In the context of sea monitoring, an important processing step is image segmentation. In this paper, the authors propose a new segmentation method that combines fuzzy and graphbased theories. The algorithm, starting from a single source element belonging to the region of interest, proceeds with a propagation mechanism that aims at finding a Minimum Path Spanning Tree (MPST). The process is automatic, unsupervised, adaptive to the image content and independent from the order of analysis. A TerraSAR-X image and Cosmo-SkyMed images are used for the experiments. The considered applications are oil spill detection, sea surface analysis, and ship detection.
A fuzzy graph-based segmentation for marine and maritime applications in SAR images
GEMME, LAURA;DELLEPIANE, SILVANA
2015-01-01
Abstract
In the context of sea monitoring, an important processing step is image segmentation. In this paper, the authors propose a new segmentation method that combines fuzzy and graphbased theories. The algorithm, starting from a single source element belonging to the region of interest, proceeds with a propagation mechanism that aims at finding a Minimum Path Spanning Tree (MPST). The process is automatic, unsupervised, adaptive to the image content and independent from the order of analysis. A TerraSAR-X image and Cosmo-SkyMed images are used for the experiments. The considered applications are oil spill detection, sea surface analysis, and ship detection.File | Dimensione | Formato | |
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A fuzzy graph-based segmentation for marine and maritime applications in SAR imagesIGARSS2015.pdf
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