|
|||||
|
|
| 基于灰度共生矩阵的图像纹理特征地物分类应用 | |
| 引用本文： | 李智峰.基于灰度共生矩阵的图像纹理特征地物分类应用[J].地质与勘探,2011,47(3):456-461. |
| 作者姓名： | 李智峰 |
| 作者单位： | 1. 中南大学地学与环境工程学院,湖南长沙,410083 2. 中南大学地学与环境工程学院,湖南长沙410083;有色金属矿产地质调查中心,北京1000123 3. 中科院遥感应用研究所,北京,100101 |
| 基金项目： | 中国地质调查局地质调查项目“甘肃中东部重点成矿带与西藏昌都等矿集区矿山开发多目标遥感调查与监测”地质调查项目(121201916062)资助 |
| 摘 要： | 针对传统遥感影像分类方法的分类精度不高,在分析图像的光谱信息的基础上,对基于灰度共生矩阵的纹理特征在地物分类中的应用进行了研究.本研究利用原始图像进行主成分分析后的前两个主成分,经过编程运算,提取了基于灰度共生矩阵方法的不同测度的纹理特征,将提取的纹理特征作为新的波段,与原始波段进行组合,再对组合图像进行监督分类,探索... |
| 关 键 词： | 遥感影像 纹理 灰度共生矩阵 地物分类 |
| 收稿时间： | 2010/6/27 0:00:00 |
| 修稿时间： | 2010/9/26 0:00:00 |
Application of GLCM-Based Texture Features to Remote Sensing Image Classification |
|
| LI Zhi-feng.Application of GLCM-Based Texture Features to Remote Sensing Image Classification[J].Geology and Prospecting,2011,47(3):456-461. | |
| Authors: | LI Zhi-feng |
| Institution: | (LI Zhi-feng1,ZHU Gu-chang1,2,DONG Tai-feng3) (1.Centre South University,Changsha,Hunan 410083,2.China Non-ferrous Metals Resource Geological Survey,Beijing 100012,3.Chinese Academy of Sciences Institute of Remote Sensing Applications,Beijing 100101) |
| Abstract: | In order to solve the problem of low-accuracy in the conventional classification of remote sensing image classification, a new method based on gray level co-occurrence matrix(GLCM) texture features is presented and utilized. After the principal component analysis, the first two principal components were selected to extract the texture features of different measurements based on gray level co-occurrence matrix. As a new band, the extracted texture features with the original bands were combined by supervised ... |
| Keywords: | remote sensing images texture characteristics gray level co-occurrence matrix(GLCM) classification of ground objects |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
| 点击此处可从《地质与勘探》浏览原始摘要信息 | |
| 点击此处可从《地质与勘探》下载免费的PDF全文 | |