Polarimetric SAR image classification method based on eigenvector measurement spectral clustering

Abstract

The invention belongs to the technical field of remote sensing image processing, and particularly discloses a polarimetric SAR image classification method based on eigenvector measurement spectral clustering. The aim that the eigenvectors obtained after a polarimetric coherence matrix eigenvalue is decomposed are studied and utilized is mainly achieved. The implementation process mainly comprises the steps that (1) Lee filtering is carried out on a polarimetric SAR image; (2) eigenvalue decomposition is carried out on a coherence matrix of each pixel to obtain the eigenvectors; (3) the eigenvector corresponding to the maximum eigenvalue is used for constructing features; (4) a similarity matrix is constructed in a measurement mode of included angle cosine distance; (5) a spectral clustering algorithm is carried out on the similarity matrix to obtain initial classification tags; (6) wishart clustering is carried out on the basis of the initial classification tags to obtain the final classification result. The method has the advantages of being low in complexity and finer and more accurate in classification result, and can be used for target detection and target recognition of the polarimetric SAR image.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing and relates to classification of polarimetric synthetic aperture radar images, which can be used for image target detection and image target classification and recognition, and specifically relates to a polarimetric SAR image classification method based on eigenvector metric spectrum clustering. Background technique [0002] With the development of radar technology, polarimetric SAR has become the development trend of SAR, and polarimetric SAR can obtain richer target information. The understanding and interpretation of polarimetric SAR images involves signal processing, pattern recognition and many other disciplines. As one of the basic problems of polarimetric SAR image processing, polarimetric SAR image classification lays the foundation for later target recognition of polarimetric SAR images. [0003] The existing polarization SAR image classification methods can be ro...

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Problems solved by technology

[0004] Existing methods have fully studied the polarimetric SAR coherence matrix and its eigenvalues ​​after eigenvalue decomposition, and achieved certain results. However, the concept of matrix theory shows that the matrix that best reflects the properties of a matrix is ​​the matrix The eigenvector of the eigenvector, the direction information contained in the eigenvector embodies the essence of matrix transformation, and the existing methods make less use of the eigenvector, resulting in a waste of scattering information

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