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Multi-channel satellite cloud picture fusion method based on Shearlet conversion

A satellite cloud image and fusion method technology, applied in the field of multi-channel satellite cloud image fusion, can solve the problems of easy introduction of pseudo-Gibbs phenomenon, large amount of data, long time, etc.

Active Publication Date: 2014-06-04
ZHEJIANG NORMAL UNIVERSITY
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  • Summary
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, when Contourlet transform is applied to image fusion, it is easy to introduce pseudo-Gibbs phenomenon, and it takes too long and a large amount of data to overcome this phenomenon.

Method used

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  • Multi-channel satellite cloud picture fusion method based on Shearlet conversion
  • Multi-channel satellite cloud picture fusion method based on Shearlet conversion
  • Multi-channel satellite cloud picture fusion method based on Shearlet conversion

Examples

Experimental program
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Effect test

experiment example 1

[0126] As shown in Figure 3(a)~(h), we selected the infrared 2-channel and water-air channel cloud images from the typhoon "Tali" at 12:00 on August 31, 2005 as the original image for fusion processing. It is processed into a grayscale image by MATLAB7.0, which is a fusion experiment image of 512×512 pixels intercepted from the satellite cloud image of 2288×2288 size shown in Figure 2. Each pixel represents its brightness digitally. A higher number indicates a brighter point.

[0127] We respectively perform Shearlet transformation on the two cloud image images to be fused. In the decomposition process of the above steps, the number of decomposition layers is one layer and eight directions. In order to verify the effectiveness of the fusion algorithm proposed in this paper, the fusion results of the method in this paper are compared with the Laplacian pyramid image fusion method, the classical discrete The frequency coefficient takes the part with large energy in the area, a...

experiment example 2

[0144] As shown in Figure 7(a)-(h), we selected the infrared channel 1 and water-air channel cloud images from the typhoon "Pearl" at 00:00 on May 11, 2006 as the original image for fusion processing. The cloud images of its infrared channel 1 and water-air channel are shown in Fig. 7(a) and Fig. 7(b). Figure 7(c) is the fusion result of the Laplacian pyramid, Figure 7(d) is the fusion result of the classical discrete orthogonal wavelet, Figure 7(e) is the fusion result of the Curvelet image fusion method Figure 7(f) is the Contourlet image The fusion result of the fusion method, Fig. 7(g) is the fusion result of the NSCT image fusion method, and Fig. 7(h) is the fusion result of this image fusion algorithm. Since there is no eye typhoon in Figure 7, judging from the details of the cloud image on the periphery of the cyclone, the components with large gray values ​​in the fusion results of the Curvelet image fusion algorithm in Figure 7(e) and the fusion results of the NSCT im...

experiment example 3

[0155] In order to further illustrate the effectiveness of the fusion algorithm proposed in this paper, the computational complexity of the method proposed in the present invention is analyzed below. The image fusion algorithm in this paper is run on MatLab R2009a software. The software runs on Intel Core 2 Quad Core Q9400 2.66GHz, 2GB RAM (Kingston DDR31333MHz), and Windows XP Professional 32-bit SP3 (DirectX9.0c) as the operating system. on a Dell OptiPlex 780 desktop computer. Here, the running time of various fusion methods is measured, and the second set of experimental images is used for testing. The running time of various fusion algorithms is shown in Table 5.

[0156] Table 5 Running time of various fusion algorithms

[0157]

[0158] As can be seen from Table 5, except that the running time of the image fusion algorithm based on the Laplacian pyramid and the image fusion algorithm of classic orthogonal discrete wavelet is relatively short, the time used by other ...

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Abstract

The invention relates to a multi-channel satellite cloud picture fusion method based on Shearlet conversion and belongs to the field of weather prognoses. Firstly, two registered satellite cloud pictures are subjected to Shearlet conversion to acquire a low-frequency coefficient and a high-frequency coefficient; secondly, a low-frequency Shearlet domain part is divided again through a Laplacian pyramid, the mean value of the top layer of the Laplacian pyramid is worked out, and then reconstruction of other layers with large gray-level absolute values of the Laplacian pyramid is carried out; in the high-frequency Shearlet domain part, the information entropy, average gradient and standard deviation of each high-frequency sub-picture are worked out and are then subjected to normalization processing, the product of every group of three processed values is worked out, and the sub-picture with the large product serves as a fused sub-picture; the fused sub-picture is subjected to detail enhancement treatment through a non-linear operator; finally, a final fused picture is obtained through Shearlet inverse transformation. The method can be popularized to fusion of three or more satellite cloud picture to achieve multi-channel satellite cloud picture fusion and acquire high-precision typhoon center positioning results.

Description

technical field [0001] The invention belongs to the field of meteorological prediction. Specifically, it involves a multi-channel satellite cloud image fusion method based on Shearlet transform for the purpose of improving the typhoon center positioning accuracy. Background technique [0002] Meteorological satellite cloud images play an extremely important role in weather monitoring and forecasting and atmospheric environment detection, especially in the monitoring of some extreme meteorological disasters. Therefore, the follow-up analysis and processing of satellite cloud images can better obtain information such as the atmosphere, land, ocean, and clouds, provide reliable data support for monitoring and forecasting, and improve the automation and accuracy of forecasting, which has important practical significance. [0003] my country's Fengyun-2 C star (FY-2C) geostationary orbit meteorological satellite receives visible light, infrared and water vapor radiation from the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50
Inventor 张长江陈源
Owner ZHEJIANG NORMAL UNIVERSITY
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