| 基于多特征对象的高分辨率遥感影像分类方法及其应用 |
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| 引用本文： | 蔡银桥,毛政元.基于多特征对象的高分辨率遥感影像分类方法及其应用[J].国土资源遥感,2007,18(1):77-81. |
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| 作者姓名： | 蔡银桥 毛政元 |
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| 作者单位： | 福州大学空间数据挖掘与信息共享教育部重点实验室,福建省空间信息工程研究中心,福州,350002 |
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| 摘 要： | 提出了基于多特征对象的高分辨率遥感影像分类方法，分析了该方法相对于基于像元的和单纯依靠光谱特征的传统处理方式所具有的优势，总结了该方法的特点，并给出了相关实验结果。实验表明，对于高分辨率遥感影像，基于多特征对象的分类技术能产生较好的结果。
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| 关 键 词： | 遥感影像 影像分割 多特征 对象 eCognition |
| 文章编号： | 1001-070X（2007）01-0077-05 |
| 收稿时间： | 2006-06-27 |
| 修稿时间： | 2006-06-272006-08-18 |
A METHOD FOR CLASSIFICATION OF HIGH RESOLUTION REMOTELY SENSED IMAGES BASED ON MULTI-FEATURE OBJECTS AND ITS APPLICATION |
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| CAI Yin-qiao,MAO Zheng-yuan.A METHOD FOR CLASSIFICATION OF HIGH RESOLUTION REMOTELY SENSED IMAGES BASED ON MULTI-FEATURE OBJECTS AND ITS APPLICATION[J].Remote Sensing for Land & Resources,2007,18(1):77-81. |
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| Authors: | CAI Yin-qiao MAO Zheng-yuan |
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| Institution: | Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Center, Fuzhou University, Fuzhou 350002, China |
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| Abstract: | This paper puts forward a classification method for high resolution remotely sensed images based on multi -feature objects, analyzes its advantages in comparison with the traditional pixel- based means which completely depend on spectral information. A case study related to the classification method is described, and the result shows that the new technique based on multi -feature objects is more efficient than the pixels -based methods. |
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| Keywords: | Remotely sensed image Image segmentation Multi - features Object eCognition |
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