电子学报Issue(9)：1841-1849,9.DOI:10.3969/j.issn.0372-2112.2015.09.024
基于图像分解的稀疏正则化多区域图像分割方法
A Sparsity Regularized Multiregion lmage Segmentation Method Based on lmage Decomposition
摘要
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 seg-mentation 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 La-grange 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.关键词
图像分割/图像分解/稀疏表示/小波/变分模型Key words
image segmentation/image decomposition/sparse representation/wavelet/variational model分类
信息技术与安全科学引用本文复制引用
李亚峰..基于图像分解的稀疏正则化多区域图像分割方法[J].电子学报,2015,(9):1841-1849,9.基金项目
国家自然科学基金（No．61379030）；陕西省教育厅专项科研计划项目（No．14JK1048）；陕西省自然科学基础研究计划基金（No．2015JM6329）；宝鸡文理学院院级科研重点项目 （）
