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On the accuracy of snow cover segmentation in optical satellite images

D. Luca, K. Seidel and M. Datcu
A Scientific Vision for Sustainable Development, IGARSS'97
1997

Abstract

The paper presents a comparison of current algorithms for snow area segmentation in optical satellite images. This comparison addresses the accuracy of the "forward model" used and the information theoretical aspects characterizing the detection/segmentation algorithms. Comparatively we introduce and a new approach: the segmentation of the snow cover as an ill-posed inverse problem and its solution in the frame of the Bayesian inference.


Download in postscript format
@InProceedings{eth_biwi_00113,
  author = {D. Luca and K. Seidel and M. Datcu},
  title = {On the accuracy of snow cover segmentation in optical satellite images},
  booktitle = {A Scientific Vision for Sustainable Development, IGARSS'97},
  year = {1997},
  editor = {T. I. Stein},
  keywords = {remote sensing, model-based, optimization, rendering, simulation, DEM/DTM, Landsat}
}