Corpus ID: 49908740

Coupled dictionary learning for unsupervised change detection between multi-sensor remote sensing images

@article{Ferraris2018CoupledDL,
  title={Coupled dictionary learning for unsupervised change detection between multi-sensor remote sensing images},
  author={Vinicius Ferraris and Nicolas Dobigeon and Yanna Cruz Cavalcanti and Thomas Oberlin and Marie Chabert},
  journal={ArXiv},
  year={2018},
  volume={abs/1807.08118}
}
Archetypal scenarios for change detection generally consider two images acquired through sensors of the same modality. However, in some specific cases such as emergency situations, the only images available may be those acquired through sensors with different characteristics. This paper addresses the problem of unsupervisedly detecting changes between two observed images acquired by different sensors. These sensor dissimilarities introduce additional issues in the context of operational change… Expand
1 Citations
Robust fusion algorithms for unsupervised change detection between multi-band optical images - A comprehensive case study
TLDR
This paper addresses the problem of detecting changes between any two multi-band optical images disregarding their spatial and spectral resolution disparities by modeling the two observed images as spatially and spectrally degraded versions of two (unobserved) latent images characterized by the same high spatial and high spectral resolutions. Expand

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