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A minimum-cost thresholding technique for unsupervised change detection

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We propose an automatic thresholding technique for difference images in unsupervised change detection. Such a technique takes into account the different costs that may be associated with commission and omission errors in the selection of the decision threshold. This allows the generation of maps in which the overall change-detection cost is minimized, i.e. the more critical kind of error is reduced according to end-user requirements.

Document Type: Research Article


Affiliations: 1: DICA-University of Trento, Via Mesiano 77, I-38050, Trento, Italy 2: DIBE-University of Genoa, Via Opera Pia 11 A, I-16145, Genova, Italy

Publication date: 2000-12-15

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