计算机应用 ›› 2012, Vol. 32 ›› Issue (05): 1286-1288.

• 图形图像处理 • 上一篇    下一篇

邻域窗能量平均的Contourlet变换自适应阈值去噪算法

何雅丽1,杨恢先1,李利2,冷爱莲3,祝贵1   

  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 信息工程学院,湖南 湘潭 411105
    3. 湘潭大学 能源工程学院,湖南 湘潭 411105
  • 收稿日期:2011-11-09 修回日期:2012-01-10 发布日期:2012-05-01 出版日期:2012-05-01
  • 通讯作者: 何雅丽
  • 作者简介: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;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;李利(1986-),女,湖南长沙人,硕士研究生,主要研究方向:图像处理、数字信号处理;冷爱莲(1969-),女,湖南益阳人,讲师,主要研究方向:数字信号处理、智能控制;祝贵(1986-),男,四川西昌人,硕士研究生,主要研究方向:图形图像处理。
  • 基金资助:

    湖南省教育厅科研项目(10C1263);湘潭大学科研项目(11QDZ11)

Adaptive threshold denoising algorithm with neighboring window average energy based on Contourlet transform

HE Ya-li1,YANG Hui-xian1,LI Li2,LENG Ai-lian3,ZHU Gui1   

  1. 1. Faculty of Material, Photoelectronics and Physics, Xiangtan University, Xiangtan Hunan 411105, China
    2. College of Information Engineering, Xiangtan University, Xiangtan Hunan 411105, China
    3. Energy Engineering College, Xiangtan University, Xiangtan Hunan 411105, China
  • Received:2011-11-09 Revised:2012-01-10 Online:2012-05-01 Published:2012-05-01
  • Contact: HE Ya-li

摘要: 针对Contourlet多尺度阈值去噪算法中阈值的选取忽略了方向信息影响的问题,提出一种基于邻域窗能量平均的自适应阈值去噪算法。根据Contourlet系数能量分布特点,将系数划分到三个不同的区域,对三个区域的阈值采用不同的因子进行调整,从而得到更好的去噪效果。实验结果表明,与小波阈值去噪、Contourlet阈值去噪以及Contourlet多尺度阈值去噪相比,该算法在峰值信噪比以及视觉效果上都有明显的提高,且能够有效地保留图像边缘细节信息。

关键词: 图像去噪, Contourlet变换, 小波变换, 能量平均, 自适应阈值

Abstract: Concerning the defects of multi-scale threshold on directional information using Contourlet transform,a new adaptive threshold denoising algorithm was proposed, which was based on average energy of neighboring window. According to the distribution of the coefficients energy, the Contourlet coefficients were divided up into three areas. The noise could be reduced obviously by adjusting the threshold of these areas with different variables. In contrast with the wavelet threshold, Contourlet threshold and multi-scale threshold using Contourlet transform, the experimental results demonstrate that the new algorithm has superiority in Peak Signal-to-Noise Ratio (PSNR) and visual effect, which can maintain effectively the edges of the image.

Key words: image denoising, Contourlet transform, wavelet transform, average energy, adaptive threshold

中图分类号: