PPI-SVM-Iterative FLDA Approach to Unsupervised Multispectral Image Classification.
Hsian-Min ChenChinsu LinShih-Yu ChenChia-Hsien WenClayton Chi-Chang ChenYen Chieh OuyangChein-I ChangPublished in: IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2013)
Keyphrases
- multispectral
- image classification
- svm classifier
- support vector machine svm
- remotely sensed data
- support vector
- remote sensing images
- remote sensing
- spatial resolution
- hyperspectral
- multispectral images
- image data
- protein protein interactions
- support vector machine
- image analysis
- remote sensing data
- semi supervised
- feature extraction
- multispectral satellite images
- satellite images
- multi band
- hyperspectral imagery
- feature selection
- supervised learning
- image features
- training data
- spectral images
- land cover classification
- multispectral imaging
- land cover
- unsupervised learning
- spectral characteristics
- high spatial resolution
- supervised classification
- spectral bands
- remotely sensed images
- hyperspectral images
- machine learning