DocumentCode :
298444
Title :
Evaluation on SPOT data of classification algorithms based on Markovian modelization
Author :
Cubero-Castan, E. ; Pons, I. ; Zerubia, J.
Author_Institution :
CNES, Toulouse, France
Volume :
1
fYear :
34881
fDate :
10-14 Jul1995
Firstpage :
115
Abstract :
CNES (French Space Agency) has developed a research program related to SPOT imagery to deal with cartography topics. Many studies, conducted with different laboratories, are intended to work on remote sensing data. The main purpose of the present research is information extraction (network extraction, urban area extraction, segmentation, etc.) One of these studies, made in collaboration with INRIA Sophia Antipolis, intends to classify remote sensing images using MRF (Markov random field) modelization. The paper presents an experiment, conducted by GEOSYS, on crop surveys. An evaluation of the MRF based algorithms is proposed to estimate the results in a supervised context, in order to validate this new approach. A comparison between the proposed methods and standard classification techniques have been done on multispectral SPOT data (XS1, XS2, XS3)
Keywords :
Markov processes; cartography; farming; image classification; random processes; remote sensing; Markov random field; Markovian modelization; cartography; classification algorithms; crop surveys; information extraction; multispectral SPOT data; remote sensing data; Classification algorithms; Collaborative work; Crops; Data mining; Image segmentation; Laboratories; Passive optical networks; Remote sensing; Testing; Urban areas;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
Conference_Location :
Firenze
Print_ISBN :
0-7803-2567-2
Type :
conf
DOI :
10.1109/IGARSS.1995.519664
Filename :
519664
Link To Document :
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