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Variational nonlocal image segmentation using split-Bregman

Published: 09 September 2012 Publication History

Abstract

In this paper, we proposed an image segmentation model in a variational nonlocal means framework. The model has following advantages. Firstly, Theconvexity global minimize optimum informations are taken into account and got the better segmentation results; secondly, the proposedglobal convex energy functional combined the nonlocal regularization and the local intensity fitting terms. The nonlocal total variational (TV) regularization term can preserve the detail structures of the target objects. At the same time, the modified locally binary fitting (LBF) term introduced to the model as the local fitting term can efficiently deal with the intensity inhomogeneity images; finally, we apply the split Bregman method to minimize the proposed energy functional efficiently. Weapplied the proposed model to the real medical images and extent to sensing images. Comparing with other models, the proposed model not only demonstrates accuracy but also display superiority.

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cover image ACM Other conferences
ICIMCS '12: Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
September 2012
243 pages
ISBN:9781450316002
DOI:10.1145/2382336
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • National Science Foundation of China
  • CCNU: Central China Normal University
  • Daqian Vision: Daqian Vision
  • Microsoft Research: Microsoft Research
  • Beijing ACM SIGMM Chapter
  • NEC: NEC Labs China

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 September 2012

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Author Tags

  1. image segmentation
  2. nonlocal means
  3. split Bregman
  4. variational model

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  • Research-article

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ICIMCS '12
Sponsor:
  • CCNU
  • Daqian Vision
  • Microsoft Research
  • NEC

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Overall Acceptance Rate 163 of 456 submissions, 36%

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