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1、第31卷第11期null null null null null null null null null 西南大学学报(自然科学版) null null null null null null null null null null null 2009年11月Volnull31 null Nonull11 Journal of Southwest University (Natural Science Edition) Novnull null 2009 c I | : 1673null9868( 2009)11null0125null04+ m . Z E 1 null唐娅琴1, 21nul
2、l i D S v $ D , i 400016; 2null 2 v S / L i , 2 210096K 1 : 图像处理过程中, 图像降噪是底层的处理, 将影响图像的后继分析处理质量. 在介绍了现有的几种图像去噪方法的原理, 算法及各自的优缺点后, 利用仿真实验, 对比几种方法在去噪中的应用, 给出实验结果. 并采用了客观评价指标比较几种方法.1 null o null M : 去噪; 小波; 变分 m s | : TP751 D S M : A m ) V , m , . ) . . 2 V ? m a V 3 ,9 V ? m . V 3 . . 2 i v m . m ? ) a
3、s Y . , . ) B m ) 9 j $ . B z Z E . 2 H ? z m H % .m V :g(x, y) = f (x, y)+ n(x, y) (1) f (x, y) c . 2 X m , g(x, y) L = 4 m , n(x, y) . 2 . m . 5 s a 0 F: R R, P F(g(x, y) = f (x, y) (2)1null + . Z E s 1 . 1 . 2 | q s . | s a u , m % s u , 7 . 2 1 9 s u . . d . Z E ( r o r o 1 | m s r .1null1null (
4、 r o 1 | # = ( 9 ) . Y # | N ! N Z 3g , . m g(x, y) = 1M (i, j) # sg(i, j ) (3) , s (x, y) # = , M s 9 .| ( r o T B , | # = F ( 9 , F ( r o . V A , v . F ( E V V U g(x, y) = (i, j) # snull(i, j )g(i, j) (4)null(i, j ) , V U T v l .1null2null r oN Z E M # 9 . B r o .Vout = mediana1, a2, a3, an (5)a1,
5、 a2, a3, ,an # . , r o m g(x, y) (x, y) N ! N 3g W .nulll : 2009null04null11 : 7 v ? Z 9 (IRT0611).T e : V (1976null), o , + r , V 3 , = , 1 V Y m ) .1null3null l o M . Z E 2 M , l o d ? Z , z H + , L = d s H , h H % + T . 7 O 1 p s Z , p s Z 1 4 , E , l 9 5 . I D : 1 null . 9 m ) E $ M . : S , 2005
6、: 85null91. 2 null V . m s M . : S , 2005: 210null211. 3 null k , x , null , . l o M 4 | D X; m H J . 2 = S v (1 S ),2001, 26( 4) : 462null465. 4 null Donoho D L, Johnstone I M. Adapting to U nknown Smoothness Via Wavelets Shrinkage J . Journal of the AmericanStatistical Association, 1995, 90(432):
7、1200null1224. 5 null Chang S G, Yu B, Vetterli M. AdaptiveWavelet Thresholding for ImageDenoising and Compression J. IEEE Transnullactions on Image Processing, 2000, 9(9) : 1532null1546. 6 null Rudin L I, Osher S, Fatemi E. Nonlinear Total Variation Based Noise Removal Algorithms J. physica D, 1992,
8、 60:259null268. 7 null null , , f . M s s Z m / M. : v , 2008: 56null57. 8 null null . m . y _ s Q E J . h v (1 S ), 2008, 23(1): 30null35.A Review of Several Image Smoothing and Denoising MethodsTANG Yanullqin1, 21null School of Basic Medical Science, Chongqing Medical University, Chongqing 400016,
9、 China;2null Laboratory of Image Science and Technology, Southeast University, Nanjin Jiangsu 210096, ChinaAbstract: In image process, denoising is a lownulllevel process and will definitely affect the final analyis andprocessing quality. This paper introduces several popular methods in image denoising. We explain theirbasic theories, give out their algorithms and analyze and compare the experiment results of different methods.Key w
