小波去噪在智能引线键合机图像处理中的应用

Application of wavelet denoising in image process of intelligent wire bonding machine

针对小波去噪中硬阈值法和软阈值法存在的缺陷,提出了一种新的多尺度自适应阈值选择算法,该方法根据小波变换的特点和噪声信号的3σ准则,对于不同的小波系数乘以一个与自身小波系数相关的降噪因子。在现有的图像去噪评估算法的基础上,提出了基于图像平滑度和匹配度的去噪效果评估算法。实验结果表明:多尺度自适应阈值选择算法能有效去除图像噪声,保留图像细节信息,性能上明显优于传统的软、硬阈值算法。

Because of existing shortcomings in wavelet denoising for the hard-threshold and soft-threshold method,a new multi-scale adaptive algorithm on threshold selection is presented.According to the characteristics of wavelet transform and 3σ-rule in noise signal,a self-noise reduction factor is multiplied by different wavelet coefficients.A new algorithm assessment of image denoising based on matching degree and image smoothness is proposed on the existing assessments of denoising algorithms.Experimental results show that multi-scale adaptive algorithm on threshold selection can effectively remove the image noise,retaining the image details.It significantly superiors to the traditional soft and hard threshold algorithms.