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基于样本自动选择与SVM结合的海岸线遥感自动提取 被引量:46

Automatic extraction of coastline by remote sensing technology based on SVM and auto-selection of training samples
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摘要 利用卫星遥感手段自动、快速、准确地测定海岸线动态信息是遥感应用的一个重要领域,对海域管理规划具有重要意义。由于近岸水体光谱特征受区域环境影响较大,在水陆分离过程中,利用传统的归一化差值水体指数(normalized difference water index,NDWI)阈值分割法时,一部分近岸水体易被错分为陆地,严重影响了岸线提取精度。为此,在NDWI模型的基础上,提出了基于样本自动选择与支持向量机(support vector machine,SVM)的海岸线遥感自动提取算法。首先进行NDWI计算与全局阈值分割,实现水体信息的初步提取;再通过NDWI信息控制初始样本的自动选择;然后利用SVM分类器对水体再次分类,实现海陆分离;最后填充小的陆地水体单元,实现岸线自动跟踪。实验结果表明,该方法能有效增强对近岸水体的识别能力,提高海岸线遥感提取的精度和自动化程度。 The timely and accurate automatic extraction of coastline from satellite remote sensing imagery is one of the important applications of remote sensing technology and has great significance for management planning of the sea area. Because the spectral characteristics of coastal water are susceptible to regional environment, the traditional method of normalized difference water index(NDWI) threshold segmentation may easily misclassify water as land in the process of separation of land and water, which will seriously affect the accuracy of shoreline extraction. In this paper, on the basis of NDWI model, the authors proposed an automatic coastline extraction method based on classification sample auto - selection and support vector machine (SVM). Firstly, through the NDWI calculation and global threshold segmentation, the initial water distribution information is obtained. And then, the classification samples are selected automatically under the control of NDWI information. Thirdly, the water are separated from the land by using SVM classifier. The last step is to fill small terrestrial water body units and track coastline automatically. The experimental results show that this method can effectively enhance the capability of coastal water identification and improve the accuracy and automation of the coastline extraction from remote sensing imager.
出处 《国土资源遥感》 CSCD 北大核心 2013年第2期69-74,共6页 Remote Sensing for Land & Resources
基金 国家自然科学基金项目(编号:40971228 41101041 41201460) 国家科技支撑计划项目(编号:2011BAH06B02) 水利部公益性行业科研专项经费项目(编号:201201092)共同资助
关键词 海岸线 归一化差值水体指数(NDWI) 支持向量机(SVM) 自动提取 coastline normalized difference water index (NDWI) support vector machine (SVM) automatic ex- traction
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