/Hyper-Spectral-Image-Clustering

Qualitative and quantitative evaluation of the performance of clustering algorithms in HSI clustering

Primary LanguageMATLAB

Hyper-Spectral-Image-Clustering

This analysis aims to evaluate the effectiveness of various clustering algorithms in in identifying homogeneous regions within the Salinas valley in california Hyperspectral Image (HSI).

  • Cost function optimization clustering algorithms:
    • K-means
    • Fuzzy c-means
    • Possibilistic c-means
    • Probabilistic clustering(Gaussian Mixture Models)
  • Hierarchical algorithms:
    • Complete-link
    • WPGMC
    • Ward

The Matlab code along with the exported pdf are provided.