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Hyperspectral image clustering method, device, equipment and storage medium

A technology of hyperspectral image and clustering method, which is applied in the fields of hyperspectral image clustering method, equipment and storage medium, and device, can solve the problems of unsatisfactory clustering results and high computational complexity, and achieves the reduction of computational complexity and high efficiency. Clustering results, the effect of avoiding the need for thermal kernel parameters

Active Publication Date: 2020-10-09
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0005] This application provides a hyperspectral image clustering method, device, equipment, and storage medium, which solves the existing technical problems of high computational complexity and unsatisfactory clustering results

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  • Hyperspectral image clustering method, device, equipment and storage medium
  • Hyperspectral image clustering method, device, equipment and storage medium
  • Hyperspectral image clustering method, device, equipment and storage medium

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Embodiment approach

[0094] A specific implementation of a hyperspectral image clustering method in the present application may be:

[0095] S1: First input the hyperspectral image data matrix X, the number of anchor points m, the category c, and the number of clusters k;

[0096] S2: Use the binary tree anchor point algorithm to generate the anchor point set U;

[0097] S3: Calculate the similarity matrix A by constructing the adjacency matrix Z of the hyperspectral image data with a kernel-free method;

[0098] S4: Obtain the diagonal matrix D and the Laplacian matrix L through the similarity matrix A, then perform singular value decomposition on the matrix B to obtain the class index matrix F of the hyperspectral image data, and finally perform K-means on the matrix F to obtain clustering result.

[0099]In a specific experiment, the HIS hyperspectral image data set is used to verify the method of the application in order to evaluate the performance of the method of the application. In the e...

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Abstract

The invention discloses a hyperspectral image clustering method, device, equipment and a storage medium. The method comprises the steps: obtaining a hyperspectral image data matrix, and generating ananchor point set through employing a binary tree anchor point algorithm; constructing an adjacent matrix by the anchor point set and the hyperspectral image data matrix through a preset first formula,and solving a similarity matrix by the adjacent matrix through a preset second function; constructing a Laplace matrix according to the similarity matrix, and constructing a hyperspectral clusteringtarget function according to the Laplace matrix; and solving the target function to obtain a clustering result. The technical problems that in the prior art, the calculation complexity is too high, and the clustering result is not ideal are solved.

Description

technical field [0001] The present application relates to the technical field of image clustering, in particular to a hyperspectral image clustering method, device, equipment and storage medium. Background technique [0002] Hyperspectral image (Hyperspectral Image, HSI) has a large amount of spatial geometric and spectral information, has become an important resource in the field of remote sensing data analysis, and is widely used in precision agriculture, environmental monitoring, and military fields. Spectral clustering is a very popular clustering algorithm, and it is rarely used in HIS clustering, so it has great potential in HIS clustering. It does not require strong assumptions about the type of cluster and can cluster data of any shape. [0003] The traditional spectral clustering (Spectral Clustering, SC) method uses a nuclear spectral clustering method, and there are four steps of nuclear spectral clustering: first calculate the data matrix through the Gaussian ke...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2136G06F18/23213
Inventor 杨晓君杜鹏林郭春炳许裕雄蔡湧达黄晓蓓
Owner GUANGDONG UNIV OF TECH
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