A Weighted Difference of Anisotropic and Isotropic Total Variation for Relaxed Mumford-Shah Image Segmentation

Abstract

We propose to incorporate a weighted difference of anisotropicand isotropic total variation (TV) norms into a relaxed formulation of the two phase Mumford-Shah (MS) model for image segmentation. We show results exceeding those obtained by the MS model when using the standard TV norm to regularize partition boundaries. In particular, examples illustrating the qualitative differences between the proposed model and the standard MS one are shown. A fast numerical methodis introduced to minimize the proposed model utilizing the difference-of-convex algorithm (DCA) and the primal dual hybrid gradient (PDHG) method.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2016
Accession Number
AD1018372

Entities

People

  • Fredrick Park
  • Jack Xin
  • Yifei Lou

Organizations

  • University of California

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Atmospheric Motion
  • Boundaries
  • Computational Fluid Dynamics
  • Computer Vision
  • Convergence
  • Detectors
  • Dynamic Programming
  • Gaussian Noise
  • Geometry
  • Gray Scale
  • Image Processing
  • Image Segmentation
  • Index Terms
  • Mathematics
  • Universities
  • Video Frames

Fields of Study

  • Mathematics

Readers

  • Computer Vision.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Operations Research