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小波多分辩率分析在图像滤波中的应用
引用本文:黄晓红,范小志,顾彦飞.小波多分辩率分析在图像滤波中的应用[J].河北理工学院学报,2008,30(2):27-31.
作者姓名:黄晓红  范小志  顾彦飞
作者单位:河北理工大学信息学院,河北师范大学物理科学与信息工学院,重庆大学通信工程学院 河北 唐山 063009,河北 石家庄 030023,重庆 400044
摘    要:小波闲值滤波基本思想是在小波分解后的各层系数中,对模大于和小于某个阈值的系数分别进行处理。主要针对图像滤波,利用正交小波(db4)和双正交(9/7小波)对三种滤波函数尺度的相关性和滤波图形效果进行比较。由实验可以发现,正交小波(db4)时,半软阈值函数滤波效果较好;双正交小,波(9/7小波)软阚值函数滤波效果较好;正交小波(db4)相对于双正交小波(9/7小波)有效的滤波特性。最后,还通过中值滤波算法对硬阈值滤波函数进行改进。

关 键 词:多分辨率分析  阈值  滤波
文章编号:1674-0262(2008)02-0027-05
修稿时间:2007年5月14日

The Application of Wavelet Multi-resolution Analysis in Image Filtering
HUANG Xiao-hong FAN Xiaozhi GU Yan-fei .College of Information,Hebei Polytechnic University,Tangshan Hebei ,China, .School of Physics and Information Hebei Normal University Shijiazhuang China, .College of Telecommunication Engineering,Chongqing University,Chongqing,China.The Application of Wavelet Multi-resolution Analysis in Image Filtering[J].Journal of Hebei Institute of Technology,2008,30(2):27-31.
Authors:HUANG Xiao-hong FAN Xiaozhi GU Yan-fei College of Information  Hebei Polytechnic University  Tangshan Hebei  China  School of Physics and Information Hebei Normal University Shijiazhuang China  College of Telecommunication Engineering  Chongqing University  Chongqing    China
Institution:HUANG Xiao-hong~1 FAN Xiaozhi~2 GU Yan-fei~3 1.College of Information,Hebei Polytechnic University,Tangshan Hebei 063009,China, 2.School of Physics and Information Hebei Normal University Shijiazhuang 03002 China, 3.College of Telecommunication Engineering,Chongqing University,Chongqing,400044,China
Abstract:The main idea of wavelet threshohl filtering is based on the processing method of the wavelet coefficients. which is bigger or smaller than threshold coefficient.The processing method is according to the absolute figures.The article is aimed at fihering noise in image with orthogonai wavelet (db4) and biothogonal wavelet (9/7) in three filtering functions.The consequences are compared in two aspects:one is relativity of scalevalues.another is effects of filered images.According to the experiments,we can conclude that half-soft threshohl filtering fimction does better with orthogonal wavelet (db4) and soft threshohi filtering function with biorthogonal wavelet (9/7).and orthogonal wavelet (db4) has better filtering specialities than biorthogonal wavelet (9/7).In the end,the hard threshold filte- ring function is ameliorated with median filtering algorithm.
Keywords:muhiresolution analysis  threshold  filtering
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