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Characteristic Scale Detection in Remote-sensing Data

H. Rehrauer, K. Seidel and M. Datcu
IEEE Intern. Geoscience and Remote Sensing Symposium IGARSS'99


Texture models are widely in use for image content description. In remote-sensing images textures occur at very different scales, requiring the application of multiple texture models. We present an algorithm based on a multi-scale random field model to detect the characteristic scales at which textures are present, so that texture models can be applied to a few selected scales only. The algorithm is compared to two other models based on Haralick and wavelet features. Such a scale selection scheme reduces computation time and minimizes the index size. Both are critical parameters in the design of large remote-sensing databases with content-based retrieval services.

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  author = {H. Rehrauer and K. Seidel and M. Datcu},
  title = {Characteristic Scale Detection in Remote-sensing Data},
  booktitle = {IEEE Intern. Geoscience and Remote Sensing Symposium IGARSS'99},
  year = {1999},
  keywords = {remote sensing,scale space,dynamic,non-parametric,texture}