Refereed full papers (journals, book chapters, international conferences)

1998

@inproceedings{RSD1998,
	vgclass =	{refpap},
	author =	{H. Rehrauer and K. Seidel and M. Datcu},
	title =	{Multiscale Image Segmentation with a Dynamic Label Tree},
	editor =	{T. I. Stein},
	booktitle =	{IEEE International Geoscience and Remote Sensing Symposium, (IGARSS'98)},
	pages =	{1772--1774},
	year =	{1998},
	url =	{ftp://ftp.vision.ee.ethz.ch/publications/1998/postscripts/iga98_rehrauer.ps.gz},
	abstract =	{Automatic information extraction from satellite images is the
	base of remote sensing image archives with content-based query services.
	Pyramidal image models based on multiscale Markov random fields in
	combination with a texture model proved to yield good classification and
	segmentation results. The texture model is used for initial soft
	classification and then the optimal segmentation given the classification
	is found using a hierarchical process. Segment probabilities are calculated
	in a fine-to-rough analysis and segmentation is performed by a
	rough-to-fine decision algorithm. Previously proposed models optimise the
	strength of the dependencies in a fixed hierarchical structure. In our
	model we allow the dependencies to switch, so that the hierarchical
	structure itself is optimised. Our model is exactly tractable, achieves
	very smooth segmentations, even at coarse scale, and can be fast
	computed.},
}