Gibbs random field models for image content characterization

Author

Schröder, Michael ; Seidel, Klaus ; Datcu, Mihai

Author_Institution

Swiss Federal Inst. of Technol., Eidgenossische Tech. Hochschule, Zurich, Switzerland

Volume

1

fYear

1997

fDate

3-8 Aug 1997

Firstpage

258

Abstract

Satellite images contain an enormous amount of spatial information. To capture that information the authors propose, in the framework of a stochastic modelling of the image, the use of Gibbs Markov random fields. They expand on a particular model suitable for the use with typical remote sensing images. They demonstrate the capabilities of that model with two examples. In particular, they perform directed queries for specific spatial information

Keywords

geographic information systems; geophysical signal processing; geophysical techniques; query formulation; query processing; remote sensing; GIS; Gibbs Markov random fields; Gibbs random field model; database searching; directed query formulation; geophysical measurement technique; image content characterization; image processing; land surface; remote sensing; satellite image; spatial information; stochastic model; terrain mapping; Degradation; Image reconstruction; Image segmentation; Lattices; Parameter estimation; Physics; Probability distribution; Remote sensing; Speckle; Statistical distributions;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International

Print_ISBN

0-7803-3836-7

Type

conf

DOI

10.1109/IGARSS.1997.615856

Filename

615856