Inventor 龙小祥李庆鹏王冰冰喻文勇崔林秦敬芳
Owner CHINA CENT FOR RESOURCES SATELLITE DATA & APPL
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