[1]杨晶晶,吴 辉,陈颖频*.基于 Lp 收缩算子的改进广义全变分去噪方法[J].计算机技术与发展,2020,30(04):20-25.[doi:10. 3969 / j. issn. 1673-629X. 2020. 04. 004]
　YANG Jing-jing,WU Hui,CHEN Ying-pin*.Improved Generalized Total Variation Denoising Method Based on Lp Shrinkage[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2020,30(04):20-25.[doi:10. 3969 / j. issn. 1673-629X. 2020. 04. 004]
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基于 Lp 收缩算子的改进广义全变分去噪方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年04期
页码:
20-25
栏目:
智能、算法、系统工程
出版日期:
2020-04-10

文章信息/Info

Title:
Improved Generalized Total Variation Denoising Method Based on Lp Shrinkage
文章编号:
1673-629X(2020)04-0020-06
作者:
杨晶晶1 ; 吴 辉2 ; 陈颖频2*
1. 福州大学 物理与信息工程学院,福建 福州 350000; 2. 闽南师范大学 物理与信息工程学院,福建 漳州 363000
Author(s):
YANG Jing-jing1 ; WU Hui2 ; CHEN Ying-pin2*
1. School of Physics and Information Engineering,Fuzhou University,Fuzhou 350000,China; 2. School of Physics and Information Engineering,Minnan Normal University,Zhangzhou 363000,China
关键词:
二阶广义全变分模型; 图像去噪; Lp 收缩算子; 交替乘子迭代法; 稀疏性
Keywords:
second - order generalized total variational model;  image denoising;  Lp shrinkage;  alternating direction method of multipliers; sparsity
分类号:
TP301. 6
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 04. 004
摘要:
二阶广义的全变分模型是一种建立在全变分模型的思想之上进行改进的图像去噪模型,该模型是一种考虑一阶以及高阶梯度稀疏性的模型,能够有效地抑制阶梯伪影效应的产生。Lp 收缩算子相比于 L1 算子增加了一个自由度,它能够更好地刻画稀疏梯度信息,同时 Lp 收缩算子的等高线对噪声更加鲁棒。 考虑到 Lp 收缩算子的优势,将 Lp 收缩算子引入二阶广义全变分去噪模型,提出改进的二阶广义全变分 Lp 收缩算子模型(TGV2-Lp) 。利用交替乘子迭代法对模型进行求解,引入快速傅里叶算法提高算法效率。 通过测试 6 组图片、对比传统的 3 种去噪模型,从实验结果可以得出,提出的模型 TGV2-Lp 在有效保留图片边缘细节信息的同时,能够有效去除噪声,在视觉效果、峰值信噪比和结构相似性都有一定优势。
Abstract:
Second-order total generalized variation model is an image denoising model based on the idea of the total variation (TV) model. Both the first-order and high-level sparseness are taken into account so that the generation of the stair-case artifact of TV is effectively suppressed. The Lp shrinkage adds a degree of freedom compared to the L1 operator,which better describes the sparse gradient information,while the contours of the Lp shrinkage are more robust to noise. Considering the advantages mentioned above,we introduce the Lp shrinkage in second - order total generalized variation model and propose second - order total generalized variation with Lp shrinkage (TGV2-Lp) model. The model is solved by the alternating multiplier iteration method. The fast Fourier transform algorithm is introduced to further improve the efficiency of the algorithm. By testing six sets of pictures and comparing the traditional three denoising models, it can be concluded from the experimental results that the proposed model can effectively remove noise while effectively retaining the edge details of the processed picture and has certain advantages in visual effects,peak signal-to-noise ratio,and structural similarity.

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更新日期/Last Update: 2020-04-10