/Change-Detection-PCA-KMeans

Unsupervised Change Detection Algorithm using PCA and K-Means Clustering

Primary LanguageMATLAB

Unsupervised Change Detection using PCA and K-Means Clustering

Le Duc Khai
Ho Chi Minh City, Vietnam   
Bachelor in Biomedical Engineering at FH Aachen - University of Applied Sciences, Germany

Released on 01.04.2019.

Abstract

The proposed algorithm detects changes between 2 satellite images using Principle Component Analysis (PCA) and K-Means Clustering.

Implementation info

Implementation is based on this scientific paper:

Turgay Celik
"Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and k-Means Clustering"
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 6, NO. 4, OCTOBER 2009
DOI: 10.1109/LGRS.2009.2025059

Message

The following codes are implemented only for PERSONAL USE, e.g improving programming skills in the domain of Image Processing and Computer Vision.
If you use this algorithm, please cite the paper mentioned above to support the authors.