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零件图像的Hilbert扫描-小波分解去噪处理
引用本文:盛党红,夏庆观,温秀兰,邵祥兵.零件图像的Hilbert扫描-小波分解去噪处理[J].中国制造业信息化,2009,38(17).
作者姓名:盛党红  夏庆观  温秀兰  邵祥兵
作者单位:南京工程学院,自动化学院,江苏,南京,211167
基金项目:江苏省教育厅自然基金资助项目 
摘    要:提出了利用图像的Hilbert扫描曲线和小波变换实现图像去噪的方法.将含噪声图像生成为Hilbert扫描矩阵,再将Hilbert扫描矩阵转换为一维向量,对一维向量进行小波分解,提取低频分量并转换为二维矩阵.然后,对二维矩阵进行Hilbert反扫描,完成图像去噪处理.仿真实验结果表明该方法是有效的.

关 键 词:小波分解  Hilbert扫描  去噪处理  零件图像

Analysis on The Depressing Noise Process of Hilbert Curve-Wavelet in Part Image
SHENG Dang-hong,XIA Qing-guan,WEN Xiu-lan,SHAO Xiang-bing.Analysis on The Depressing Noise Process of Hilbert Curve-Wavelet in Part Image[J].Manufacture Information Engineering of China,2009,38(17).
Authors:SHENG Dang-hong  XIA Qing-guan  WEN Xiu-lan  SHAO Xiang-bing
Affiliation:Nanjing Institute of Technology;Jiangsu Nanjing;211167;China
Abstract:It presents a image depressing noise method based on Hilbert curve in image scanning and wavelet analysis. It uses the noising image to generate Hilbert curve based on matrix,transforms the matrix into one-dimensional vector,detects the wavelet low frequency components and transforms them into two-dimensional matrix. This matrix produces Hilbert inverse scanning and the noises of image are removed. Experiment results show that the method can efficiently remove the noises of image.
Keywords:Wavelet Analysis  Hilbert Curve  Depressing Noise Process  Part Image  
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