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An inverse problem approach for the segmentation of the snow cover in satellite images

M. Datcu, D. Luca and K. Seidel
Future Trends in Remote Sensing , 17th EARSeL Symposium 1997, Lyngby, Denmark
1997

Abstract

A new model for the correction of topographic effects in satellite images of rough terrain is described. The model simulates a synthetic image of the scene using a computer graphics approach which combines ray-tracing techniques with radiosity methods. Computation is structured on three levels: a macro level in which the image is described by the Digital Elevation Model and the light source, a meso-scale in which the model simulates the integration effect of the imaging sensor and a micro-scale which is characterized by the reflectance of the snow cover (specular and diffuse). The parameters of the model are tuned with a gradient search to fit real images acquired by the Landsat-TM sensor. The results show a better accuracy than the classical "cosine of incidence" and Minnaert models. Additionally a new technique based on maximum entropy estimation is used to determine the reflectance function of snow and compare it with the one predicted by our model.


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@InProceedings{eth_biwi_00128,
  author = {M. Datcu and D. Luca and K. Seidel},
  title = {An inverse problem approach for the segmentation of the snow cover in satellite images},
  booktitle = {Future Trends in Remote Sensing , 17th EARSeL Symposium 1997, Lyngby, Denmark},
  year = {1997},
  editor = {P. Gudmandsen},
  publisher = {A. A. Balkema Rotterdam/Brookfield},
  keywords = {remote sensing, model-based, optimization, rendering, simulation, DEM/DTM, Landsat}
}