首页|稀疏分解和图拉普拉斯正则化的图像前景背景分割方法

稀疏分解和图拉普拉斯正则化的图像前景背景分割方法

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  • NETL
  • NSTL
  • 万方数据
  • 维普
针对现有图像前景背景分割方法的分割结果存在孤立像素点的问题，利用图信号处理理论和稀疏分解模型，提出新的图像前景背景分割方法。将图像的内在结构建模为图，通过图模型有效地刻画像素之间的内在关联性。将图像的像素强度建模为图信号，其中图像背景作为平滑分量，由一组图傅里叶变换基函数线性表示，叠加在背景上的前景为稀疏分量，前景像素间的连通性可由图拉普拉斯正则化项进行刻画。将图像前景背景分割问题归结为包含稀疏分解模型和图拉普拉斯正则化项的约束优化问题，采用交替方向乘子法对该优化问题进行求解。实验结果表明，与现有的其他方法相比，所提方法具有更好的分割效果。
Image foreground-background segmentation method based on sparse decomposition and graph Laplacian regularization
A new method for segmenting the foreground and background of images was proposed by using the graph signal processing theory and sparse decomposition model aiming at the problem of isolated pixel points in the segmentation results of existing image foreground-background segmentation methods.The intrinsic structure of an image was modeled as a graph,and the intrinsic correlation between pixels was effectively characterized by the graph model.The pixel intensity of the image was modeled as a graph signal.The image background was linearly represented as a smooth component by a set of graph Fourier transform basis functions,the foreground overlaid on the background was a sparse component,and the connectivity between foreground pixels could be characterized by the graph Laplacian regularization term.The image foreground-background segmentation problem was reduced to a constrained optimization problem incorporating the sparse decomposition model and graph Laplacian regularization term,and the alternating direction multiplier method was adopted to solve the optimization problem.The experimental results show that the proposed method has better segmentation performance compared with other existing methods.

graph signal processinggraph Laplacian regularizationgraph Fourier transform basis functionsparse decompositionforeground-background segmentation

谭婷芳、蔡万源、蒋俊正

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桂林电子科技大学信息与通信学院,广西壮族自治区 桂林 541004

桂林电子科技大学卫星导航定位与位置服务国家地方联合工程研究中心,广西壮族自治区 桂林 541004

西安电子科技大学杭州研究院,浙江杭州 311231

图信号处理 图拉普拉斯正则化 图傅里叶变换基函数 稀疏分解 前景背景分割

国家自然科学基金国家自然科学基金广西壮族自治区创新驱动发展专项广西自然科学基金杰出青年基金广西科技基地和人才专项桂林电子科技大学研究生教育创新项目

6217114662261014桂科AA210770082021GXNSFFA220004桂科AD212201122022YCXS039

2024

10.3785/j.issn.1008-973X.2024.05.011

浙江大学学报(工学版)
浙江大学

浙江大学学报(工学版)

CSTPCD北大核心
影响因子：0.625
ISSN：1008-973X
年,卷(期)：2024.58(5)
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