二元收缩方程与复数小波用于SAR影像去噪
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摘要
二元收缩方程定义了由相邻尺度小波系数的联合概率密度函数,其与噪声模型联立后利用最大后验概率估计可进行图像去噪。在SAR图像斑点噪声服从瑞利分布的假设下,结合双树复数小波变换推导了基于二元收缩方程的SAR图像的简化去噪模型,然后利用局部方差估计和维纳滤波器获得噪声方差与带噪小波系数方差的估计值,并计算出合适阈值对SAR图像进行去噪。实验结果显示,去噪图像的峰值信噪比以及有效视数都较其它算法有大幅提高,且很好地保持了图像的边缘特征。
Bivariate shrinkage functions (BSF) statistically denoted as joint probability density functions (PDF) and noise PDF could be united by MAP to de-noise image. The intensity of speckle was hypothesized to be distributed according to Rayleigh distribution. Then SAR image de-noising modal based on BSF and dual-tree complex wavelet transform (DT-CWT) was constructed and reduced. Local variance estimation and wiener filter were used to estimate noise variance and noisy wavelet coefficients variance, which were used to choose an appreciated threshold to de-noise SAR image. Experiment results demonstrate that PSNR and ENL values of de-noised images are extremely larger than other algorithms and edge features have been perfectly preserved.
Bivariate shrinkage functions (BSF) statistically denoted as joint probability density functions (PDF) and noise PDF could be united by MAP to de-noise image. The intensity of speckle was hypothesized to be distributed according to Rayleigh distribution. Then SAR image de-noising modal based on BSF and dual-tree complex wavelet transform (DT-CWT) was constructed and reduced. Local variance estimation and wiener filter were used to estimate noise variance and noisy wavelet coefficients variance, which were used to choose an appreciated threshold to de-noise SAR image. Experiment results demonstrate that PSNR and ENL values of de-noised images are extremely larger than other algorithms and edge features have been perfectly preserved.
引文
[1]肖国超,朱彩英.雷达摄影测量[M].北京:地震出版社,2001.
[2]David Donoho L.De-noising by Soft-thresholding[J].IEEE Transac-tions on Information Theory(S0018-9448),1995,41:613-627.
[3]王炜华,沈振康.用小波变换抑制SAR图像中的斑点噪声[J].红外与激光工程,2002,31(1):14-17.
[4]张俊,柳建.SAR图像斑点噪声的小波软门限滤除算法[J].测绘学报,1998,27(2):119-124.
[5]Nick Kingsbury,Julian Magarey.Wavelet Transforms in Image Processing[C]//Proc.First European Conference on Signal Analysis and Prediction,Prague,1997.Prague,1997:23-34.
[6]N Kingsbury.The Dual-tree Complex Wavelet Transform:A New Technique for Shift-invariance and Directional Filters[R].DSPWorkshop,1998.
[7]Nick Kingsbury.The Dual-tree Complex Wavelet Transform:A New Efficient Tool for Image Restoration and Enhancement[C]//Proc.European Signal Processing Conference,EUSIPCO98,Rhodes,1998:319-322.
[8]Peter de Rivaz,Nick Kingsbury.Bayesian Image De-convolution and De-noising Using Complex Wavelets[C]//Proc.IEEE Conf.on Image Processing,Greece,Oct8-10,2001.Greece,2001:2639.
[9]易翔,王蔚然.复数小波统计模型在图像降噪中的应用[J].光电工程,2004,31(8):69-72.
[10]杨蒙召,李朝峰,许磊.基于复数小波和H-Curve准则对图像的去噪[J].计算机应用,2005,25(4):769-774.
[11]易翔,王蔚然.一种概率自适应图像去噪模型[J].电子学报,2005,33(1):63-66.
[12]王红霞,成礼智,吴翊.基于复数小波变换增强带噪图像的空间自适应方法[J].计算机辅助设计与图形学学报,2005,17(9):1911-1916.
[13]Levent S Endur,Ivan W Selesnick.Bivariate Shrinkage Functions for Wavelet-Based Denoising Exploiting Interscale Dependency[J].IEEE transactions on signal processing(S1053-587X),2002,50(11):2744-2756.
