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

Correlation weighted remote-sensing image fusion method and fusion effect evaluation method thereof

A technology of remote sensing image and fusion method, applied in image enhancement, image analysis, image data processing and other directions, can solve problems such as difficulty in improving fusion effect, loss of spatial information, distortion of spectral information, etc.

Inactive Publication Date: 2013-04-24
NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
View PDF0 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem that the traditional remote sensing image processing technology has the disadvantages of loss of spatial information or distortion of spectral information, and it is difficult to improve the fusion effect, the invention proposes a correlation weighted remote sensing image fusion method and a fusion effect evaluation method of the fusion method

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
  • Correlation weighted remote-sensing image fusion method and fusion effect evaluation method thereof
  • Correlation weighted remote-sensing image fusion method and fusion effect evaluation method thereof
  • Correlation weighted remote-sensing image fusion method and fusion effect evaluation method thereof

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0043] Specific implementation mode 1. Combination figure 1 This embodiment is described in detail. The correlation weighted remote sensing image fusion method described in this embodiment includes the following steps:

[0044] Step 1. Preprocessing the original images to be fused, where the original images to be fused include multispectral images and panchromatic images;

[0045] Step 2, calculating the correlation between each band of the preprocessed multispectral image and each band of the panchromatic image;

[0046] Step 3, by adjusting the weight of the multispectral image, the best weight coefficient of the multispectral image is obtained, and the correlation weighted fusion model is obtained according to the best weight coefficient;

[0047] Step 4, realizing the fusion of the multispectral image and the panchromatic image according to the correlation weighting algorithm.

specific Embodiment approach 2

[0048] Embodiment 2. The difference between this embodiment and the correlation-weighted remote sensing image fusion method described in Embodiment 1 is that the specific process of preprocessing the original image to be fused as described in Step 1 is:

[0049] Acquire multispectral images and panchromatic images through sensors;

[0050] According to the quadratic polynomial method, the multi-spectral image is geometrically registered, so that the multi-spectral image and the panchromatic image maintain geometric consistency;

[0051] Resampling the registered multispectral image according to the linear interpolation method, so that the pixel size of the multispectral image is consistent with that of the panchromatic image;

[0052] The panchromatic image and the resampled multispectral image were cropped, and the image of the test area was cropped to obtain the panchromatic image and multispectral image of the same area.

specific Embodiment approach 3

[0053] Embodiment 3. The difference between this embodiment and the correlation-weighted remote sensing image fusion method described in Embodiment 1 is that in Step 2, the calculation of the bands of the preprocessed multispectral images and the bands of the panchromatic images The specific process of correlation is:

[0054] The correlation reflects the degree of the panchromatic image and the original image to be fused through the correlation coefficient. The closer the correlation coefficient is to 1, the better the correlation between the two images is. According to the formula (1), each band of the preprocessed multispectral image is obtained. Correlation coefficient with each band of panchromatic image

[0055] rt ( A B ) = Σ i = 1 M ...

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 correlation weighted remote-sensing image fusion method and a fusion effect evaluation method of the remote-sensing image fusion method, and relates to the technical field of remote-sensing image process. The correlation weighted remote-sensing image fusion method comprises a first step of preprocessing an original to-be-fused image, a second step of calculating the correlation between each wave section of a processed multispectral image and each wave section of a panchromatic image, a third step of adjusting weight of the multispectral image to obtain a best weight coefficient of the multispectral image, and acquiring a correlation weighted fusion model according to the best weight coefficient, and a fourth step of achieving fusion of the multispectral image and the panchromatic image according to a weighting algorithm. The fusion effect evaluation method of the correlation weighted remote-sensing image fusion method comprises a first step of acquiring a fusion image according to the correlation weighted remote-sensing image fusion method, a second step of evaluating the fusion image through a mathematical statistics quantitative method which evaluates the to-be-fused image and the fusion image according to chosen fusion effect evaluation indexes, and the fusion effect evaluation indexes respectively are variance, information entropy and torsion resistance.

Description

technical field [0001] The invention relates to remote sensing image processing technology, in particular to a correlation weighted remote sensing image fusion method and a fusion effect evaluation method of the fusion method. Background technique [0002] With the rapid development of modern remote sensing sensors and related technologies, the means of remote sensing data acquisition are increasing, and various earth observation satellites are continuously providing remote sensing data with different spatial resolutions, spectral resolutions, and temporal resolutions for applications. However, due to the different imaging principles of remote sensing satellites and the limitations of technical conditions, any single information source cannot fully reflect the characteristics of the target object, and it is difficult to have the characteristics of high spatial and high spectral resolution at the same time, so it has certain limitations on application. In order to make full u...

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): G06T5/50G06T7/00
Inventor 董张玉刘殿伟王宗明赵萍汤旭光贾明明汪燕丁智邵田田
Owner NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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