Hyperspectral change detection with IR-MAD and initial change mask

Prashanth Marpu*, Paolo Gamba, Jon A. Benediktsson

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

5 Citations (Scopus)

Abstract

An adaptation of the previously published iteratively reweighted multivariate alteration detection (IR-MAD) method is presented in this article in the context of hyperspectral change detection. The fact that IR-MAD transformation is invariant to linear transformations is exploited in this work. First, some change pixels are eliminated based on the principal component analysis (PCA) of the difference image and then IR-MAD method is applied to the rest of the pixels after feature reduction using the PCA. The method is demonstrated on a bitemporal hyperspectral dataset. The results show good correlation with ground truth.

Other keywords

  • Change detection
  • IR-MAD
  • PCA

Fingerprint

Dive into the research topics of 'Hyperspectral change detection with IR-MAD and initial change mask'. Together they form a unique fingerprint.

Cite this