@inproceedings {362,
	title = {SAR sea ice image segmentation based on edge-preserving watersheds},
	booktitle = {4th Annual Canadian Conference on Computer and Robot Vision},
	year = {2007},
	month = {05/2007},
	address = {Montreal, Quebec, Canada},
	abstract = {<p>This paper presents a hybrid method for the segmentation of SAR sea ice images, which consists of an initial watershed segmentation followed by a region merging. Iterative bilateral filtering is used to reduce speckle noise and suppress irrelevant image details, which can significantly alleviate oversegmentation of watersheds. Since edges are well preserved by bilateral filtering, the watershed algorithm is capable of precisely locating object boundaries. Final segmentation is accomplished by applying an iterative region merging on the watershed regions by taking into account local boundary strengths and regional statistics. The efficiency of the proposed method has been demonstrated on the segmentation of SAR sea ice images. In comparison with traditional watershed algorithm, our method achieves better performance in identifying filament structures such as leads.</p>
},
	keywords = {edge-preserving watersheds, filtering theory, image segmentation, iterative bilateral filtering, iterative methods, local boundary strengths, radar imaging, region merging, regional statistics, SAR sea ice image segmentation, speckle noise, statistical analysis, synthetic aperture radar},
	doi = {http://dx.doi.org/10.1109/CRV.2007.58},
	author = {X Yang and D A. Clausi}
}
