• Home
  • CODES
    • Classification of Hyperspectral Images
    • Classification of Remote Sensing Data
    • Data fusion: hyperspectral + Lidar
    • Hyperspectral Super Resolution
    • Machine Learning in Remote Sensing
    • Pansharpening
    • Registration
    • Spectral Unmixing
  • DATA
  • About us
  • Home
  • CODES
    • Classification of Hyperspectral Images
    • Classification of Remote Sensing Data
    • Data fusion: hyperspectral + Lidar
    • Hyperspectral Super Resolution
    • Machine Learning in Remote Sensing
    • Pansharpening
    • Registration
    • Spectral Unmixing
  • DATA
  • About us
home/Knowledge Base/CODES/Classification of Hyperspectral Images/Fast Forward Feature Selection of Hyperspectral Images for Classification With Gaussian Mixture Models

Fast Forward Feature Selection of Hyperspectral Images for Classification With Gaussian Mixture Models

February 4, 2016

Fast Forward Feature Selection of Hyperspectral Images for Classification With Gaussian Mixture Models [toolbox]
M. Fauvel, C. Dechesne, A. Zullo and F. Ferraty.

Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Volume: 8 , Issue: 6
DOI : 10.1109/JSTARS.2015.2441771
Publication Year: 2015 , Page(s): 2824 – 2831

Tags:gaussian mixture model (GMM)hyperspectral image classificationnonlinear feature selectionparsimony
Attached Files
#
File Type
File Size
Download
1 .pdf 770.15 KB Fauvel_2015_JSTARS
Related Articles
  • DGSSC: A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspectral Imagery
  • Semisupervised Cross-Scale Graph Prototypical Network for Hyperspectral Image Classification
  • Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects
  • Hyperspectral Imagery Classification via Random Multi-Graphs Ensemble Learning
  • SGML: A Symmetric Graph Metric Learning Framework for Efficient Hyperspectral Image Classification
  • More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

Didn't find your answer? Contact Us

Categories
  • CODES
    • Anomaly
    • Change Detection
    • Classification of Hyperspectral Images
    • Classification of Remote Sensing Data
    • Data fusion: hyperspectral + Lidar
    • Data fusion: Hyperspectral + Multispectral
    • Deep Learning
    • Denoising
    • Feature Extraction
    • Graphs
    • Graphs, Manifold
    • Hyperspectral
    • Hyperspectral remote sensing
    • Hyperspectral Super Resolution
    • Infrared
    • Machine Learning in Remote Sensing
    • Multi-modal
    • Object Detection
    • Pansharpening
    • Registration
    • Sequences
    • Spectral Unmixing
    • Super Resolution
    • Synthetic Aperture Radar and Radar Sounder
    • Target Detection
    • Tensor
  • DATA

  Generalized Composite Kernel Framework for Hyperspectral Image Classification

Extended profiles with morphological attribute filters for the analysis of hyperspectral data  

Contact

Mail : Jocelyn Chanussot

Like Us On Facebook
Facebook Pagelike Widget
Follow Us On Twitter
Follow @RemoteOpen
Links

http://www.jocelyn-chanussot.net