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A low-altitude multi-view remote sensing image matching method based on improved sift operator

A remote sensing image and matching method technology, applied in computing, image analysis, image enhancement, etc., can solve the problems of immature multi-view images, no optimal threshold, and large local area dependence, so as to improve the matching effect and increase the similarity Sexuality, taking into account the effect of time efficiency

Active Publication Date: 2017-08-25
WUHAN UNIV
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Problems solved by technology

This method greatly improves the time efficiency, and in the case of large viewing angle changes between images, some correct matching points can still be obtained. However, it is highly dependent on the extracted local area. When the MSER operator is used to extract the local area, There is no optimal threshold, and the existing region segmentation algorithm is not yet mature for multi-view images

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  • A low-altitude multi-view remote sensing image matching method based on improved sift operator
  • A low-altitude multi-view remote sensing image matching method based on improved sift operator
  • A low-altitude multi-view remote sensing image matching method based on improved sift operator

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[0044] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0045] A low-altitude multi-view remote sensing image matching method based on the improved SIFT operator proposed by the present invention first uses the optimized DoG operator to extract feature points on the reference image and the image to be matched respectively; secondly uses the SIFT descriptor based on local area simulation The feature description is carried out; then the feature points are matched based on the ratio strategy of the nearest distance to the next nearest distance, and the initial matching result is purified by RANSAC based on polar geome...

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Abstract

The invention discloses an improved scale invariant feature transformation (SIFT) operator based low altitude multi-view remote-sensing image matching method. Firstly, an optimized DoG operator is used for performing feature point detection on a first image and a second image, then, a local area sampling simulation based SIFT descriptor is used for describing a feature point so as to form a feature vector, and finally, an initial matching feature point is formed by use of a nearest neighbor distance ratio (NNDR) policy, and matching points are purified by use of an epipolar geometric constraint based random sample consensus (RANSAC) algorithm. Through adoption of the method, problems of multi-view and weak texture in low altitude remote-sensing image matching can be solved effectively.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, relates to a remote sensing image matching method, and relates to a low-altitude multi-angle remote sensing image matching method based on an improved SIFT operator. Background technique [0002] Image matching has always been a research focus and hotspot in the field of photogrammetry and remote sensing. It is one of the key steps in image orientation, orthophoto production, automatic image registration, stitching, and 3D reconstruction. It directly affects the accuracy and effect of subsequent product production. . Compared with traditional remote sensing images, the acquisition environment of low-altitude remote sensing images is more complex, especially for images acquired from different perspectives, there are serious geometric distortions, similar textures, texture breaks, shadows, occlusions, etc., which greatly reduce the accuracy of the same target. The similarit...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/33
CPCG06T2207/10032
Inventor 邵振峰李从敏周维勋
Owner WUHAN UNIV
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