全变分耦合图像去噪模型

汪美玲; 周先春; 周林锋; 石兰芳

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

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全变分耦合图像去噪模型

学术通信 | 更新时间：2024-06-05

- 全变分耦合图像去噪模型
- Coupling image denoising model based on total variation
- 通信学报 2016年37卷第4期页码：182-191
- 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：
  
  [ "汪美玲（1988-），女，安徽芜湖人，南京信息工程大学硕士生，主要研究方向为图像处理、模式识别等。" ]
  [ "周先春（1974-），男，安徽合肥人，南京信息工程大学副教授、硕士生导师，主要研究方向为信号与信息处理。" ]
  [ "周林锋（1991-），男，安徽蚌埠人，南京信息工程大学硕士生，主要研究方向为信号处理、图像处理等。" ]
  [ "石兰芳（1976-），女，安徽合肥人，南京信息工程大学副教授、硕士生导师，主要研究方向为非线性分析。" ]
- 基金信息：
  
  国家自然科学基金资助项目(11202106);国家自然科学基金资助项目(61201444);教育部高等学校博士学科点专项科研基金资助项目(20123228120005);江苏省“信息与通信工程”优势学科建设基金资助项目；江苏省自然科学基金资助项目(BK20131005);江苏省青蓝工程和江苏省高校自然科学研究基金资助项目(13KJB170016)
- DOI：10.11959/j.issn.1000-436x.2016085
  中图分类号： TN911.7
- 网络出版日期：2016-04，
  
  纸质出版日期：2016-04-25
- 稿件说明：
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汪美玲, 周先春, 周林锋, 等. 全变分耦合图像去噪模型[J]. 通信学报, 2016,37(4):182-191.

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.
汪美玲, 周先春, 周林锋, 等. 全变分耦合图像去噪模型[J]. 通信学报, 2016,37(4):182-191. DOI： 10.11959/j.issn.1000-436x.2016085.

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.

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