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Improved wavelet transformation remote-sensing image fusion method and improved wavelet transformation remote-sensing image fusion system

A remote sensing image and fusion method technology, applied in the field of wavelet transform remote sensing image fusion, can solve the problems of poor remote sensing image fusion effect, improve the fusion effect, realize the softwareization of remote sensing image fusion, and solve the problems of spatial information loss and spectral information distortion Effect

Inactive Publication Date: 2013-02-06
NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an improved wavelet transform remote sensing image fusion method and system in order to solve the common problem of poor fusion effect in traditional remote sensing images

Method used

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  • Improved wavelet transformation remote-sensing image fusion method and improved wavelet transformation remote-sensing image fusion system
  • Improved wavelet transformation remote-sensing image fusion method and improved wavelet transformation remote-sensing image fusion system
  • Improved wavelet transformation remote-sensing image fusion method and improved wavelet transformation remote-sensing image fusion system

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specific Embodiment approach 1

[0030] Specific implementation mode one: the following combination figure 1 Describe this embodiment, a kind of improved wavelet transform remote sensing image fusion method described in this embodiment, the realization process of this method is:

[0031] Step 1. Preprocess the multispectral image and the panchromatic image separately: firstly, use the quadratic polynomial method to perform geometric registration on the multispectral image so as to maintain geometric consistency with the panchromatic image; then, use linear interpolation The multispectral image is resampled by the method, so that the pixel size of the multispectral image to be fused is consistent; finally, the image of the area to be fused is cut out, and the multispectral image to be processed and the panchromatic image to be fused are obtained in the same area;

[0032] Step 2. Perform PCA transformation on the preprocessed multispectral image:

[0033] First, the first three components of the preprocessed ...

specific Embodiment approach 2

[0040] Specific implementation mode two: the following combination Figure 1 to Figure 5 Describe this embodiment. This embodiment is a further description of the fusion of the high-frequency information of the first component and the high-frequency information of the panchromatic image using the fusion rule of local variance in step 4 of the first embodiment. In step 4, the method of fusing the high-frequency information of the first component image and the high-frequency information of the panchromatic image using the fusion rule of local variance, and the method of obtaining the new high-frequency information after fusion is:

[0041] Select a 3×3 window for calculation,

[0042] The window traverses the first component image. The moving step of the window is one pixel. The local variance method is used to calculate the variance value of all pixels in the area covered by the window one by one, and then obtain the gray value of the pixel at the center of the window. ;

[0...

specific Embodiment approach 3

[0050] Specific implementation mode three: the following combination Figure 1 to Figure 5 This embodiment is described. This embodiment is a further description of the fusion rule of the fusion rule using local difference weighting in Step 4 of Embodiment 1 to fuse the low-frequency information of the first component with the low-frequency information of the panchromatic image. In step 4, the low-frequency information of the first component image and the low-frequency information of the panchromatic image are fused using the fusion rule of local difference weighting, and the method of obtaining new low-frequency information after fusion is as follows:

[0051] Select a 7×7 window for calculation,

[0052] avgAB ( x , y ) = Σ i = x - 3 ...

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Abstract

The invention discloses an improved wavelet transformation remote-sensing image fusion method and an improved wavelet transformation remote-sensing image fusion system and belongs to the technical field of remote-sensing image processing, which solve the problem that the traditional remote-sensing image fusion method is usually bad in fusion effect. The method comprises the following steps of: performing preprocessing and PCA (principal component analysis) transformation to a to-be-fused multispectral image, taking first three components, matching the first component with a panchromatic image by histogram, performing wavelet transformation, and obtaining new high-frequency information from the obtained high-frequency information by a local variance fusion rule; obtaining the fused new low-frequency information by a local difference weighting fusion rule; and performing wavelet reverse transformation, taking the result as a new component, and performing PCA reverse transformation to the new component and the original second and third components to obtain the last fusion result image. The remote-sensing image fusion system comprises an image input module, a wavelet analysis module, a remote-sensing image fusion module, a remote-sensing image fusion effect assessment module and a fusion result saving module. The method and the system are suitable for fusion of the remote-sensing images.

Description

technical field [0001] The invention relates to a wavelet transform remote sensing image fusion method and system, belonging to the technical field of remote sensing image processing. 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 use of these rich data sources, dig out the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 董张玉刘殿伟王宗明赵萍汤旭光贾明明汪燕丁智
Owner NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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