The semivariogram in comparison to the co-occurrence matrix for classification of image texture

被引:115
作者
Carr, JR [1 ]
de Miranda, FP
机构
[1] Univ Nevada, Dept Geol Sci, Reno, NV 89557 USA
[2] Petroleo Brasileiro SA, CENPES, BR-21949900 Rio De Janeiro, Brazil
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 1998年 / 36卷 / 06期
关键词
correlation; covariance analysis; image classification; image texture analysis; pattern classification;
D O I
10.1109/36.729366
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Semivariogram functions are compared to cooccurrence matrices for classification of digital image texture, and accuracy is assessed using test sites, Images acquired over the following six different spectral bands are used: 1) SPOT HRV, near infrared; 2) Landsat thematic mapper (TM), visible red; 3) India Remote Sensing (IRS) LISS-II, visible green; 4) Magellan, Venus, S-band microwave; 5) shuttle imaging radar (SIR)-C, X-band microwave; 6) SIR-C, L-band microwave. The semivariogram textural measure provides a larger classification accuracy than a classifier based on a co-occurrence matrix for the microwave images and a smaller classification accuracy for the optical images.
引用
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页码:1945 / 1952
页数:8
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