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A new image formation model for the segmentation of the snow cover in mountainous areas

M. Datcu, D. Luca and K. Seidel
EARSeL - Advances in Remote Sensing
Vol. 5, pp. 55--63, 1997


The paper describes a new model for the correction of topographic effects in satellite images of snow covered rough terrain. The model simulates a synthetic image of the scene using a computer graphics approach which combines ray-tracing techniques with radiosity methods to render accurately both diffuse and specular reflections. Computation is structured on three levels: a macro level in which the image is described by the Digital Elevation Model, the position and physical properties of the light source and global atmospheric effects, 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 reflections). After setting up the model, its parameters are tuned with a gradient search to fit real images acquired from the Landsat-TM sensor. The results show a good coincidence between synthetic and real images and prove the validity of the suggested image formation model.

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  author = {M. Datcu and D. Luca and K. Seidel},
  title = {A new image formation model for the segmentation of the snow cover in mountainous areas},
  journal = {EARSeL - Advances in Remote Sensing},
  year = {1997},
  month = {},
  pages = {55--63},
  volume = {5},
  number = {},
  keywords = {snow segmentation, modeling, ray-tracing/radiosity, remote sensing}