期刊文献+
共找到342篇文章
< 1 2 18 >
每页显示 20 50 100
Compressive near-field millimeter wave imaging algorithm based on Gini index and total variation mixed regularization
1
作者 Jue Lyu Dong-Jie Bi +7 位作者 Bo Liu Guo Yi Xue-Peng Zheng Xi-Feng Li Li-Biao Peng Yong-Le Xie Yi-Ming Zhang Ying-Li Bai 《Journal of Electronic Science and Technology》 CAS CSCD 2023年第1期65-74,共10页
A compressive near-field millimeter wave(MMW)imaging algorithm is proposed.From the compressed sensing(CS)theory,the compressive near-field MMW imaging process can be considered to reconstruct an image from the under-... A compressive near-field millimeter wave(MMW)imaging algorithm is proposed.From the compressed sensing(CS)theory,the compressive near-field MMW imaging process can be considered to reconstruct an image from the under-sampled sparse data.The Gini index(GI)has been founded that it is the only sparsity measure that has all sparsity attributes that are called Robin Hood,Scaling,Rising Tide,Cloning,Bill Gates,and Babies.By combining the total variation(TV)operator,the GI-TV mixed regularization introduced compressive near-field MMW imaging model is proposed.In addition,the corresponding algorithm based on a primal-dual framework is also proposed.Experimental results demonstrate that the proposed GI-TV mixed regularization algorithm has superior convergence and stability performance compared with the widely used l1-TV mixed regularization algorithm. 展开更多
关键词 Millimeter wave(MMW) Compressed sensing(CS) Gini index(GI) total variation(tv) Signal processing Image reconstruction
下载PDF
Seismic high-resolution processing method based on spectral simulation and total variation regularization constraints
2
作者 Guo Xin Gao Jian-Hu +3 位作者 Yin Xun-De Yong Xue-Shan Wang Hong-Qiu Li Sheng-Jun 《Applied Geophysics》 SCIE CSCD 2022年第1期81-90,145,共11页
There is little low-and-high frequency information on seismic data in seismic exploration,resulting in narrower bandwidth and lower seismic resolution.It considerably restricts the prediction accuracy of thin reservoi... There is little low-and-high frequency information on seismic data in seismic exploration,resulting in narrower bandwidth and lower seismic resolution.It considerably restricts the prediction accuracy of thin reservoirs and thin interbeds.This study proposes a novel method to constrain improving seismic resolution in the time and frequency domain.The expected wavelet spectrum is used in the frequency domain to broaden the seismic spectrum range and increase the octave.In the time domain,the Frobenius vector regularization of the Hessian matrix is used to constrain the horizontal continuity of the seismic data.It eff ectively protects the signal-to-noise ratio of seismic data while the longitudinal seismic resolution is improved.This method is applied to actual post-stack seismic data and pre-stack gathers dividedly.Without abolishing the phase characteristics of the original seismic data,the time resolution is signifi cantly improved,and the structural features are clearer.Compared with the traditional spectral simulation and deconvolution methods,the frequency distribution is more reasonable,and seismic data has higher resolution. 展开更多
关键词 high-resolution seismic processing total variation regularization spectral simulation Hessian matrix
下载PDF
图像重建中total variation正则化项的有限元计算方法
3
作者 王彩芳 《计算机辅助工程》 2012年第3期49-52,56,共5页
为在迭代图像重建算法中获得更高质量的重建图像,推导出TV(Total Variation)正则化项关于重建图像的Fréchet导数,并给出该导数的有限元表示;利用两个数值实验,分别采用不同的网格尺寸和不同的形函数验证该有限元表示结果.数值实验... 为在迭代图像重建算法中获得更高质量的重建图像,推导出TV(Total Variation)正则化项关于重建图像的Fréchet导数,并给出该导数的有限元表示;利用两个数值实验,分别采用不同的网格尺寸和不同的形函数验证该有限元表示结果.数值实验结果表明:采用相同的k次单纯形元时,随着网格不断加密,计算结果的L1和L2误差均下降;采用相同的网格时,线性单纯形元函数计算结果明显优于分片常数有限元和二次单纯形元计算结果. 展开更多
