信息安全与技术
信息安全與技術
신식안전여기술
INFORMATION SECURITY AND TECHNOLOGY
2012年
4期
54-58
,共5页
图像去噪%小波变换%电子元器件%统计模型
圖像去譟%小波變換%電子元器件%統計模型
도상거조%소파변환%전자원기건%통계모형
image de-noising%wavelet packet transform%electronic components%statistic model
在先进电子制造中,为了应用机器视觉方法来完成电子元器件的检测、处理和识别,必须对采集的相关图像进行去噪处理。文章研究了一种基于小波变换统计模型的去噪算法,利用四树复小波包变换把含噪图像高频方向子图分为主要类和次要类。然后,采用非高斯双变量模型和零均值高斯分布模型分别对主要类和次要类复系数进行建模,从而实现噪声抑制功能。实验结果验证了本文方法的有效性。
在先進電子製造中,為瞭應用機器視覺方法來完成電子元器件的檢測、處理和識彆,必鬚對採集的相關圖像進行去譟處理。文章研究瞭一種基于小波變換統計模型的去譟算法,利用四樹複小波包變換把含譟圖像高頻方嚮子圖分為主要類和次要類。然後,採用非高斯雙變量模型和零均值高斯分佈模型分彆對主要類和次要類複繫數進行建模,從而實現譟聲抑製功能。實驗結果驗證瞭本文方法的有效性。
재선진전자제조중,위료응용궤기시각방법래완성전자원기건적검측、처리화식별,필수대채집적상관도상진행거조처리。문장연구료일충기우소파변환통계모형적거조산법,이용사수복소파포변환파함조도상고빈방향자도분위주요류화차요류。연후,채용비고사쌍변량모형화령균치고사분포모형분별대주요류화차요류복계수진행건모,종이실현조성억제공능。실험결과험증료본문방법적유효성。
In advanced electronic manufacturing,the image de-noising processing is very necessary for the machine vision method,which can complete the testing,handling and identification of electronic components.In this paper,a novel image de-noising method based on wavelet packet transform is presented by using a mixed statistical model.The noisy image was decomposed into a low frequency approximation sub-image and some high frequency directional sub-images via the wavelet packet transform,and the high frequency directional sub-images are classified two categories：major coefficients and minor coefficients.So the noise in the major coefficients and the minor coefficients are removed by using of a mixed statistical model combining non-Gaussian bivariate model with zero mean Gaussian distributing model.The simulation has shown the effectiveness of the proposed method.
