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。
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.Aiming at the problem of image denoising affected by impulse noise,this paper studies the automatic selection of regularization parameters in the method of removing pulse noise based on L1-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.
作者
朱慧敏
陈智斌
文有为
ZHU Huimin;CHEN Zhibin;WEN Youwei(Faculty of Science,Kunming University of Science and Technology,Kunming 650500,China;College of Mathematics and Statistics,Hunan Normal University,Changsha 410000,China)
出处
《激光杂志》
CAS
北大核心
2024年第5期203-208,共6页
Laser Journal
基金
国家自然科学基金项目(No.12361065)。
