期刊文献+

基于提升小波的图像脉冲噪声抑制方法

Approach of Image Impulse Noise Reduction Based on Li fting Wavelet
下载PDF
导出
摘要 分析利用小波进行图像去噪的方法和特点 ,根据电视跟踪测量系统的实际需要提出利用易于硬件实现的提升小波滤波器对实时图像进行去噪 ,重点研究受脉冲干扰的实时图像的噪声抑制问题。小波分解的高频部分在噪声附近具有较大值 ,通过调整提升项设计提升小波滤波器 ,所设计的滤波器包含噪声特性 ,应用这些滤波器可以检测到脉冲噪声 ,利用小波的重构公式消去图像中的噪声。由于提升小波滤波器比普通小波滤波器运算量大大减少 ,因此算法易于硬件实现。 The method and characteristic of image denoising using w avelet were analysed. According to the demand of TV tracking system , an approa ch of noise reduction from real-time image using the lifting scheme wavelet that can be implemented on hardware easily was presented. The emphasis was impulse n oise reduction. High frequency components obtained by wavelet decomposition was large around impulse noise .Lifting wavelet filters were designed by changing th eir free parameters.The designed filters had features of impulse noise. Detectio n of impulse noise can be done by applying the learnt filters to noising images. Reduction of impulse noise from the image was carried out using a wavelet reco nstruction formula. Because the computation of lifting scheme filter was decreas ed largely than general wavelet filters, the algorithm was implemented easily o n hardware. There would be a perfect perspective if the lifting wavelet denoisin g method were combined with the modern signal processing devices DSP and FPGA.
出处 《长春理工大学学报(自然科学版)》 2004年第3期76-79,共4页 Journal of Changchun University of Science and Technology(Natural Science Edition)
关键词 图像处理 脉冲噪声 提升小波 Image processing Impulse noise lifting wavelet
  • 相关文献

参考文献9

  • 1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
  • 2Xie Jie-cheng,Zhang Da-li.Overvier on Wavelet Image Denoising .Jounal of Image and Graphics. 2002,7(3):1-6.
  • 3Donoho D L, Johnstone I m, Kerkyacharian G et al. Wavelet shrinkage :asymptopia. Journal of royal statistics society series (B),1995:301-369
  • 4W. Sweldens. The lifting scheme: A custom-design construction of second generation wavelet SIMA Journal of Mathematical Analysis. 1998,29(2):511-546
  • 5W.Sweldens.The lifting scheme: A custom-design construction of biorthogonal wavelets. Applied and Computational Harmonic Analysis.1996,3(2):186-200
  • 6S.Takano and K.NIIJIMA,'Sub-image extraction by learnt lifting wavelet filters,"" Processing of the Fifth International Symposium Signal Processing and its Applications,1999,pp.309-312
  • 7E.Abreu,M. Lightstone, S. K. Mitra and K. Arakawa, ""A new efficient approach for the removal of impulse noise from highly corrupted images,"" IEEE Trans. on Image Processing, 1996,5(6):1012-1025
  • 8K.Kuzume and K.niijima, ""Wavelets with convolution-type orthogonality conditions ,""IEEE Trans. Signal Processing, 1999,PP.408-421
  • 9S.Mallat and W.L.Hwang,""Singularity detection and processing with wavelets,""IEEE Trans.on Information Theory,1992,38(2):617-643

二级参考文献66

  • 1[9]You Yuli, Kaveh D. Fourth-order partial differential equations for noise removal[J]. IEEE Trans. Image Processing, 2000,9(10):1723~1730.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

共引文献253

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部