关键词 图像重建 迭代算法 total variation正则化 Fréchet导数 单纯形元 有限元
下载PDF
A Hybrid Regularization-Based Multi-Frame Super-Resolution Using Bayesian Framework 被引量:1
4
作者 Mahmoud M.Khattab Akram M.Zeki +3 位作者 Ali A.Alwan Belgacem Bouallegue Safaa S.Matter Abdelmoty M.Ahmed 《Computer Systems Science & Engineering》 SCIE EI 2023年第1期35-54,共20页
The prime purpose for the image reconstruction of a multi-frame super-resolution is to reconstruct a higher-resolution image through incorporating the knowledge obtained from a series of relevant low-resolution images... The prime purpose for the image reconstruction of a multi-frame super-resolution is to reconstruct a higher-resolution image through incorporating the knowledge obtained from a series of relevant low-resolution images,which is useful in numerousfields.Nevertheless,super-resolution image reconstruction methods are usually damaged by undesirable restorative artifacts,which include blurring distortion,noises,and stair-casing effects.Consequently,it is always challenging to achieve balancing between image smoothness and preservation of the edges inside the image.In this research work,we seek to increase the effectiveness of multi-frame super-resolution image reconstruction by increasing the visual information and improving the automated machine perception,which improves human analysis and interpretation processes.Accordingly,we propose a new approach to the image reconstruction of multi-frame super-resolution,so that it is created through the use of the regularization framework.In the proposed approach,the bilateral edge preserving and bilateral total variation regularizations are employed to approximate a high-resolution image generated from a sequence of corresponding images with low-resolution to protect significant features of an image,including sharp image edges and texture details while preventing artifacts.The experimental results of the synthesized image demonstrate that the new proposed approach has improved efficacy both visually and numerically more than other approaches. 展开更多
关键词 SUPER-RESOLUTION regularized framework bilateral total variation bilateral edge preserving
下载PDF
Image decomposition and staircase effect reduction based on total generalized variation 被引量:2
5
作者 Jianlou Xu Xiangchu Feng +1 位作者 Yan Hao Yu Han 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第1期168-174,共7页
Total variation (TV) is widely applied in image process-ing. The assumption of TV is that an image consists of piecewise constants, however, it suffers from the so-cal ed staircase effect. In order to reduce the sta... Total variation (TV) is widely applied in image process-ing. The assumption of TV is that an image consists of piecewise constants, however, it suffers from the so-cal ed staircase effect. In order to reduce the staircase effect and preserve the edges when textures of image are extracted, a new image decomposition model is proposed in this paper. The proposed model is based on the to-tal generalized variation method which involves and balances the higher order of the structure. We also derive a numerical algorithm based on a primal-dual formulation that can be effectively imple-mented. Numerical experiments show that the proposed method can achieve a better trade-off between noise removal and texture extraction, while avoiding the staircase effect efficiently. 展开更多
关键词 total variation (tv image decomposition staircaseeffect total generalized variation.
