Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Improved scale invariant feature transformation (SIFT) operator based low altitude multi-view remote-sensing image matching method

A technology of remote sensing images and matching methods, which is applied in computing, image analysis, image enhancement, etc., and can solve problems such as no optimal threshold, immature multi-view images, and large dependence on local areas

Active Publication Date: 2015-12-16
WUHAN UNIV
View PDF2 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Improved scale invariant feature transformation (SIFT) operator based low altitude multi-view remote-sensing image matching method
  • Improved scale invariant feature transformation (SIFT) operator based low altitude multi-view remote-sensing image matching method
  • Improved scale invariant feature transformation (SIFT) operator based low altitude multi-view remote-sensing image matching method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] In order to facilitate the understanding and implementation of the present invention by those of ordinary skill in the art, the present invention will be further described in detail with reference to 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] The present invention proposes a low-altitude multi-view remote sensing image matching method based on an improved SIFT operator. First, the optimized DoG operator is used to extract feature points on the reference image and the image to be matched; secondly, the SIFT descriptor based on local area simulation is used. Perform feature description; then match the feature points based on the ratio strategy of the closest distance to the next-adjacent distance, and use RANSAC based on polar geometry to refine the initial matching results to obtain the f...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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-view remote sensing image matching method based on an improved SIFT operator. Background technique [0002] Image matching has always been the 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, splicing, 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 complicated. Especially images acquired from different perspectives have serious geometric distortions, similar textures, texture fractures, shadows, occlusion, etc., which greatly reduces the same target The similarity in different images wit...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06T7/00
CPCG06T2207/10032
Inventor 邵振峰李从敏周维勋
Owner WUHAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com