Character window weighting related spectrum matching method facing rocks and minerals

A technology of correlation spectrum and matching method, applied in optical exploration and other directions, can solve the problems of weak pertinence and large influence, and achieve the effect of strong pertinence, improvement of elimination ability, and reasonable results.

Inactive Publication Date: 2013-05-01
CHENGDU UNIVERSITY OF TECHNOLOGY
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a feature window weighted correlation spectral matching method for rock ore, to solve the problems in the prior art that the spectral matching method is greatly affected by natural environmental factors and weak in pertinence.

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
  • Character window weighting related spectrum matching method facing rocks and minerals
  • Character window weighting related spectrum matching method facing rocks and minerals
  • Character window weighting related spectrum matching method facing rocks and minerals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0033] In the present invention, natural environmental factors mainly refer to temperature, temperature, water vapor, and atmosphere. The basic idea of ​​the present invention is to firstly use the global unified model to eliminate the error of the natural environment factor error on the remote sensing image. At this time, the influence error of the natural environment factor on the electromagnetic waves of rocks and mines still exists, and these errors are called residual errors in this paper. ; Assume that the quantitative indicators of these residual errors are random and have normal distribution characteristics; then in the full wavelength range, according to the rock ore spectrum measured in the laboratory, the characteristic intervals are divided, and the weight distribution is carried out according to the sensitivity of the intervals, and then The correlation coefficient of the feature window is calculated, and finally the reference basis for identifying the type of rock...

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 a character window weighting related spectrum matching method facing rocks and minerals, and the method comprises the following steps that: (1) supposing that errors caused by the natural environment are normally distributed at random, a remote sensing image is based on each wave band, the reflectivity of each wave band is expanded to an interval between zero and one within the reflectivity range according to a normal distribution law, and a matrix data set X is formed; (2) a standard spectrum curve is based on each wave band, and the reflectivity of each wave band is expanded to an interval between zero and one within the reflectivity range according to a normal distribution law, and a matrix data set Y is formed; (3) the rocks and minerals are subjected to sensitive interval division within the full wave length range according to the standard spectrum curve, a character window is formed and a predetermined weight coefficient is set; (4) a related coefficient r of the character window is calculated and is combined with the weight coefficient in the step (3), and a comprehensive related coefficient K is obtained; and (5) the comprehensive related coefficient K is utilized as the final basis for distinguishing the types of the rocks and minerals.

Description

technical field [0001] The invention relates to a method for identifying rock ore types, in particular to a rock ore-oriented feature window weighted correlation spectrum matching method in the field of hyperspectral remote sensing. Background technique [0002] At present, based on hyperspectral remote sensing data, the methods of using spectral matching technology to extract rock and mineral information to identify rock and mineral types mainly include: spectral angle classification method, spectral curve fitting method, mixed modulation matching filter, etc. The technical core of these methods is to use the sample spectrum measured in the laboratory or the sample spectrum selected from the image to compare and judge with the surface object spectrum to be judged on the remote sensing image. However, since the remote sensing data is the energy information of the solar reflection and radiation received by the remote sensing sensor in the natural environment, and the factors ...

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 Patents(China)
IPC IPC(8): G01V8/02
Inventor 叶成名罗慧芬苗放
Owner CHENGDU UNIVERSITY OF TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap