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小波去噪在智能引线键合机图像处理中的应用
引用本文:张和颖,戚其丰,李浩.小波去噪在智能引线键合机图像处理中的应用[J].传感器与微系统,2011,30(4):134-137.
作者姓名:张和颖  戚其丰  李浩
作者单位:华南理工大学,精密电子制造装备教育部工程研究中心,自动化学院,广东,广州,510640
基金项目:国家自然科学基金重点资助项目
摘    要: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...

关 键 词:小波变换  引线键合  噪声  阈值  局部方差

Application of wavelet denoising in image process of intelligent wire bonding machine
ZHANG He-ying,QI Qi-feng,LI Hao.Application of wavelet denoising in image process of intelligent wire bonding machine[J].Transducer and Microsystem Technology,2011,30(4):134-137.
Authors:ZHANG He-ying  QI Qi-feng  LI Hao
Abstract: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.
Keywords:wavelet transform  wire bonding  noise  threshold  local variance
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