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  • Research Article
  • Open Access

Improved Mumford-Shah Functional for Coupled Edge-Preserving Regularization and Image Segmentation

EURASIP Journal on Advances in Signal Processing20062006:037129

  • Received: 11 October 2005
  • Accepted: 18 February 2006
  • Published:


An improved Mumford-Shah functional for coupled edge-preserving regularization and image segmentation is presented. A nonlinear smooth constraint function is introduced that can induce edge-preserving regularization thus also facilitate the coupled image segmentation. The formulation of the functional is considered from the level set perspective, so that explicit boundary contours and edge-preserving regularization are both addressed naturally. To reduce computational cost, a modified additive operator splitting (AOS) algorithm is developed to address diffusion equations defined on irregular domains and multi-initial scheme is used to speed up the convergence rate. Experimental results by our approach are provided and compared with that of Mumford-Shah functional and other edge-preserving approach, and the results show the effectiveness of the proposed method.


  • Information Technology
  • Computational Cost
  • Convergence Rate
  • Quantum Information
  • Image Segmentation

Authors’ Affiliations

The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Xi'an, 710049, China
Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China


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© Hongmei and Mingxi 2006