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

High spectral image end member automatic extraction method

A hyperspectral image, automatic extraction technology, applied in the field of hyperspectral remote sensing applications, can solve the problem of reducing the accuracy of the number of end members

Active Publication Date: 2015-12-23
BEIHANG UNIV
View PDF5 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The correct estimation of the number of endmembers is the prerequisite for the extraction of endmembers. The result of endmember extraction directly determines the accuracy of mixed pixel decomposition to a certain extent. At present, scholars have proposed many effective endmember extraction algorithms, but most of them are The algorithm mainly estimates the number of endmembers based on the interpretation experience, which often reduces the accuracy of the estimation of the number of endmembers due to the personal experience of the interpreter or the presence of high noise in the spectral data

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 spectral image end member automatic extraction method
  • High spectral image end member automatic extraction method
  • High spectral image end member automatic extraction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail by citing the following embodiments and referring to the accompanying drawings.

[0049] In order to explicitly explore the strengths and weaknesses of the end-metadata estimation method, simulated images will be used as experimental data. Select 5 material spectra from the USGS (United States Geological Survey) spectral library (denoted as P 1 ,P 2 ,P 3 ,P 4 ,P 5 ) constitutes a simulation image according to a certain ratio, and the wavelength range is from 350nm to 1000nm. The simulated image contains 25 square areas, the location of which is as follows image 3 As shown, the pixels in other areas in the image are called background pixels, and their size is the average value of the spectra of five substances (abbreviated as B), and the corresponding background spectral features are in figure 2 drawn in. The ...

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 spectral image end member automatic extraction method. Based on the phenomenon that high spectral data possesses characteristics approximate to low dimensional manifold data, and by employing the orthogonal projection principle, the method comprises expanding extracted end members to an orthogonal projection operator; analyzing the p norm value of each image element vector after projection; and automatically estimating end member quantity so as to extract end members. The method can automatically extract end members, increase the decomposition automatic degree of mixed image elements to a certain degree, and reduce manual intervention; the method possesses stronger robustness, and can still accurately estimate end member quantity at a low signal to noise ratio, and extract end members.

Description

technical field [0001] The invention relates to the application field of hyperspectral remote sensing, in particular to an automatic extraction method of hyperspectral image endmembers. Background technique [0002] Hyperspectral remote sensing is an important trend in the development of remote sensing technology. It has a large number of spectral channels, usually dozens or even hundreds. This feature has been successfully applied to research in the fields of geological exploration, agricultural and forestry surveys, and environmental monitoring. Impressive results. Hyperspectral has the characteristics of map-spectrum integration, and can obtain the spectral curve and image information of each pixel. With the rapid development of hyperspectral remote sensing technology, the complementary hyperspectral image endmember automatic extraction technology has also received more and more attention. [0003] The correct estimation of the number of endmembers is the prerequisite f...

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): G06K9/46
CPCG06V10/44
Inventor 李庆波牛春阳
Owner BEIHANG 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