全变分耦合图像去噪模型

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

通信学报 ›› 2016, Vol. 37 ›› Issue (4): 182-191.doi: 10.11959/j.issn.1000-436x.2016085

全变分耦合图像去噪模型

汪美玲^1,^2,³,周先春^1,^2,³,周林锋^1,^2,³,石兰芳⁴

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

出版日期:2016-04-25 发布日期:2016-04-26
基金资助:
国家自然科学基金资助项目;国家自然科学基金资助项目;教育部高等学校博士学科点专项科研基金资助项目;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;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

Coupling image denoising model based on total variation

Mei-ling WANG^1,^2,³,Xian-chun ZHOU^1,^2,³,Lin-feng ZHOU^1,^2,³,Lan-fang SHI⁴

¹ School of Electronic and Information Engineering, Nanjing Uni ity of Information Science and Technology, Nanjing 210044, China
² Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
³ Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Nanjing 210044, China
⁴ School of Mathematics and Statistics, Nanjing University of I formation Science and Technology, Nanjing 210044, China

Online:2016-04-25 Published:2016-04-26
Supported by:
The National Natural Science Foundation of China;The National Natural Science Foundation of China;The Specialized Research Fund for the Doctoral Program of Higher Education;The Jiangsu Information and Communication Engineer-ing Preponderant Discipline Platform, The Natural Science Foundation of Jiangsu Province;The Jiangsu Qing Lan Project and the Natural Sciences Fundation of the Universities of Jiangsu Province

摘要/Abstract

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。

关键词: 图像去噪, Canny算法, 趋势保真项, 控制函数

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.

Key words: image denoising, Canny algorithm, trend fidelity term, control function

汪美玲,周先春,周林锋,石兰芳. 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,Lan-fang SHI. Coupling image denoising model based on total variation[J]. Journal on Communications, 2016, 37(4): 182-191.

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模型	指标	TV	NLM	BM3D	Non-iterative PPB	Iterative PPB	WHT	WST	本文方法
Buddha	PSNR	34.132 5	28.045 5	29.803 0	28.384 3	28.551 9	25.974 5	25.610 1	49.980 4
Buddha	SSIM	0.944 0	0.742 0	0.887 6	0.754 4	0.771 5	0.641 5	0.626 5	0.997 9
Lena	PSNR	41.411 9	32.759 6	35.121 4	33.114 1	32.891 0	30.341 4	30.102 4	55.904 8
Lena	SSIM	0.981 5	0.889 1	0.961 6	0.886 5	0.892 4	0.812 1	0.808 8	0.999 1

全变分耦合图像去噪模型

Coupling image denoising model based on total variation

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