遥感图像的特征包括光谱特征(Spectral features)、空间几何特征(geometrical features)、纹理特征(Texture features)和辅助数据(auxiliary data)。本次提取的是遥感图像的纹理特征。 纹理特征(Texture extraction) 纹理:地物颜色和灰度的某种变化特征,在图像中局部呈现不规则变化,而在整体和宏观上表现出某种规律性的图斑。不...
Visualization of all features was achieved using ArcGIS. The results demonstrate significant associations between all GLCM texture features, except for correlation, and the parametric measures of E RD α T f . Notably, entropy shows the strongest correlations with E RD α T...
GLCM问题记录 Texture Features: Texture contains importantinformation in image classification, as it represents the contentof many real-world images. Textures are characteristic intensity(or color) variations that typically originate from roughness ofobject surfaces (Davies, 2008). As a powerful source of...
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 ...
More information can be found in the two papers: Haralick et. al, 'Textural Features for Image Classification',http://doi.org/10.1109/TSMC.1973.4309314and Conners, et al, Segmentation of a high-resolution urban scene using texture operators',http://doi.org/10.1016/0734-189X(84)90197-X. ...
ofgreatguidingimportanceforthepracticalapplicationofimagetexturefeatures. 【Keywords】gray-levelco-occurrencematrix;texturefeature;imageclassification 0引言 近20年来,随着计算机技术的迅速发展以及机 器视觉系统在生产过程、农产品质量检测、国防安 全、交通管理等领域的应用,纹理图像分析技术正 在成为机器视觉领域的热点...
特征提取灰度共生矩阵(GLCM)第十四讲遥感图像分类 RemoteSensingImageClassification 主要内容 一、遥感图像分类概述二、监督分类三、非监督分类四、遥感图像分类的新方法五、分类后处理和精度分析 一、遥感图像分类概述 1.遥感图像分类概念 •遥感图像计算机分类：是通过模式识别理论，利用计算机 将遥感图像上的每个像元或...
Novel Method for Color Textures Features Extraction based on GLCM. Radioengineering 2007;4(16):64-67. [44] Hu, Y.. Unsupervised Texture Classification by Combining Multi-Scale Features and K- Means Classifier. In: Chinese Conference on Pattern Recognition. 2009, p. 1-5.Benco M, Hudec R. ...
Performance of topological texture features to classify fibrotic interstitial lung disease patterns Texture features were extracted using statistical features (Stat), six properties calculated from gray-level co-occurrence matrices (GLCMs), Minkowski ... MB Huber,MB Nagarajan,G Leinsinger,... - 《Medi...
The tendency of CON, COR, DIS and HOM to vary with window size was significantly affected by orientation. This study can help with parameter selection when texture features from high resolution imagery are used to estimate broad-leaved forest structure information....