下载PDF
Total Variation Constrained Non-Negative Matrix Factorization for Medical Image Registration 被引量:4
6
作者 Chengcai Leng Hai Zhang +2 位作者 Guorong Cai Zhen Chen Anup Basu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2021年第5期1025-1037,共13页
This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorizati... This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorization by total variation constraint and graph regularization.The main contributions of our work are the following.First,total variation is incorporated into NMF to control the diffusion speed.The purpose is to denoise in smooth regions and preserve features or details of the data in edge regions by using a diffusion coefficient based on gradient information.Second,we add graph regularization into NMF to reveal intrinsic geometry and structure information of features to enhance the discrimination power.Third,the multiplicative update rules and proof of convergence of the TV-GNMF algorithm are given.Experiments conducted on datasets show that the proposed TV-GNMF method outperforms other state-of-the-art algorithms. 展开更多
关键词 Data clustering dimension reduction image registration non-negative matrix factorization(NMF) total variation(tv)
下载PDF
Adaptive Parameter Selection for Total Variation Image Deconvolution 被引量:3
7
作者 You-Wei Wen Andy M. Yip 《Numerical Mathematics(Theory,Methods and Applications)》 SCIE 2009年第4期427-438,共12页
In this paper,we propose a discrepancy rule-based method to automatically choose the regularization parameters for total variation image restoration problems. The regularization parameters are adjusted dynamically in ... In this paper,we propose a discrepancy rule-based method to automatically choose the regularization parameters for total variation image restoration problems. The regularization parameters are adjusted dynamically in each iteration.Numerical results are shown to illustrate the performance of the proposed method. 展开更多
关键词 Image restoration regularization parameter total variation.
下载PDF
Dark channel prior based blurred image restoration method using total variation and morphology 被引量:1
8
作者 Yibing Li Qiang Fu +1 位作者 Fang Ye Hayaru Shouno 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2015年第2期359-366,共8页
The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is... The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation (TV) and image morphology transform (specifically top-hat transform and bottom- hat transform) have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es- timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the ill-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition. 展开更多
关键词 image restoration dark channel prior total variation (tv) morphology transform
下载PDF
Novel image restoration model coupling gradient fidelity term based on adaptive total variation 被引量:1
9
作者 石明珠 许廷发 +3 位作者 梁炯 冯亮 张坤 周立伟 《Journal of Beijing Institute of Technology》 EI CAS 2011年第2期261-266,共6页
A novel image restoration model coupling with a gradient fidelity term based on adaptive total variation is proposed in this paper. In order to choose proper parameters, the selection criteria were analyzed theoretica... A novel image restoration model coupling with a gradient fidelity term based on adaptive total variation is proposed in this paper. In order to choose proper parameters, the selection criteria were analyzed theoretically, and a simple scheme to demonstrate its validity was adopted experimentally. To make fair comparisons of performances of three models, the same numerical algorithm was used to solve partial differential equations. Both the international standard test image on Lena and HR image of CBERS-02B of Dalian city were used to verify the performance of the model. Experimental results illustrate that the new model not only preserved the edge and important details but also alleviated the staircase effect effectively. 展开更多
