Improved image denoising algorithm of Contourlet transform based on gray relational degree

doi:10.3724/SP.J.1087.2013.01103

Journal of Computer Applications ›› 2013, Vol. 33 ›› Issue (04): 1103-1107.DOI: 10.3724/SP.J.1087.2013.01103

• Network and distributed techno • Previous Articles Next Articles

Improved image denoising algorithm of Contourlet transform based on gray relational degree

ZENG Youwei¹,YANG Huixian¹,²,TANG FEI¹,TAN Zhenghua³,HE Yali¹

1. Faculty of Material and Photoelectronic Physics, Xiangtan University, Xiangtan Hunan 411105, China
2.
3. Information Engineering College, Xiangtan University, Xiangtan Hunan 411105, China

Received:2012-10-09 Revised:2012-11-28 Online:2013-04-01 Published:2013-04-23
Contact: YANG Huixian
Supported by:
A Project Supported by Scientific Research Fund of Hunan Provincial Education Department

基于灰色关联度改进的Contourlet变换图像去噪算法

曾友伟¹,杨恢先¹,²,唐飞¹,谭正华³,何雅丽¹

1. 湘潭大学材料与光电物理学院，湖南湘潭 411105
2. 湘潭大学材料与光电物理学院
3. 湘潭大学信息工程学院，湖南湘潭 411105

通讯作者: 杨恢先
作者简介:曾友伟(1987-), 男，湖南衡阳人,硕士研究生,主要研究方向：图像处理、数字信号处理；杨恢先(1963-),男,湖南益阳人,教授,主要研究方向：图像处理、人工智能；唐飞(1987-),男,湖南邵阳人,硕士研究生,主要研究方向：图像处理、数字信号处理；谭正华(1981-),男,湖南邵阳人,博士,主要研究方向：计算机图形学、数字矿山；何雅丽(1987-),女,湖南衡阳人,硕士研究生,主要研究方向：图像处理、数字信号处理。
基金资助:
湖南省教育厅科研项目(10C1263);湘潭大学科研项目(11QDZ11)

Abstract

Abstract: In order to denoise image more effectively, an improved Contourlet transform denoising algorithm based on gray relational degree was proposed. On one hand, considering the gray relational degree and inter-scale from the high-frequency sub-band and low frequency sub-band by Contourlet transform, the Bayes threshold was improved; On the other hand, in order to achieve the purpose of adaptive denoising, the characteristics of Contourlet coefficients were used to improve the compromising threshold function. The experimental results show that the proposed algorithm can denoise image effectively, get higher PSNR and better visual quality, and has a good practicability.

Key words: Contourlet transform, gray relational degree, Bayes threshold, image denoising, Peak Signal-to-Noise Ratio (PSNR)

摘要： 为了更有效降低图像中的噪声，提出一种基于灰色关联度改进的Contourlet变换图像去噪算法。一方面考虑到Contourlet变换尺度内各相邻方向子带之间的灰色关联度、尺度间的影响及噪声强度的因素，对贝叶斯阈值进行改进;另一方面根据Contourlet系数的特点对折中阈值函数进行改进，以达到自适应去噪的目的。实验结果表明，该算法能有效地降低图像噪声，获得更高的峰值信噪比(PSNR)和更好的视觉效果，具有较好的实用性。

关键词: Contourlet变换, 灰色关联度, 贝叶斯阈值, 图像去噪, 峰值信噪比

CLC Number:

TP391.41

ZENG Youwei YANG Huixian TANG FEI TAN Zhenghua HE Yali. Improved image denoising algorithm of Contourlet transform based on gray relational degree[J]. Journal of Computer Applications, 2013, 33(04): 1103-1107.

曾友伟杨恢先唐飞谭正华何雅丽. 基于灰色关联度改进的Contourlet变换图像去噪算法[J]. 计算机应用, 2013, 33(04): 1103-1107.

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Improved image denoising algorithm of Contourlet transform based on gray relational degree

基于灰色关联度改进的Contourlet变换图像去噪算法

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