Energy minimization based segmentation and denoising using a multilayer level set approach

  • Authors:

  • Ginmo Chung;Luminita A. Vese

  • Affiliations:

  • Department of Mathematics, University of California, Los Angeles, Los Angeles, CA;Department of Mathematics, University of California, Los Angeles, Los Angeles, CA

  • Venue:
  • EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
  • Year:
  • 2005

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Abstract

This paper is devoted to piecewise-constant segmentation of images using a curve evolution approach in a variational formulation. The problem to be solved is also called the minimal partition problem, as formulated by Mumford and Shah [20]. The proposed new models are extensions of the techniques previously introduced in [9], [10], [27]. We represent here the set of boundaries of the segmentation implicitly, by a multilayer of level-lines of a continuous function. In the standard approach of front propagation, only one level line is used to represent the boundary. The multilayer idea is inspired from previous work on island dynamics for epitaxial growth [14], [4]. Using a multilayer level set approach, the computational cost is smaller and in some applications, a nested structure of the level lines can be useful.