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Remote Sens. 2018, 10(4), 533; doi:10.3390/rs10040533

An Approach for Unsupervised Change Detection in Multitemporal VHR Images Acquired by Different Multispectral Sensors

1
Fondazione Bruno Kessler, Center of Information and Communication Technology, I-38123 Trento, Italy
2
Department of Information Engineering and Computer Science, Università degli Studi di Trento, I-38123 Trento, Italy
*
Authors to whom correspondence should be addressed.
Received: 1 February 2018 / Revised: 15 March 2018 / Accepted: 29 March 2018 / Published: 30 March 2018
(This article belongs to the Special Issue Analysis of Multi-temporal Remote Sensing Images)
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Abstract

This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR) optical images acquired by different multispectral sensors. The proposed approach, which is inspired by a recent framework developed to support the design of change-detection systems for single-sensor VHR remote sensing images, addresses and integrates in the general approach a strategy to effectively deal with multisensor information, i.e., to perform change detection between VHR images acquired by different multispectral sensors on two dates. This is achieved by the definition of procedures for the homogenization of radiometric, spectral and geometric image properties. These procedures map images into a common feature space where the information acquired by different multispectral sensors becomes comparable across time. Although the approach is general, here we optimize it for the detection of changes in vegetation and urban areas by employing features based on linear transformations (Tasseled Caps and Orthogonal Equations), which are shown to be effective for representing the multisensor information in a homogeneous physical way irrespectively of the considered sensor. Experiments on multitemporal images acquired by different VHR satellite systems (i.e., QuickBird, WorldView-2 and GeoEye-1) confirm the effectiveness of the proposed approach. View Full-Text
Keywords: Very High Resolution images; change detection; multisensor; multitemporal; Change Vector Analysis; Tasseled Cap; Remote Sensing Very High Resolution images; change detection; multisensor; multitemporal; Change Vector Analysis; Tasseled Cap; Remote Sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Solano-Correa, Y.T.; Bovolo, F.; Bruzzone, L. An Approach for Unsupervised Change Detection in Multitemporal VHR Images Acquired by Different Multispectral Sensors. Remote Sens. 2018, 10, 533.

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