An improved graph-cut-based unsupervised change detection method for multispectral remote-sensing images
Author:
Affiliation:
1. Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, China
2. School of Geography and Tourism, Qufu Normal University, Rizhao, China
Funder
Fundamental Research Funds for the Central Universities
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2021.1881182
Reference31 articles.
1. A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain
2. A Novel Approach to Unsupervised Change Detection Based on a Semisupervised SVM and a Similarity Measure
3. Fast approximate energy minimization via graph cuts
4. Automatic analysis of the difference image for unsupervised change detection
5. Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and $k$-Means Clustering
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