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。
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
出处
《光电工程》
EI
CAS
CSCD
北大核心
2007年第4期105-108,共4页
Opto-Electronic Engineering
基金
湖南省自然科学基金资助项目(04JJ6035)
湘潭市科技计划项目(GY2006-07)
