DocumentCode :
315092
Title :
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
Link To Document :
بازگشت