High-spectral image processing method for gibbsite information extraction

An information extraction and image processing technology, which is applied in the field of hyperspectral image processing for gibbsite information extraction, can solve the problems of long processing time, large amount of data, and many manual operation steps, and achieves improved computing speed, good effect and significance. , the effect of reducing interference

Inactive Publication Date: 2016-03-16
BEIJING RES INST OF URANIUM GEOLOGY
View PDF5 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The current methods for extracting gibbsite information from hyperspectral remote sensing images are mainly spectral matching of full bands or partial continuous bands. Mineral composition, these methods are easily affected by the spectrum or noise of other ground objects in the process of information extraction, and the accuracy of extracted information is relatively low
Secondly, the existing spectrum extraction method has many manual steps, which increases the error of human judgment.
The third is that the hyperspectral data has many bands and a large amount of data. The existing methods take a long time to process, which reduces the speed of data processing and the scale of application.

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

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] The present invention comprises the steps in turn:

[0031] Step 1, preprocessing

[0032] Obtain hyperspectral images; preprocess hyperspectral images, perform atmospheric correction, and obtain image data of ground reflectance;

[0033] The atmospheric correction described in this step is a processing method known in the art.

[0034] Step 2: Sampling

[0035] Sampling the image data obtained in step 1, sampling images with wavebands at 1355nm, 1445nm, 1490nm, 1520nm, 1550nm, 1625nm, 1775nm, 1940nm, 2150nm, 2255nm, and recording them as b1~b10 in sequence, that is, b1 is the waveband of 1355nm Sampling data, b2 is the sampling data of the band 1445nm, and so on. Each sampling is a grayscale image, and the value of each pixel in the image is its grayscale value, that is, b1 is a grayscale image, and the value of point (1,1) of the b1 image is gray degree value, and so on for the rest of the points, and so on for the rest of the sampling maps.

[0036] Step Three: ...

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 belongs to a high-spectral image processing method, and especially relates to a high-spectral image processing method for gibbsite information extraction. The method comprises the steps: 1, preprocessing; 2, sampling: carrying out the sampling of images with bands being at 1355nm, 1455nm, 1490nm, 1520nm, 1550nm, 1625nm, 1775nm, 1940nm, 2150nm, and 2255nm; 3, judgment; 4, calculation. The effects of the invention lie in that the method just employs ten bands; compared with a method employing a high-spectral image SASI full-wave band (101 bands), the method reduces the size of to-be-processed data by 90%, reduces the steps of principal component transformation and end member wave spectrum selection with the help of automatic one-step extraction through a computer, and can improve the operation speed by ten times or more. Because most of bands which are hardly correlated with the information extraction, the method reduces the interference with the spectrum from other materials or noises, and improves the precision of information extraction. The method is has greater effect and significance for the quick extraction of the gibbsite information in high-spectral image data.

Description

technical field [0001] The invention belongs to a hyperspectral image processing method, in particular to a hyperspectral image processing method for extracting gibbsite information. Background technique [0002] The current methods for extracting gibbsite information from hyperspectral remote sensing images are mainly spectral matching of full bands or partial continuous bands. In the process of information extraction, these methods are easily affected by the spectrum or noise of other ground features, and the accuracy of extracted information is relatively low. Secondly, the existing spectrum extraction method has many manual steps, which increases the error of human judgment. The third is that hyperspectral data has many bands and a large amount of data. The existing methods take a long time to process, which reduces the speed of data processing and the scale of application. Therefore, how to reduce the influence of other ground features or noise, manual operation steps...

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): G06T5/00G06T7/00
Inventor 杨燕杰赵英俊武鼎宗自华张川陆冬华钱坤车永飞叶发旺李瀚波高仉生吴文欢
Owner BEIJING RES INST OF URANIUM GEOLOGY
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