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• 计算机科学 • 上一篇    下一篇

一种新的脉冲噪声图像恢复方法

张震1,2,刘建国3, 刘辉1   

  1. 1. 吉林大学 数学研究所, 长春 130012; 2. 大庆油田 物业集团, 黑龙江 大庆 163453;3. 长春师范学院 信息技术学院, 长春 130032
  • 收稿日期:2007-10-31 修回日期:1900-01-01 出版日期:2008-07-26 发布日期:2008-07-26
  • 通讯作者: 马驷良

A New Impulse Noise Image Recovering Method

ZHANG Zhen1,2, MA Siliang1, LIU Jianguo3, LIU Hui1   

  1. 1. Institute of Mathematics, Jilin University, Changchun 130012, China;2. Estate Group, Daqing Oilfield, Daqing 163453, Heilongjiang Province, China;3. College of Informational Technology, Changchun Normal University, Changchun 130032, China
  • Received:2007-10-31 Revised:1900-01-01 Online:2008-07-26 Published:2008-07-26
  • Contact: MA Siliang

摘要: 为消除图像中的脉冲噪声, 提出一种窗口自适应开关中值滤波方法. 利用BP神经网络将图像中的每个像素点分类为信号点或噪声点, 再采用改进的中值滤波器对检测后的图像进行滤波处理. 根据噪声检测结果, 滤波器自适应调整窗口大小并选择性取样, 逐点滤波消除图像中的噪声. 该方法在抑制脉冲噪声、 保护图像细节方面均优于以往基于中值滤波的法, 即使在图像遭受70%噪声污染的极端情况下, 仍能得 到很好恢复.

关键词: 图像去噪, 脉冲噪声检测, 自适应开关中值滤波

Abstract: In order to denoise impulse noises in images, an adaptive window switching median filtering method is proposed in this paper. First, each pixel is classified as signal or noisy point by the BPnet. Next, the image is filtered by an improved median filter. According to the result of noise detection, the filter can adjust adaptively windows width and sample choicely, each noisy point in image is denoised by filtering. In terms of suppressing impulse noise and preserving image details, the proposed method is better than that based on median filter. Even in the extreme case of 70% noise corruption, noisy images can be effectively recovered.

Key words: image denoising, impulse noise detection, adaptive switching median filters

中图分类号: 

  • TP391.41