基于L1-TV模型参数自适应的脉冲噪声去除
Impulse noise removal based on L1-TV model parameter adaptive
朱慧敏 1陈智斌 1文有为2
作者信息
- 1. 昆明理工大学理学院,昆明 650500
- 2. 湖南师范大学数学与统计学院,长沙 410000
- 折叠
摘要
在医学影像、军事目标识别、网络安全、图像处理等多个领域,由于其严重的噪声干扰和大幅度信号突变,脉冲噪声问题广泛存在.针对受脉冲噪声影响的图像去噪问题,研究基于L1-TV模型去除脉冲噪声方法中的自动选取正则化参数问题.对于约束模型的求解问题,采用原对偶方法进行求解.鉴于模型中正则化参数难确定的问题,提出了 一种自动求解正则化参数项的方法,减少了反复实验的次数.实验结果表明,提出的自适应选取模型中正则化参数方法具有鲁棒性,不仅能够去除图像中的脉冲噪声,而且较好地保留图像的边缘及细节信息.
Abstract
In a number of areas,such as medical imaging,military target recognition,network security and image processing,due to the serious noise interference and large signal mutation,impulse noise problems exist widely.Ai-ming at the problem of image denoising affected by impulse noise,this paper studies the automatic selection of regulari-zation parameters in the method of removing pulse noise based on Ll-TV model.The primal dual method is used to solve the problem of constraint model.In view of the difficulty in determining regularization parameters in the model,a method of automatically solving regularization parameters is proposed to reduce the number of repeated experiments.The experimental results show that the regularization parameter method proposed in this paper is robust,which can not only remove the impulse noise in the image,but also better retain the edge and detail information of the image.
关键词
图像去噪/脉冲噪声/L1-TV模型/参数估计Key words
image denoising/impulse noise/L1-TV model/parameter estimation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据