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Proceedings Paper

Hierarchical watershed segmentation based on gradient image simplification
Author(s): François Cokelaer; Mauro Dalla Mura; Jocelyn Chanussot
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Paper Abstract

Watershed is one of the most widely used algorithms for segmenting remote sensing images. This segmentation technique can be thought as a flooding performed on a topographic relief in which the water catchment basins, separated by watershed lines, are the regions in the resulting segmentation. A popular technique for performing a watershed relies on the flooding of the gradient image in which high level values correspond to watershed lines and regional minima to the bottom of the catchment basins. Here we will refer as hierarchical segmentation a decomposition of the segmentation map respecting the nesting property from a finer to a coarser scale i.e. the set of partition lines at a coarser scale should be included in that of the finer scale. From the watershed lines or partitions lines of the gradient image, we propose to perform a simplification using novel operators of mathematical morphology for the filtering of thin and oriented features. By lowering the smallest edges, one can reach a coarser partition of the image. Then, by applying a sequence of progressively more aggressive filters it is possible to generate a hierarchy of segmentations.

Paper Details

Date Published: 8 November 2012
PDF: 6 pages
Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85371O (8 November 2012); doi: 10.1117/12.999358
Show Author Affiliations
François Cokelaer, GIPSA-Lab (France)
Mauro Dalla Mura, GIPSA-Lab (France)
Jocelyn Chanussot, GIPSA-Lab (France)


Published in SPIE Proceedings Vol. 8537:
Image and Signal Processing for Remote Sensing XVIII
Lorenzo Bruzzone, Editor(s)

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