Coupling image denoising model based on total variation

Mei-ling WANG; Xian-chun ZHOU; Lin-feng ZHOU; Lan-fang SHI

doi:10.11959/j.issn.1000-436x.2016085

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Coupling image denoising model based on total variation

Academic communication | 更新时间：2024-06-05

- Coupling image denoising model based on total variation
- Journal of Communications Vol. 37, Issue 4, Pages: 182-191(2016)
- 作者机构：
  
  1. 南京信息工程大学电子与信息工程学院，江苏南京210044
  2. 南京信息工程大学江苏省大气环境与装备技术协同创新中心，江苏南京210044
  3. 南京信息工程大学江苏省气象探测与信息处理重点实验室，江苏南京210044
  4. 南京信息工程大学数学与统计学院，江苏南京210044
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(11202106);The National Natural Science Foundation of China(61201444);The Specialized Research Fund for the Doctoral Program of Higher Education(20123228120005);The Jiangsu Information and Communication Engineer-ing Preponderant Discipline Platform, The Natural Science Foundation of Jiangsu Province(BK20131005);The Jiangsu Qing Lan Project and the Natural Sciences Fundation of the Universities of Jiangsu Province(13KJB170016)
- DOI：10.11959/j.issn.1000-436x.2016085
  CLC： TN911.7
- Online First：2016-04，
  
  Published：25 April 2016
- 稿件说明：
移动端阅览
Mei-ling WANG, Xian-chun ZHOU, Lin-feng ZHOU, et al. Coupling image denoising model based on total variation[J]. Journal of Communications, 2016, 37(4): 182-191.
DOI：

Mei-ling WANG, Xian-chun ZHOU, Lin-feng ZHOU, et al. Coupling image denoising model based on total variation[J]. Journal of Communications, 2016, 37(4): 182-191. DOI： 10.11959/j.issn.1000-436x.2016085.

摘要

针对TV模型去噪后图像容易产生“阶梯效应”的现象，提出一种全变分耦合图像去噪模型。首先，根据去噪过程中图像梯度的变化趋势，构造一个趋势保真项，该保真项不但能有效去除图像噪声，而且能抑制“阶梯效应”。然后用小波在频域里对图像进行系数分解，利用Canny 算法的边缘检测特性，设计控制函数，控制能量的扩散方向，保持了TV模型和趋势保真项的优点，能够在保护图像边缘纹理等细节信息的同时，抑制“阶梯效应”。实验结果表明，新模型的峰值信噪比、结构相似度、视觉效果均有显著提高。另外，所提模型的运行时间较短。

Abstract

The total variation (TV) model used in image denoising may produce “staircase effect”. A coupling image de-noising model based on total variation was proposed. First

a trend fidelity term based on the change tendency of image gradient was established. The fidelity term could not only remove image noise

but also restrain “staircase effect”. Then

wavelet was used to decompose coefficient in frequency domain

control based on the edge detection ability of Canny algorithm were designed. The control functions control energy spread direction

the advantages of TV model and trend fidelity term are maintained

edge and texture details were protected

and “staircase effect'' was also suppressed. Experiment results show that peak signal to noise ratio (PSNR)

structure similarity (SSIM) and visual effects of the nov-el model are much better. Moreover

the running time of the novel model is shorter.

关键词

Keywords

references

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