A New Approach to Change Detection in Multispectral Images by Means of ERGAS Index

In this letter, we propose a novel method for unsupervised change detection (CD) in multitemporal Erreur Relative Globale Adimensionnelle de Synthese (ERGAS) satellite images by using the relative dimensionless global error in synthesis index locally. In order to obtain the change image, the index is calculated around a pixel neighborhood (3 $\times$ 3 window) processing simultaneously all the spectral bands available. With the objective of finding the binary change masks, six thresholding methods are selected. A comparison between the proposed method and the change vector analysis method is reported. The accuracy CD showed in the experimental results demonstrates the effectiveness of the proposed method.

• Publication year

  2013

• Venue

  IEEE Geoscience and Remote Sensing Letters

• Publication date

  Unknown publication date

• Fields of study

  Mathematics, Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/LGRS.2012.2193372
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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