搜索资源列表
PCA
- PCA_进行indian_pines数据集合分类。((use PCA to classify the indian_pines data with train and test data in the rar))
chengxu
- 用于高光谱图像处理的matlab程序,包括图像融合,降维和图像的极大似然分类程序(Matlab program for hyperspectral image processing, including image fusion, dimension reduction, and maximum likelihood classification of images)
processing
- 包括遥感图像分类(监督和非监督)、分类后处理、NDVI、波段运算、颜色转换、光谱分析等等。(It includes remote sensing image classification (supervised and unsupervised), post-processing classification, NDVI, band operation, color conversion, spectral analysis and so on.)
Bsqview原型+加入NDVI+加入最小距离法+Kmeans+PPI
- 高光谱处理、分类、NDVI计算。。。。。。。。。。。。。。。。。。。。(Hyperspectral image processing, classification and NDVI calculation)
spectralmatrix_msc_sgolay
- 今日对光谱数据预处理中的MSC(多元散射校正)和SG(0阶、高阶)平滑进行了学习,参考书目是李志刚老师著的《光谱数据处理与定量分析技术》(原理介绍较为详细)并结合CSDN和联合开发网上下载的代码进行了简单的matlab编程。代码稍后上传,介绍详细,感兴趣的可以去看看。(Today, MSC (Multiple Scattering Correction) and SG (0th order, high order) smoothing in spectral data preprocessing
CNN_HSIC-master
- CNN高光谱图像分类,包含1D,2D,3D(CNN hyperspectral image classification)
msc
- 可对高光谱数据进行多元散射校正处理,平滑光谱去噪(Multi-scatter correction processing for hyperspectral data, smooth spectral denoising)
建模
- 利用matlab2012a,制作两个excel表格,一个是建模集train,另一个是验证集test,然后就可以构建出人工神经网络模型bp,之后再用验证集做外部验证。(Using MATLAB 2012a, two excel tables are made, one is the modeling set train, the other is the validation set test, then the artificial neural network model BP can be
hyper-master
- 用于高光谱异常检测,一种很好的可识别的RX算法(A good recognizable RX algorithm for hyperspectral anomaly detection we need Reduce Dimension by Principal Component Analysis)
random forest
- 利用R语言编程实现高光谱遥感的随机森林分类(Random Forest Classification Based on Hyperspectral Remote Sensing Using R Language Programming)
SVM
- SVM分类用于高光谱遥感图像分类、预测....................(SVM classification for classification and prediction of hyperspectral remote sensing images)
cem-mnf
- 基于最小噪声分离变换的CEM算法,首先经过高通滤波处理后,进行MNF变换,对变换完成后的图像进行CEM处理,主要用于高光谱的目标探测
Semantic-Segmentatiomaster
- 遥感图像的语义分割,分别使用Deeplab V3+(Xception 和mobilenet V2 backbone)和unet模型(Semantic segmentation of remote sensing images using Deeplab V3+ (Xception and Mobilenet V2 backbone) and UNET models)
SatelliteImageClassification-master
- GAN网络用于做高光谱图像分类的算法,亲测可以使用,最近写的(GAN network is used to do hyperspectral image classification algorithm, pro - test can be used, recently written)
SuperPCA-master
- 高光谱图像无监督特征提取的超像素PCA方法(A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery)
DR_CNN_scripts
- 高光谱图像分类,利用CNN,里面有全套的流程,包括数据处理,样本生成,测试,精度评价。(hyperspectral image classification based on CNN)
CNN_Hyperspectral_Classification-master
- 使用神经网络进行训练,对高光谱普图像进行分类(Using neural network to train and classify hyperspectral images)
无信息变量消除法提取特征
- UVE提取特征,数据为高光谱数据,感兴趣区域数据,最后一列为标签(Uve extracts features, hyperspectral data, region of interest data, and the last column is label)
GA提取特征
- GA提取特征,数据为高光谱数据,感兴趣区域数据,最后一列为标签(GA extracts features, hyperspectral data, region of interest data, and the last column is label)
纯像元指数
- 高光谱图像端元提取ppi算法,最基本的算法实现。