Unsupervised Change Detection in Multispectral Remotely Sensed Imagery With Level Set Methods

@article{Bazi2010UnsupervisedCD,
  title={Unsupervised Change Detection in Multispectral Remotely Sensed Imagery With Level Set Methods},
  author={Yakoub Bazi and Farid Melgani and Hamed D. Al-Sharari},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2010},
  volume={48},
  pages={3178-3187}
}
In this paper, the unsupervised change-detection problem in remote sensing images is formulated as a segmentation issue where the discrimination between changed and unchanged classes in the difference image is achieved by defining a proper energy functional. The minimization of this functional is carried out by means of a level set method which iteratively seeks to find a global optimal contour splitting the image into two mutually exclusive regions associated with changed and unchanged classes… CONTINUE READING
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