DocumentCode :
1123044
Title :
Markov random field on region adjacency graph for the fusion of SAR and optical data in radargrammetric applications
Author :
Tupin, Florence ; Roux, Michel
Author_Institution :
GET-Telecom Paris, France
Volume :
43
Issue :
8
fYear :
2005
Firstpage :
1920
Lastpage :
1928
Abstract :
This paper deals with the estimation of an elevation model using a pair of synthetic aperture radar (SAR) images and an optical image in semiurban areas. The proposed method is based on a Markovian regularization of an elevation field defined on a region adjacency graph (RAG). This RAG is obtained by oversegmenting the optical image. The support for elevation hypotheses is given by the structural matching of features extracted from both SAR images. The regularization model takes into account discontinuities of buildings thanks to an implicit edge process. Starting from a good initialization, optimization is obtained through an iterated conditional mode algorithm.
Keywords :
geophysical signal processing; geophysical techniques; image segmentation; remote sensing by radar; sensor fusion; synthetic aperture radar; 3D reconstruction; Markov random field; Markovian regularization; SAR data; SAR image; data fusion; elevation model estimation; feature extraction; iterated conditional mode algorithm; optical data; optical image oversegmentation; radargrammetry; region adjacency graph; semiurban area; structural matching; synthetic aperture radar; Adaptive optics; Image reconstruction; Laser radar; Markov random fields; Optical distortion; Optical interferometry; Optical sensors; Spaceborne radar; Synthetic aperture radar; Urban areas; High-resolution synthetic aperture radar (SAR) images; Markov random field (MRF); radargrammetry; three-dimensional reconstruction; urban areas;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2005.852080
Filename :
1487649
Link To Document :
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