关键词 image restoration total variation(tv) gradient fidelity term staircase effect
下载PDF
Multiquadric Radial Basis Function Approximation Scheme for Solution of Total Variation Based Multiplicative Noise Removal Model 被引量:1
10
作者 Mushtaq Ahmad Khan Ahmed BAltamimi +4 位作者 Zawar Hussain Khan Khurram Shehzad Khattak Sahib Khan Asmat Ullah Murtaza Ali 《Computer Modeling in Engineering & Sciences》 SCIE EI 2021年第1期55-88,共34页
This article introduces a fastmeshless algorithm for the numerical solution nonlinear partial differential equations(PDE)by Radial Basis Functions(RBFs)approximation connected with the Total Variation(TV)-basedminimiz... This article introduces a fastmeshless algorithm for the numerical solution nonlinear partial differential equations(PDE)by Radial Basis Functions(RBFs)approximation connected with the Total Variation(TV)-basedminimization functional and to show its application to image denoising containing multiplicative noise.These capabilities used within the proposed algorithm have not only the quality of image denoising,edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images.It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of dependence on a mesh or integration procedure.The numerical investigations and corresponding examples prove the effectiveness of the recommended algorithm regarding the robustness and visual improvement as well as peak-signal-to-noise ratio(PSNR),signal-to-noise ratio(SNR),and structural similarity index(SSIM)corresponded to the current conventional TV-based schemes. 展开更多
关键词 Denoised image multiplicative and speckle noises total variation(tv)filter Euler-Lagrange restoration equation multiquadric radial basis functions meshless and mesh-based schemes
下载PDF
Box-constrained Total-variation Image Restoration with Automatic Parameter Estimation 被引量:1
11
作者 HE Chuan HU Chang-Hua ZHANG Wei SHI Biao 《自动化学报》 EI CSCD 北大核心 2014年第8期1804-1811,共8页
关键词 图像复原 参数估计 变差 图像恢复 动态范围 最小化问题 正则化参数 TM图像
下载PDF
An overview of image restoration based on variational regularization
12
作者 Qibin FAN Yuling JIAO 《Frontiers of Mathematics in China》 CSCD 2024年第3期157-180,共24页
Image restoration is a complicated process in which the original information can be recovered from the degraded image model caused by lots of factors.Mathematically,image restoration problems are ill-posed inverse pro... Image restoration is a complicated process in which the original information can be recovered from the degraded image model caused by lots of factors.Mathematically,image restoration problems are ill-posed inverse prob-lems.In this paper image restoration models and algorithms based on variational regularization are surveyed.First,we review and analyze the typical models for denoising,deblurring and inpainting.Second,we construct a unified restoration model based on variational regularization and summarize the typical numerical methods for the model.At last,we point out eight diffcult problems which remain open in this field. 展开更多
关键词 regularization image restoration inverse problem total variation WAVELET
原文传递
基于MC_RTV正则化的高分辨SAR特征增强算法
13
作者 李伟 马彦恒 +2 位作者 张玉华 李秉璇 褚丽娜 《陆军工程大学学报》 2024年第5期67-74,共8页
针对合成孔径雷达(synthetic aperture radar,SAR)稀疏成像中目标反射率易低估、目标结构特征难以精确提取的问题,提出一种基于非凸和相对全变分(relative total variation,RTV)正则化的稀疏SAR成像算法。该算法利用非凸惩罚抑制偏差效... 针对合成孔径雷达(synthetic aperture radar,SAR)稀疏成像中目标反射率易低估、目标结构特征难以精确提取的问题,提出一种基于非凸和相对全变分(relative total variation,RTV)正则化的稀疏SAR成像算法。该算法利用非凸惩罚抑制偏差效应、RTV自适应保护图像结构,在交替方向乘子法(alternating direction method of multipliers,ADMM)分布式优化框架下,实现多个正则项的协同优化增强。为更好地提高成像效率和降低内存占用量,利用匹配滤波(match filter,MF)算子构造测量矩阵进行近似观测,并对重建的SAR图像质量进行定量评价。仿真与实测数据处理结果表明,所提方法可有效抑制噪声杂波,在保证空间分辨率的情况下有效提高目标重建精度和辐射分辨率。 展开更多
