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Mumford and Shah Model and its Applications to Image Segmentation andImage Restoration

  • Leah Bar
  • Tony F. Chan
  • Ginmo Chung
  • Miyoun Jung
  • Nahum Kiryati
  • Rami Mohieddine
  • Nir Sochen
  • Luminita A. Vese

Abstract

We present in this chapter an overview of the Mumford and Shah model for image segmentation. We discuss its various formulations, some of its properties, the mathematical framework, and several approximations. We also present numerical algorithms and segmentation results using the Ambrosio–Tortorelli phase-field approximations on one hand, and using the level set formulations on the other hand. Several applications of the Mumford–Shah problem to image restoration are also presented.

Keywords

Image Restoration Impulse Noise Impulsive Noise Recovered Image Blur Kernel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Leah Bar
    • 1
  • Tony F. Chan
    • 2
  • Ginmo Chung
    • 3
  • Miyoun Jung
    • 4
  • Nahum Kiryati
    • 5
  • Rami Mohieddine
    • 6
  • Nir Sochen
    • 7
  • Luminita A. Vese
    • 8
  1. 1.University of MinnesotaMinnesotaUSA
  2. 2.University of California Los AngelesLos AngelesUSA
  3. 3.Nanyang Technological UniversitySingaporeSingapore
  4. 4.University of California Los AngelesLos AngelesUSA
  5. 5.Tel Aviv UniversityTel AvivIsrael
  6. 6.University of California Los AngelesLos AngelesUSA
  7. 7.Tel Aviv UniversityTel AvivIsrael
  8. 8.University of California Los AngelesLos AngelesUSA

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