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机构地区:[1]河海大学水文水资源与水利工程科学国家重点实验室,江苏南京210098
出 处:《地理与地理信息科学》2008年第6期46-49,共4页Geography and Geo-Information Science
基 金:河海大学水文水资源与水利工程科学国家重点实验室开放基金项目(2007490911);国家自然科学基金项目(40771039)
摘 要:从遥感影像上提取道路面临如下问题:根据光谱特征分类的图像存在建筑物与道路混淆,受交通工具、行道树等影响易产生道路中的孔洞与道路边缘的毛刺等。该文利用南京市IKONOS高分辨率影像丰富的空间纹理信息,将纹理信息加入原始波段参与分类,可以解决建筑物与道路的混淆问题。另外,道路具有丰富的形态特征,应用数学形态学的相关算法和形状指数,可以很好地去除道路提取过程中产生的各种噪声。Extracting road feature from satellite data can provide immediate, accurate and effective data for traffic geographic in- formation database. It can greatly improve the timeliness of electronic maps, and reduce the cost of electronic map. However, many problems are still to be solved, such as the confusion of existence buildings and roads on the classification images based on the spectral characteristics, and the holes and spurs due to the existence of transports and standing trees. IKONOS high--reso- lution images have rich texture information, so the texture information was added into the original bands to help the classifica- tion in this paper. The approach improved the effect of the classification. On the other hand; the mathematical morphology and shape parameters were used in the classification. According to the result of experimentation, the proposed approach can extract the main roads in the image effectively.
分 类 号:TP75[自动化与计算机技术—检测技术与自动化装置]
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