灰度和纹理特征组合的SAR影像SVM分类

doi:10.3969/j.issn.0255-8297.2012.05.010

Abstract

Abstract:

This paper proposes a set of SVM classification methods based on fusion of gray scale and texture features. A set of experiments are carried out using the SVM classifiers with feature fusion. Both qualitative and quantitative approaches are applied to assess the classification results. Experimental results demonstrate that the proposed approach is effective for SAR image classification with accuracy higher than those obtained by using single texture feature based algorithms.

Key words: SAR image classification, support vector machine (SVM), gray scale, texture, gray level cooccurrence matrix, Gabor filter

CLC Number:

P237

FU Zhong-liang, ZHANG Wen-yuan, MENG Qing-xiang. SAR Image Classification Based on SVM with Fusion of Gray Scale and Texture Features[J]. Journal of Applied Sciences, 2012, 30(5): 498-504.

References

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SAR Image Classification Based on SVM with Fusion of Gray Scale and Texture Features

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