Object-Based Spatial Feature for Classification of Very High Resolution Remote Sensing Images

被引:30
|
作者
Zhang, Penglin [1 ]
Lv, Zhiyong [1 ]
Shi, Wenzhong [2 ,3 ]
机构
[1] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
[2] Hong Kong Polytech Univ, Joint Spatial Informat Res Lab, Hong Kong, Hong Kong, Peoples R China
[3] Wuhan Univ, Wuhan 430079, Peoples R China
关键词
Classification of very high resolution (VHR) image; object correlative index (OCI); spatial feature; spectral feature; URBAN AREAS; MORPHOLOGICAL PROFILES; SATELLITE IMAGERY; NEURAL-NETWORK; VHR IMAGES; INFORMATION; EXTRACTION; VEGETATION;
D O I
10.1109/LGRS.2013.2262132
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
This letter presents a novel spatial feature called object correlative index (OCI) to enhance the classification of very high resolution images. This novel method considers the property of an image object based on spectral similarity to construct a useful OCI to describe the spatial information objectively. Compared with the generic features widely used in image classification, the classification approach based on the OCI spatial feature results in higher classification accuracy than those approaches that only consider spectral features or pixelwise spatial features, such as the pixel shape index and mathematical morphology profiles. Experiments are conducted on QuickBird satellite image and aerial photo data, and results confirm that the proposed method is feasible and effective.
引用
收藏
页码:1572 / 1576
页数:5
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