计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (31): 169-171.DOI: 10.3778/j.issn.1002-8331.2010.31.046

• 图形、图像、模式识别 • 上一篇    下一篇

一种图像自适应Wiener组合滤波方法

赵双萍,邢敬宏   

  1. 兰州工业高等专科学校 软件工程系,兰州 730050
  • 收稿日期:2010-02-01 修回日期:2010-06-02 出版日期:2010-11-01 发布日期:2010-11-01
  • 通讯作者: 赵双萍

Composite method for image adaptive wiener filtering

ZHAO Shuang-ping,XING Jing-hong   

  1. Department of Software Engineering,Lanzhou Polytechnic College,Lanzhou,Gansu 730050,China
  • Received:2010-02-01 Revised:2010-06-02 Online:2010-11-01 Published:2010-11-01
  • Contact: ZHAO Shuang-ping

摘要: 利用小波域Wiener滤波和空间域自适应Wiener滤波的特点,提出一种基于小波域自适应Wiener滤波和空间域自适应Wiener滤波的组合滤波方法。该方法首先在小波域进行自适应Wiener滤波,对恢复图像中的残留噪声方差进行重新估计,再在空间域进行自适应Wiener滤波,这种方法提高了恢复图像的精度。仿真实验表明,与单独的小波域和空间域Wiener滤波相比,该方法的均方误差最小,去噪效果更优。

关键词: 小波, Wiener滤波, 自适应, 最小均方误差

Abstract: Using the characteristics of wavelet domain adaptive Wiener filtering and spatial domain adaptive Wiener filtering,this paper presents a combined filtering method based on an adaptive Wiener filtering in wavelet domain and an adaptive Wiener filter in spatial domain.Firstly a pre-denoised image is obtained with the thresholding denoising in wavelet domain and the residual noise variance of that is re-estimated.Then an adaptive Wiener filtering in spatial domain is applied to the reconstructed image to improve the accuracy.Computer simulation results show that,compared with a separate wavelet and spatial domain Wiener filtering,the mean squared error of the proposed method is the smallest and it obtains better denoising results.

Key words: wavelet, wiener filter, adaptive, mean squared error

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