| 一种联合光谱和纹理特征的滩涂提取技术 |
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| 引用本文： | 赵亮,王淑香,李润生.一种联合光谱和纹理特征的滩涂提取技术[J].海洋测绘,2015(5):60-62. |
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| 作者姓名： | 赵亮 王淑香 李润生 |
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| 作者单位： | 61175 部队,江苏 南京 210049;解放军信息工程大学 地理空间信息学院,河南 郑州 450052 |
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| 摘 要： | 提出一种联合光谱和纹理特征的支持向量机分类算法,先通过计算灰度共生矩阵得到纹理影像,然后将纹理波段与光谱波段进行叠加形成一幅多波段影像,再使用支持向量机分类算法对该影像进行分类,从而得到最终的滩涂提取结果。实验结果表明,该方法对于滩涂及周边地物具有较好的分类效果。
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| 关 键 词： | 遥感影像 滩涂 光谱特征 纹理特征 支持向量机 |
A Joint Spectral and Texture Features Supported Tidal Flat Extraction Method |
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| ZHAO Liang,WANG Shuxiang,LI Runsheng.A Joint Spectral and Texture Features Supported Tidal Flat Extraction Method[J].Hydrographic Surveying and Charting,2015(5):60-62. |
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| Authors: | ZHAO Liang WANG Shuxiang LI Runsheng |
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| Institution: | 61175 Troops,Nanjing 210049 ,China;School of Surveying and Mapping,Information Engineering University,Zhengzhou 450052 ,China |
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| Abstract: | Tidal flat is an important land and space resources.Using the remote sensing image to extract the tidalflat is an effective way of tidal flat resources management.This paper presents a joint spectral and texture featuresSVM classification algorithm,which first gets the texture image by calculating the GLCM,and subsequentlysuperimposes texture band and spectral band to form one new image for classification,and then applies thesupport vector machine classification algorithm to the new generated image to get the final tidal flat extractionresults.Experimental results prove that the proposed method is good for tidal flat extraction and classification. |
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