关键词 合成孔径雷达 非凸正则化 相对全变分 特征联合增强
下载PDF
Iterative regularization method for image denoising with adaptive scale parameter
14
作者 李文书 骆建华 +2 位作者 刘且根 何芳芳 魏秀金 《Journal of Southeast University(English Edition)》 EI CAS 2010年第3期453-456,共4页
In order to decrease the sensitivity of the constant scale parameter, adaptively optimize the scale parameter in the iteration regularization model (IRM) and attain a desirable level of applicability for image denoi... In order to decrease the sensitivity of the constant scale parameter, adaptively optimize the scale parameter in the iteration regularization model (IRM) and attain a desirable level of applicability for image denoising, a novel IRM with the adaptive scale parameter is proposed. First, the classic regularization item is modified and the equation of the adaptive scale parameter is deduced. Then, the initial value of the varying scale parameter is obtained by the trend of the number of iterations and the scale parameter sequence vectors. Finally, the novel iterative regularization method is used for image denoising. Numerical experiments show that compared with the IRM with the constant scale parameter, the proposed method with the varying scale parameter can not only reduce the number of iterations when the scale parameter becomes smaller, but also efficiently remove noise when the scale parameter becomes bigger and well preserve the details of images. 展开更多
关键词 iterative regularization model (IRM) total variation varying scale parameter image denoising
下载PDF
Image decomposition using adaptive regularization and div(BMO) 被引量:2
15
作者 Chengwu Lu Guoxiang Song 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2011年第2期358-364,共7页
In order to avoid staircasing effect and preserve small scale texture information for the classical total variation regularization, a new minimization energy functional model for image decomposition is proposed. First... In order to avoid staircasing effect and preserve small scale texture information for the classical total variation regularization, a new minimization energy functional model for image decomposition is proposed. Firstly, an adaptive regularization based on the local feature of images is introduced to substitute total variational regularization. The oscillatory component containing texture and/or noise is modeled in generalized function space div (BMO). And then, the existence and uniqueness of the minimizer for proposed model are proved. Finally, the gradient descent flow of the Euler-Lagrange equations for the new model is numerically implemented by using a finite difference method. Experiments show that the proposed model is very robust to noise, and the staircasing effect is avoided efficiently, while edges and textures are well remained. 展开更多
关键词 image decomposition regularization total variation space div (BMO)
下载PDF
Anisotropic fourth-order diffusion regularization for multiframe super-resolution reconstruction
16
作者 黄淑英 杨勇 王国宇 《Journal of Central South University》 SCIE EI CAS 2013年第11期3180-3186,共7页
