地质与勘探2011，Vol.47Issue(3)：456-461,6.
基于灰度共生矩阵的图像纹理特征地物分类应用
Application of GLCM-Based Texture Features to Remote Sensing Image Classification
摘要
Abstract
In order to solve the problem of low-accuracy in the conventional classification of remote sensing image classification, a now method based on gray level co-occurrenco matrix( GL CM) 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 classification methods to classify the images. The classification result was compared with the maximum likelihood classification qualitatively and quantitatively. The research results show that a combination of texture features with spectral characteristics can enhance the accuracy of ground object classification, and prove the feasibility and effectiveness of the GLCM-based classification method presented in this paper.关键词
遥感影像/纹理/灰度共生矩阵/地物分类Key words
remote sensing images/ texture characteristics/ gray level co-occurrence matrix( GLCM)/ classification of ground objects分类
信息技术与安全科学引用本文复制引用
李智峰,朱谷昌,董泰锋..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):456-461,6.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. （121201916062）
