Open Access

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

EURASIP Journal on Advances in Signal Processing20062006:037129

https://doi.org/10.1155/ASP/2006/37129

Received: 11 October 2005

Accepted: 18 February 2006

Published: 29 May 2006

Abstract

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.

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Authors’ Affiliations

(1)
The Key Laboratory of Biomedical Information Engineering, Ministry of Education
(2)
Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University

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Copyright

© Hongmei and Mingxi 2006