A novel rcgularization-based approach is presented for super-resolution reconstruction in order to achieve good tradeoff between noise removal and edge preservation. The method is developed by using L1 norm as data fi... A novel rcgularization-based approach is presented for super-resolution reconstruction in order to achieve good tradeoff between noise removal and edge preservation. The method is developed by using L1 norm as data fidelity term and anisotropic fourth-order diffusion model as a regularization item to constrain the smoothness of the reconstructed images. To evaluate and prove the performance of the proposed method, series of experiments and comparisons with some existing methods including bi-cubic interpolation method and bilateral total variation method are carried out. Numerical results on synthetic data show that the PSNR improvement of the proposed method is approximately 1.0906 dB on average compared to bilateral total variation method, and the results on real videos indicate that the proposed algorithm is also effective in terms of removing visual artifacts and preserving edges in restored images. 展开更多
关键词 SUPER-RESOLUTION anisotropic fourth-order diffusion bilateral total variation regularization
下载PDF
稀疏角度CT图像重建的Huber-TV正则化方法 被引量:1
17
作者 李维 张本鑫 《现代电子技术》 2023年第2期65-69,共5页
对于稀疏角度下的投影数据,计算机断层扫描重建图像容易出现分辨率低、伪影较多的问题,难以满足工业及医学诊断要求。文中从迭代重建的角度出发,提出一个结合全变分(TV)和Huber函数(Huber-TV)的CT重建方法。该方法利用Huber函数替代传... 对于稀疏角度下的投影数据,计算机断层扫描重建图像容易出现分辨率低、伪影较多的问题,难以满足工业及医学诊断要求。文中从迭代重建的角度出发,提出一个结合全变分(TV)和Huber函数(Huber-TV)的CT重建方法。该方法利用Huber函数替代传统全变分模型中的L1范数,在合理控制函数阈值的条件下,充分利用Huber函数的线性部分对大于阈值的梯度图像进行较轻的惩罚,以保持图像边缘连续性;再结合二次项对小于阈值的梯度图像进行较大的惩罚,以抑制图像中不连续梯度跳跃。新模型目标函数的光滑性可以使得梯度下降法快速收敛到最优值,避开传统全变分模型中的次梯度计算,从而降低计算复杂度并加快迭代速度。实验结果表明,在稀疏角度重建条件下,与传统TV模型相比,Huber-TV模型的均方根误差降低19%,信噪比提升22.33 dB,说明所提方法高效可行。 展开更多
关键词 CT图像重建 梯度图像 全变分模型 Huber-tv 图像处理 数据分析
下载PDF
基于复合正则化的稀疏SAR成像方法研究
18
作者 高志奇 李贺贺 +2 位作者 黄平平 谭维贤 徐伟 《信号处理》 CSCD 北大核心 2024年第10期1895-1909,共15页
随着高分辨率对地观测要求的不断提高,合成孔径雷达(Synthetic Aperture Radar,SAR)的应用将越来越广泛。针对高分辨率SAR成像存在数据量大、存储难度高、计算时间长等问题,目前常用的解决方法是在SAR成像模型中引入压缩感知(Compressed... 随着高分辨率对地观测要求的不断提高,合成孔径雷达(Synthetic Aperture Radar,SAR)的应用将越来越广泛。针对高分辨率SAR成像存在数据量大、存储难度高、计算时间长等问题,目前常用的解决方法是在SAR成像模型中引入压缩感知(Compressed Sensing,CS)的方法降低采样率和数据量。通常使用单一的正则化作为约束条件,可以抑制点目标旁瓣,实现点目标特征增强,但是观测场景中可能存在多种目标类型,因此使用单一正则化约束难以满足多种特征增强的要求。本文提出了一种基于复合正则化的稀疏高分辨SAR成像方法,通过压缩感知降低数据量,并使用多种正则化的线性组合作为约束条件,增强观测场景中不同类型目标的特征,实现复杂场景中高分辨率对地观测的要求。该方法在稀疏SAR成像模型中引入非凸正则化和全变分(Total Variation,TV)正则化作为约束条件,减小稀疏重构误差、增强区域目标的特征,降低噪声对成像结果的影响,提高成像质量;采用改进的交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)实现复合正则化约束的求解,减少计算时间、快速重构图像;使用方位距离解耦算子代替观测矩阵及其共轭转置,进一步降低计算复杂度。仿真和实测数据实验表明,本文所提算法可以对点目标和区域目标进行特征增强,减小计算复杂度,提高收敛性能,实现快速高分辨的图像重构。 展开更多
关键词 合成孔径雷达成像 非凸正则化 全变分正则化 交替方向乘子法
下载PDF
一种基于稀疏重构的多视角MIMO雷达关联成像算法研究
19
作者 张弓 田雨薇 +1 位作者 袁家雯 张宇 《系统工程与电子技术》 EI CSCD 北大核心 2024年第2期470-477,共8页
为改善复杂目标的成像表现、提升雷达图像的视觉效果,提出一种基于稀疏重构的多视角多输入多输出(multiple input multiple output,MIMO)雷达关联成像方法,设计了多视角雷达散射面积(radar cross section,RCS)起伏的稀疏重构关联成像模... 为改善复杂目标的成像表现、提升雷达图像的视觉效果,提出一种基于稀疏重构的多视角多输入多输出(multiple input multiple output,MIMO)雷达关联成像方法,设计了多视角雷达散射面积(radar cross section,RCS)起伏的稀疏重构关联成像模型。所提算法能提高辐射场信号随机性,改善复杂目标雷达关联成像参考信号与回波之间相关性退化的情况,减小多视角RCS起伏对相关性的影响,提升多视角下的关联成像质量。最后,通过仿真验证了所提方法的有效性。 展开更多
关键词 雷达成像 多输入多输出 雷达关联成像 正则化 全变差
下载PDF
Lipschitz and Total-Variational Regularization for Blind Deconvolution 被引量:2
20
作者 Yu-Mei Huang Michael K.Ng 《Communications in Computational Physics》 SCIE 2008年第6期195-206,共12页
In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be r... In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be recovered.In this paper,we consider images in Lipschitz spaces,and propose to use Lipschitz regularization for images and total variational regularization for point spread functions in blind deconvolution.Our experimental results show that such combination of Lipschitz and total variational regularization methods can recover both images and point spread functions quite well. 展开更多
关键词 Lipschitz regularization total variational regularization blind deconvolution TEXTURE Poisson singular integral alternating iterative algorithm.
原文传递
上一页 1 2 18 下一页 到第
使用帮助 返回顶部