Title :
Interactive segmentation of high resolution synthetic aperture radar data by tree-structured MRF
Author :
Gaetano, R. ; Amitrano, D. ; Masi, G. ; Poggi, G. ; Ruello, G. ; Verdoliva, L. ; Scarpa, G.
Author_Institution :
DIETI, Univ. Federico II of Naples, Naples, Italy
Abstract :
Reliable segmentation of SAR images requires some forms of user supervision: we resort here to the interactive version of the Tree-Structured Markov Random Field (TS-MRF) segmentation suite. The TS-MRF model, and the associated segmentation tool, provide a flexible and spatially adaptive description of the data. In the interactive version, the user can drive the process based on the inspection of the current result, deciding step-by-step which direction to take, and switching from one segmentation modality to another. Experiments with the segmentation and classification of multitemporal SAR images prove the potential of the interactive approach and of the TS-MRF tool.
Keywords :
Markov processes; image classification; image resolution; image segmentation; radar imaging; random processes; synthetic aperture radar; SAR image segmentation; TS-MRF model; high resolution synthetic aperture radar data; interactive segmentation; multitemporal SAR image classification; tree-structured Markov random field model; Adaptation models; Data models; Image resolution; Image segmentation; Inspection; Remote sensing; Synthetic aperture radar; MRF; SAR; classification; interactive; segmentation; supervised;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6947295