Polarization SAR image segmentation method based on characteristic value measurement spectral clustering

Abstract

The invention discloses a polarization SAR image segmentation method based on characteristic value measurement spectral clustering. The method mainly solves the problems that the number of parameters is large and adaptive adjustment is difficult to carry out in the existing polarization SAR image segmentation process. The method includes the steps of 1, carrying out eigenvalue decomposition on a polarization SAR image to form a feature sample set x, 2, solving corresponding mean values of three eigenvalues in an 8 neighborhood of each pixel to form a mean feature sample set, 3, respectively building a similarity matrix for the feature sample set x and the mean feature sample set utilizing mahalanobis distance so as to obtain a mixed similarity matrix w' according to the two similarity matrixes, 4, obtaining a clustering label C1 of the mixed similarity matrix w' through the spectral clustering algorithm, and 5, repeating the steps 3 and 4, integrating obtained class label sets by utilizing the MCLA so as to obtain a final segmentation result. The polarization SAR image segmentation method has the advantages of being high in adaptivity, low in complexity, detailed and accurate in segmentation result, and capable of being used for target detection and target recognition of the polarization SAR image.

Description

Technical field [0001] The invention belongs to the technical field of remote sensing image processing, relates to polarization synthetic aperture radar image segmentation, and can be used for image target detection and image target segmentation and recognition. Background technique [0002] With the increasing development of radar technology, polarized SAR has become the development trend of SAR, and polarized SAR can obtain richer target information. The understanding and interpretation of polarized SAR images involves many subjects such as signal processing and pattern recognition. Polarized SAR image segmentation is one of the basic problems of polarized SAR image processing, which lays the foundation for the later target recognition of polarized SAR image. [0003] The existing polarization SAR image segmentation methods can be divided into two types: supervised and unsupervised. [0004] Supervised methods include: the use of statistical information of data proposed by Kong e...

AI Technical Summary

Problems solved by technology

For this reason, Ersahin and Anfinsen et al. used spectral clustering to segment polarimetric SAR images, and defined the similarity matrix through the Wishart distance of the polarimetric coherence matrix. Although this method can automatically complete clustering and does not require threshold determination, However, due to the special distribution of the polarization coherence matrix, the construction method of the similarity matrix is ​​limited. At the same time, the Gaussian kernel parameters need to be manually set accurately according to experience, and the calculation cost is high.

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