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In this Letter, an unsupervised algorithm for detecting changes in multi-spectral and multi-temporal remotely-sensed images is presented. Such an algorithm makes it possible to reduce the effects of 'registration noise' on the accuracy of change detection. In addition, it can be used to reduce the typologies of detected changes in order to better locate the changes under investigation.
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Bruzzone et al. (1997) studied this question.
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