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离焦模糊图像的自适应滤波及逆滤波器复原
引用本文:胡小平,尹喜云,陈国良,黄之初.离焦模糊图像的自适应滤波及逆滤波器复原[J].光电工程,2007,34(4):105-108.
作者姓名:胡小平  尹喜云  陈国良  黄之初
作者单位:1. 湖南科技大学,机械设备健康维护省重点实验室,湖南,湘潭,411201;武汉理工大学,机电工程学院,湖北,武汉,430070
2. 湖南科技大学,机械设备健康维护省重点实验室,湖南,湘潭,411201
3. 武汉理工大学,机电工程学院,湖北,武汉,430070
基金项目:湖南省自然科学基金 , 湘潭市科技计划项目
摘    要:在微操作中,显微视觉系统获取的图像通常是离焦模糊图像.根据最小二乘原理和回归模型设计自适应滤波器,用于消除图像噪声,提高图像的信噪比;离焦模糊图像的退化模型可用圆盘函数描述,利用模糊图像频域的零点位置来估计圆盘函数的模糊参数;采用基于简化Wiener滤波的逆滤波器方法对模糊图像进行复原.对算法进行了仿真和实验分析,结果表明,该方法能够以较少的运算时间代价获取较好的复原效果.

关 键 词:离焦图像  图像复原  自适应滤波  逆滤波器  Wiener滤波
文章编号:1003-501X(2007)04-0105-04
收稿时间:2006/5/7
修稿时间:2006-05-07

Adaptive filtering and counter filter restoration for defocus blurred image
HU Xiao-ping,YIN Xi-yun,CHEN Guo-liang,HUANG Zhi-chu.Adaptive filtering and counter filter restoration for defocus blurred image[J].Opto-Electronic Engineering,2007,34(4):105-108.
Authors:HU Xiao-ping  YIN Xi-yun  CHEN Guo-liang  HUANG Zhi-chu
Affiliation:1. Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan 411201, China; 2. School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Abstract:Images acquired by the micro-vision system are usually defocus blurred images in micromanipulation. An adaptive filter based on the principle of least squares and regression model was designed, which was employed to remove the noise of an image and to improve the signal-to-noise ratio. The defocus blurred image can be depicted by uniformly distributed function on circular support region, and the blur parameter of the function can be estimated using zeros position in blurred image in frequency domain. Finally, the method of counter-filter based simplified Wiener filter was applied to restore blurred image. Some experiments were performed to validate the performance of the algorithm, and the experimental results show that the approaches can obtain the good restoration effect in less computation time.
Keywords:Defocus image  Image restoration  Adaptive filtering  Counter-filter  Wiener filter
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