Unsupervised Change-Detection Methods for Remote-Sensing Images
نویسنده
چکیده
An unsupervised change detection problem can be viewed as a classification problem with only two classes corresponding to the change and no-change areas, respectively. Thanks to its simplicity, image differencing is a widely used approach to change detection. It is based on the idea of generating a difference image that represents the modulus of the spectral change vector associated with each pixel in the study area. To separate the “change” and “no-change” classes in the difference image, a simple thresholding-based procedure can be applied. However, the selection of the best threshold value is not a trivial problem. In the present work, several simple thresholding methods are investigated and compared. The combination of the Expectation-Maximization algorithm with a thresholding method is also performed for the purpose of achieving a better
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