Texture feature fusion for high resolution satellite image classification

被引：0

作者：

Zhao, YD ^{[1
]}

Zhang, LP ^{[1
]}

Li, PX ^{[1
]}

机构：

[1] Wuhan Univ, LIESMARS, Wuhan 430079, Peoples R China

来源：

Computer Graphics, Imaging and Vision: New Trends | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Multi-channel Gabor filters (MCGF) and Markov random fields (MRF) have been demonstrated to be quite effective for texture analysis. In this paper, MCGF and MRF features are respectively extracted from input texture images by means of the two above techniques. A MCGF/MRF feature fusion algorithm for texture classification is proposed The fused MCGF/MRF features achieved by this novel algorithm have much higher discrimination than either the pure features or the combined features without selection, according to the Fisher criterion and classification accuracy. The stability and effectiveness of the proposed algorithm are verified on samples of Brodatz and QuickBird images.

引用

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页码：19 / 23

页数：5

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