摘要
应用自动光学检测仪检测印刷电路板图像的过程中,图像去噪是至关重要的一个步骤,针对PCB板图像对比度差、动态范围小、图像模糊等问题,提出了一种改进的小波阈值去噪算法。该算法对含噪声的PCB图像进行小波分解,在对分解后不同尺度下的小波系数按照改进的阈值方法进行处理的基础上,进行PCB图像重构。实验结果表明,该方法的均方根误差以及峰值信噪比值均优于传统的软硬阈值去噪方法,是一种有效的图像滤波算法。
In the application process of automated optical inspection （AOI） of printed circuit board （PCB） image,image denoising is the most vital step. In order to enhance contrast,dynamic range and definition of PCB images,an improved wavelet threshold denoising algorithm is proposed,which can perform wavelet decomposition for PCB images with noise,and then recon-struct PCB images based on pretreatment of the wavelet coefficients under the different scales according to the improved thresh-old method. The experimental results show that the root-mean-square error and peak signal-to-noise ratio value of this method are superior to those of traditional soft and hard threshold denoising method. It is an effective image filtering algorithm.
出处
《现代电子技术》
2014年第2期34-37,共4页
Modern Electronics Technique
基金
国家自然科学基金项目(51307003)
安徽省教育厅重点资助项目(KJ2010A341)
