A Coastal Zone Segmentation Variational Model and Its Accelerated ADMM Method

HUANG Baoxiang; CHEN Ge; ZHANG Xiaolei; YANG Huan

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A Coastal Zone Segmentation Variational Model and Its Accelerated ADMM Method

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摘要

Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaption parameter and modifying noisy data term, the proposed variational model provides a good solution for the coastal zone SAR image with common characteristics of inherent speckle noise and complicated geometrical details. However, the proposed model is difficult to solve due to to its nonlinear, non-convex and non-smooth characteristics. Followed by curve evolution theory and operator splitting method, the minimization problem is reformulated as a constrained minimization problem. A fast alternating minimization iterative scheme is designed to implement coastal zone segmentation. Finally, various two-stage and multiphase experimental results illustrate the advantage of the proposed segmentation model, and indicate the high computation efficiency of designed numerical approximation algorithm.

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《中国海洋大学学报：英文版》 |2017年第6期|1081-1089|共9页
作者
HUANG Baoxiang; CHEN Ge; ZHANG Xiaolei; YANG Huan;
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作者单位

College of Computer Science and Technology;

Postdoctoral stations of system science;

Qingdao University;

College of Information Science and Engineering;

Ocean University of China;

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原文格式 PDF
正文语种 chi
中图分类海洋学;
关键词
coastal; zone; segmentation; variational; Potts; model; alternating; direction; method; with; multipliers; edge; self-adaption;

A Coastal Zone Segmentation Variational Model and Its Accelerated ADMM Method

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