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ICCV
2009
IEEE

Power watersheds: a new image segmentation framework extending graph cuts, random walker and optimal spanning forest

10 years 3 months ago
Power watersheds: a new image segmentation framework extending graph cuts, random walker and optimal spanning forest
In this work, we extend a common framework for seeded image segmentation that includes the graph cuts, ran- dom walker, and shortest path optimization algorithms. Viewing an image as a weighted graph, these algorithms can be expressed by means of a common energy func- tion with differing choices of a parameter q acting as an exponent on the differences between neighboring nodes. Introducing a new parameter p that fixes a power for the edge weights allows us to also include the optimal span- ning forest algorithm for watersheds in this same frame- work. We then propose a new family of segmentation algorithms that fixes p to produce an optimal spanning forest but varies the power q beyond the usual water- shed algorithm, which we term power watersheds. Placing the watershed algorithm in this energy mini- mization framework also opens new possibilities for us- ing unary terms in traditional watershed segmentation and using watersheds to optimize more general models of us...
Camille Couprie, Leo Grady, Laurent Najman, Hugues
Added 13 Jul 2009
Updated 12 Jan 2011
Type Conference
Year 2009
Where ICCV
Authors Camille Couprie, Leo Grady, Laurent Najman, Hugues Talbot
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