Improved synthetic aperture radar image spectral clustering algorithm

被引：0

作者：

Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384, China ^{[1
]}

不详 ^{[2
]}

机构：

[1] Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology

[2] Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology

来源：

Guangxue Xuebao | / SUPPL.1卷

关键词：

Affinity function; Automatic clustering; Scaling parameter; Spectral clustering; Synthetic aperture radar image segmentation;

D O I：

10.3788/AOS201232.s128001

中图分类号：

学科分类号：

摘要：

Synthetic aperture radar (SAR) image segmentation is the basis of the image understanding. Combined with the Nyström sampling technique and the graph spectral theory, a new improved algorithm with fast and effective spectral clustering is proposed for the SAR image. Based on the matrix perturbation analysis theory, the automatic determining class number criterion suitable for the SAR image segmentation is constructed. Based on analysis of influence of proportion parameters on the spectral clustering algorithm, according to the global construction characteristics of the SAR image, auto-adaptive neighborhood estimate method of scale parameter is proposed. According to the gray value and the spatial location of each pixel in the SAR image, the affinity function better describing the essence structure of the SAR image is constructed, and then the improved spectral clustering algorithm is researched. The proposed algorithm is applied to the simulation experiment and in the actual SAR image segmentation, and also it is compared with the traditional spectral clustering method.

引用

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