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Meta Features for Remote Sensing Image Content Indexing

K. Seidel, M. Schröder, H. Rehrauer and M. Datcu
IEEE International Geoscience and Remote Sensing Symposium, IGARSS'98
1998

Abstract

In this paper we present a general formalism to model several levels of meta information on spatial content. In particular, we expand on a two-level procedure of Bayesian inference: model fitting and model selection. We study five cases of extraction of spatial information from remote sensing images using this scheme. In this way, we put together pieces of information obtained from different levels of interpretation of the original image data.


Download in postscript format
@InProceedings{eth_biwi_00146,
  author = {K. Seidel and M. Schr\"oder and H. Rehrauer and M. Datcu},
  title = {Meta Features for Remote Sensing Image Content Indexing},
  booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS'98 },
  year = {1998},
  pages = {1022--1024},
  editor = {T. I. Stein},
  keywords = {remote sensing, image indexing, segmentation, Bayesian statistics, database}
}