[14]Levent S Endur,Ivan W Selesnick.A Bivariate Shrinkage Function for Wavelet-based Denoising[C]//Acoustics,Speech,and Signal Processing,Proceedings(ICASSP'02).IEEE International Conference.USA:IEEE,2002,2:1261-1264.
[15]Levent S Endur,Ivan W Selesnick.Bivariate Shrinkage with Local Variance Estimation[J].IEEE signal processing letters(S1070-9908),2002,9(12):438-441.
[16]Marc Simard,Gianfranco De Grandi,Keith P B Thomson,Goze B B′eni′e.Analysis of Speckle Noise Contribution on Wavelet Decomposition of SAR Images[J].IEEE transactions on geoscience and remote sensing(S0196-2892),1998,36(6):1953-1962.
[17]A Jalobeanu,L Blanc-Féraud,J Zerubia.Satellite Image Deconvolution Using Complex Wavelet Packets[R].Thème3-Interaction homme-machine,images,données,connaissances Projet Ariana Rapport de recherche n,2000.France,2000:3955-116.
[2]David Donoho L.De-noising by Soft-thresholding[J].IEEE Transac-tions on Information Theory(S0018-9448),1995,41:613-627.
[3]王炜华,沈振康.用小波变换抑制SAR图像中的斑点噪声[J].红外与激光工程,2002,31(1):14-17.
[4]张俊,柳建.SAR图像斑点噪声的小波软门限滤除算法[J].测绘学报,1998,27(2):119-124.
[5]Nick Kingsbury,Julian Magarey.Wavelet Transforms in Image Processing[C]//Proc.First European Conference on Signal Analysis and Prediction,Prague,1997.Prague,1997:23-34.
[6]N Kingsbury.The Dual-tree Complex Wavelet Transform:A New Technique for Shift-invariance and Directional Filters[R].DSPWorkshop,1998.
[7]Nick Kingsbury.The Dual-tree Complex Wavelet Transform:A New Efficient Tool for Image Restoration and Enhancement[C]//Proc.European Signal Processing Conference,EUSIPCO98,Rhodes,1998:319-322.
[8]Peter de Rivaz,Nick Kingsbury.Bayesian Image De-convolution and De-noising Using Complex Wavelets[C]//Proc.IEEE Conf.on Image Processing,Greece,Oct8-10,2001.Greece,2001:2639.
[9]易翔,王蔚然.复数小波统计模型在图像降噪中的应用[J].光电工程,2004,31(8):69-72.
[10]杨蒙召,李朝峰,许磊.基于复数小波和H-Curve准则对图像的去噪[J].计算机应用,2005,25(4):769-774.
[11]易翔,王蔚然.一种概率自适应图像去噪模型[J].电子学报,2005,33(1):63-66.
[12]王红霞,成礼智,吴翊.基于复数小波变换增强带噪图像的空间自适应方法[J].计算机辅助设计与图形学学报,2005,17(9):1911-1916.
[13]Levent S Endur,Ivan W Selesnick.Bivariate Shrinkage Functions for Wavelet-Based Denoising Exploiting Interscale Dependency[J].IEEE transactions on signal processing(S1053-587X),2002,50(11):2744-2756.
[14]Levent S Endur,Ivan W Selesnick.A Bivariate Shrinkage Function for Wavelet-based Denoising[C]//Acoustics,Speech,and Signal Processing,Proceedings(ICASSP'02).IEEE International Conference.USA:IEEE,2002,2:1261-1264.
[15]Levent S Endur,Ivan W Selesnick.Bivariate Shrinkage with Local Variance Estimation[J].IEEE signal processing letters(S1070-9908),2002,9(12):438-441.
[16]Marc Simard,Gianfranco De Grandi,Keith P B Thomson,Goze B B′eni′e.Analysis of Speckle Noise Contribution on Wavelet Decomposition of SAR Images[J].IEEE transactions on geoscience and remote sensing(S0196-2892),1998,36(6):1953-1962.
[17]A Jalobeanu,L Blanc-Féraud,J Zerubia.Satellite Image Deconvolution Using Complex Wavelet Packets[R].Thème3-Interaction homme-machine,images,données,connaissances Projet Ariana Rapport de recherche n,2000.France,2000:3955-116.
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