期刊文献+

基于方向小波的差值滤波图像去噪算法 被引量:2

Algorithm of Differential Filtering for Image Denoising Based on Directionalet
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摘要 针对利用方向小波的多方向框架分割图像时形成的像素序列长度的不同,提出一种新的基于方向小波的差值滤波图像去噪算法。该算法根据白噪声分布规则,将像素序列分成两组,分别采用不同的阈值萎缩方法,并将所产生的方向子图像进一步的作差值滤波处理,最后对所有子图像进行线性平均。对含不同程度高斯白噪声的图像去噪仿真实验表明,与其他小波阈值去噪方法相比,该算法能更有效的去除噪声和保持图像纹理细节,信噪比提高1~3dB。 Image was partitioned into different length pixel sequences by using multi-directional frames. An algorithm based on directionalet and differential filtering for image denoising was proposed. According to Gaussian noise statistical distribution, the pixel sequences were divided into two groups and dealt with different threshoM method respectively. And then, the differential filter was used for all sub-images produced by directionalet and all filtered sub-images were averaged. Experimental results show that the proposed method performs better than other methods, visually and quantitatively.
出处 《系统仿真学报》 EI CAS CSCD 北大核心 2007年第9期2127-2129,2137,共4页 Journal of System Simulation
关键词 图像去噪 方向小波 多方向框架 多方向小波基 差值滤波 image denoising directionalet multi-directional frames multi-directional bases differential filtering
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参考文献10

  • 1Velisavljevic V,Dragotti P L,Vetterli M.Directional Wavelet Transforms and Frames[C]//Proceedings of IEEE International Conference on Image Processing (S1522-4880),2002(3):589-592. 被引量:1
  • 2Velisavljevic V,Beferull-Lozano B,Vetterli M,Dragotti P L.Directionlets:Anisotropic Multi-directional Representation with Separable Filtering[D].IEEE Trans.on Image Proc (S1057-7149),2006,15(7):1916-1933. 被引量:1
  • 3Bresenham J E.Algorithm for Computer Control of a Digital Plotter[J].IBM Systems Journal (S0018-8670),1965,4(1):52-30. 被引量:1
  • 4Foley J D,Dam A V,Feiner S K,Hughes J F.Computer Graphics:Principles and Practice[M].Reading,MA:Adilson-Wesley Publishing Company,1990. 被引量:1
  • 5Velisavljevic V,Beferull-Lozano B,Vetterli M,Dragotti P L.Discrete Multi-directional Wavelet Bases[C]//Proceedings of IEEE International Conference on Image Processing (ISBN0-7803-7750-8),2003,9:1025-1028. 被引量:1
  • 6Donoho D L,Johnstone I M.Ideal Spatial Adaptation via Wavelet Shrinkage[J].Biometrika (S0006-3444),1994,81(3):425-455. 被引量:1
  • 7谢杰成,张大力,徐文立.小波图象去噪综述[J].中国图象图形学报(A辑),2002,7(3):209-217. 被引量:254
  • 8王思贤,曾发龙.平滑图像噪声的差值滤波法[J].电子科学学刊,2000,22(3):411-415. 被引量:16
  • 9Do M N,Vetterli M.The Contourlet Transform:An Efficient Directional Multiresolution Image Representation[J].Image Processing (S1057-7149),IEEE Tran.,2005,14(12):2091-2106. 被引量:1
  • 10Lu Y,Do M N.CRISP-Contourlet:a Critically Sampled Directional Multiresolution Image Representation[C]//in Proc.SPIE Conf.on Wavelet Applications in Signal and Image Processing.2003. 被引量:1

二级参考文献67

  • 1[9]You Yuli, Kaveh D. Fourth-order partial differential equations for noise removal[J]. IEEE Trans. Image Processing, 2000,9(10):1723~1730. 被引量:1
  • 2[10]Bouman C, Sauer K. A generalized Gaussian image model of edge preserving map estimation[J]. IEEE Trans. Image Processing, 1993,2(3):296~310. 被引量:1
  • 3[11]Ching P C, So H C, Wu S Q. On wavelet denoising and its applications to time delay estimation[J]. IEEE Trans. Signal Processing,1999,47(10):2879~2882. 被引量:1
  • 4[12]Deng Liping, Harris J G. Wavelet denoising of chirp-like signals in the Fourier domain[A]. In:Proceedings of the IEEE International Symposium on Circuits and Systems[C]. Orlando USA, 1999:Ⅲ-540-Ⅲ-543. 被引量:1
  • 5[13]Gunawan D. Denoising images using wavelet transform[A]. In:Proceedings of the IEEE Pacific Rim Conference on Communications, Computers and Signal Processing[C]. Victoria BC,USA, 1999:83~85. 被引量:1
  • 6[14]Baraniuk R G. Wavelet soft-thresholding of time-frequency representations[A]. In:Proceedings of IEEE International Conference on Image Processing[C]. Texas USA,1994:71~74. 被引量:1
  • 7[15]Lun D P K, Hsung T C. Image denoising using wavelet transform modulus sum[A]. In:Proceedings of the 4th International Conference on Signal Processing[C]. Beijing China,1998:1113~1116. 被引量:1
  • 8[16]Hsung T C, Chan T C L, Lun D P K et al. Embedded singularity detection zerotree wavelet coding[A].In:Proceedings of IEEE International Conference on Image Processing[C]. Kobe Japan, 1999:274~278. 被引量:1
  • 9[17]Krishnan S, Rangayyan R M. Denoising knee joint vibration signals using adaptive time-frequency representations[A]. In:Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering 'Engineering Solutions for the Next Millennium[C]. Alberta Canada, 1999:1495~1500. 被引量:1
  • 10[18]Liu Bin, Wang Yuanyuan, Wang Weiqi. Spectrogram enhancement algorithm: A soft thresholding-based approach[J]. Ultrasound in Medical and Biology, 1999,25(5):839~846. 被引量:1

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