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

High-resolution remote sensing image registration method based on local invariant feature point

A local invariant feature, remote sensing image technology, applied in image enhancement, image analysis, image data processing and other directions, to achieve the effect of wide application value

Inactive Publication Date: 2016-07-06
FUJIAN NORMAL UNIV
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, so far there is no solution or method that can simultaneously possess the above five characteristics, and most of the methods are specific to specific applications.

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
  • High-resolution remote sensing image registration method based on local invariant feature point
  • High-resolution remote sensing image registration method based on local invariant feature point
  • High-resolution remote sensing image registration method based on local invariant feature point

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0023] In step 101, a reference remote sensing image image1 and a remote sensing image image2 to be registered in different phases of the same region are input.

[0024] In step 102, the Harris feature points in image1 and image2 are extracted to obtain feature point sets P 1 and P 2 .

[0025] In step 103, use the SIFT descriptor to respectively classify the feature point set P 1 and P 2 Describe the eigenvectors.

[0026] In step 104, search feature point set P 1 to P 2 All the feature points that meet the matching condition C in , get the matching point pair set M 1 , at the same time, search feature point set P 2 to P 1 All the feature points that meet the matching condition C in , get the matching point pair set M 2 , the M 1 and M 2 The intersection of is used as the two-way matching point pair set Mset.

[0027] In step 105...

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 relates to a high-resolution remote sensing image registration method based on a local invariant feature point. The high-resolution remote sensing image registration method comprises the following steps: S1: extracting Harris feature points in a benchmark remote sensing image and a remote sensing image to be registered at different time phases in the same area to independently obtain feature point sets P1 and P2; S2: utilizing a SIFT (Scale Invariant Feature Transform) descriptor to independently carry out feature vector description on the feature point sets P1 and P2; S3: searching bidirectional matching point pairs; S4: randomly selecting three groups of matching point pairs PM3 from S3, and obtaining the root-mean-square error RM of the three groups of matching point pairs PM3; S5: judging the threshold value, and returning to S4 or entering S6; S6: calculating an affine transformation relationship matrix Matrix; and S7: utilizing transformation in S6 to obtain a registration image image_R. The high-resolution remote sensing image registration method solves the problem of big registration error of the high-resolution remote sensing image, can realize the high precision and the automation of registration and has a wide application value in the field of the change detection of the remote sensing image.

Description

technical field [0001] The invention relates to a registration field, in particular to a high-resolution remote sensing image registration method based on local invariant feature points. Background technique [0002] A good remote sensing image registration method or scheme should have the following characteristics: A. Strong robustness, that is, the algorithm is not affected by the content and quality of the input image; B. Wide adaptability, which includes two aspects: one is input The type of image can be images of different time phases, or images of different sensors, or even the registration between images and maps; on the other hand, the type of geometric transformation model can be similar transformation, affine transformation or Polynomial transformation, even more complex transformation forms; C, high degree of automation, the algorithm does not require operator participation as much as possible, including the selection of ground control points, parameters and algor...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T2207/10032
Inventor 施文灶
Owner FUJIAN NORMAL 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