Two-Stage Image Segmentation Scheme Based on Inexact Alternating Direction Method

Two-Stage Image Segmentation Scheme Based on Inexact Alternating Direction Method
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基于不精确交替方向法的两阶段图像分割方案

DOI:
10.4208/nmtma.2016.m1509
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发表时间:
2016-08
影响因子:
1.3
通讯作者:
Pang Zhi-Feng
Pang Zhi-Feng
中科院分区:
数学3区
文献类型:
--
作者:
Zhi Zhanjiang;Sun Yi;Pang Zhi-Feng

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图像分割是图像处理和计算机视觉中的一个基本问题,有着广泛的应用。本文提出了一种基于非精确交替方向法的两阶段图像分割方法。具体地说,我们首先求解Mumford-Shah模型的凸变量,得到光滑的解,然后将K -均值聚类方法应用于解,得到分割结果。通过对人工图像、自然图像和脑MRI图像等多种图像的分割,数值比较表明了所提方法的有效性。
Image segmentation is a fundamental problem in both image processing and computer vision with numerous applications. In this paper, we propose a two-stage image segmentation scheme based on inexact alternating direction method. Specifically, we first solve the convex variant of the Mumford-Shah model to get the smooth solution, the segmentation are then obtained by apply the K -means clustering method to the solution. Some numerical comparisons are arranged to show the effectiveness of our proposed schemes by segmenting many kinds of images such as artificial images, natural images, and brain MRI images.
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