A Sparsity Regularized Multiregion Image Segmentation Method Based on Image Decomposition

LI Ya-feng

doi:10.3969/j.issn.0372-2112.2015.09.024

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A Sparsity Regularized Multiregion Image Segmentation Method Based on Image Decomposition

更新时间：2025-07-16

- A Sparsity Regularized Multiregion Image Segmentation Method Based on Image Decomposition
- Acta Electronica Sinica Vol. 43, Issue 9, Pages: 1841-1849(2015)
- 作者机构：
  
  1. 宝鸡文理学院计算机学院,陕西,宝鸡,721016
  2. 宝鸡文理学院计算机学院,陕西,宝鸡,721016
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61379030);Research Project of Education Department of Shaanxi Province (No.14JK1048);Natural Science Basic Research Program of Shaanxi Province (No.2015JM6329);Key Research Project of Baoji College of Arts and Science (No.ZK15057)
- DOI：10.3969/j.issn.0372-2112.2015.09.024
  CLC： TP391
- Published：2015
- 稿件说明：
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LI Ya-feng. A Sparsity Regularized Multiregion Image Segmentation Method Based on Image Decomposition[J]. Acta Electronica Sinica, 2015, 43(9): 1841-1849.
DOI：

LI Ya-feng. A Sparsity Regularized Multiregion Image Segmentation Method Based on Image Decomposition[J]. Acta Electronica Sinica, 2015, 43(9): 1841-1849. DOI： 10.3969/j.issn.0372-2112.2015.09.024.

摘要

针对图像具有不同特征的成分

提出一种基于图像分解的多区域图像分割模型和算法.首先将图像分解项引入到图像分割模型中

递减了纹理和噪声对分割的影响;其次使用稀疏正则化方法保持分割区域的边缘几何结构;最后基于增广Lagrange乘子法

给出一种由扩散流引导的小波迭代阈值图像分割算法.一系列实验结果表明

提出的方法抗干扰能力强

对噪声具有更好的鲁棒性.提出的方法不仅能够分割结构图像

并且能够分割较复杂的纹理图像.

Abstract

Taking into account different feature components of images this paper presents a multiregion image segmentation model and algorithm based on image decomposition.Firstly

we introduce image decomposition term into the proposed image segmentation model.Image decomposition term can reduce the influence of texture and noise on our segmentation tasks.Secondly

we use sparsity regularization method to protect the edges and shape of the segmented regions.Finally

based on the augmented Lagrange multiplier method

we present an iterative wavelet shrinkage image segmentation algorithm which is guided by a diffusion flow.A series of experimental results show that the proposed method has strong anti-interference ability and it is more robust to noise.The proposed method can segment not only images with simple construction but also complex texture images.

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Related Institution

Department of Computer Science, Baoji University of Arts and Science

Department of Computer Science Baoji University of Arts and Science Baoji Shaanxi China

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