高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于中值变换和金字塔分解的图像去噪方法

黄文涛 毕笃彦 毛柏鑫 马时平

黄文涛, 毕笃彦, 毛柏鑫, 马时平. 基于中值变换和金字塔分解的图像去噪方法[J]. 电子与信息学报, 2004, 26(11): 1686-1692.
引用本文: 黄文涛, 毕笃彦, 毛柏鑫, 马时平. 基于中值变换和金字塔分解的图像去噪方法[J]. 电子与信息学报, 2004, 26(11): 1686-1692.
Huang Wen-tao, Bi Du-yan, Mao Bai-xin, Ma Shi-ping. A Image Denoising Method Based on Median Transform and Pyramid Decomposition[J]. Journal of Electronics & Information Technology, 2004, 26(11): 1686-1692.
Citation: Huang Wen-tao, Bi Du-yan, Mao Bai-xin, Ma Shi-ping. A Image Denoising Method Based on Median Transform and Pyramid Decomposition[J]. Journal of Electronics & Information Technology, 2004, 26(11): 1686-1692.

基于中值变换和金字塔分解的图像去噪方法

A Image Denoising Method Based on Median Transform and Pyramid Decomposition

  • 摘要: 该文基于中值变换提出了一种信号的非线性多尺度金字塔分解算法,然后给出了一种利用它来对同时含有脉冲噪声和高斯噪声图像的去噪方法。由于图像经过中值金字塔变换后的系数表现出不同的特点,能对噪声产生有效的分离,可以对不同的噪声采用不同的系数抑制方法来达到去噪的目的。仿真试验结果表明本方法很有效,且优于其它方法。
  • Burt P, Adelson E. The Laplacian pyramid as a compact image code[J].IEEE Trans. on Commun.1983, 31(4):532-540[2]Donoho D L, Yu T P Y. Robust nonlinear wavelet transform based on median-interpolation.Conf. Rec. Thirty-First Asilomar Conf. Signals, Syst. Comput., 1997, 1: 75-79.[3]Starck J L, Murtagh F, Louys M. Astronomical image compression using the pyramidal median transform. IV. ASP Conference Series, 1995, 77(1): 162-165. [4] Melnik V P, Shmulevich I, Egiazarian K, Astola J. Block-median pyramidal transform: analysis and denoising applications. IEEE Trans. on IP, 2001, 49(2): 364-372.[4]Melnik V, Shmulevich I, Egiazarian K, Astola J. Image denoising using a block-median pyramid,in Proc. IEEE Int. Conf. Image Process., Kobe, Japan, 1999: 84-87.[5]Yin L, Yang B, Gabbouj M. Weighted median filters: a tutorial[J].IEEE Trans. Circuits Syst. .1996, 43(3):157-192[6]Donoho D L. Denoising by soft thresholding. IEEE Trans. Info. Theory, 1994, 41(3): 613-627.[7]Zervakis M E, Sundararajan V, Parhi K K. A wavelet-domain algorithm for denoising in the presence of noise outliers. Washington, DC, USA, 1997, 1: 632-635.[8]Chang S G, Yu B, Vetterli M. Spatially adaptive wavelet thresholding with context modeling for image denoising, IEEE Trans. on IP, 2000, 9(9): 1522-1531.[9]Gong W, Shi Q Y, Cheng M D. CB morphology and its applications, Proc. Int. Conf. for Young Computer Scientists, Beijing, 1991: 260-264.
  • 加载中
计量
  • 文章访问数:  3011
  • HTML全文浏览量:  83
  • PDF下载量:  607
  • 被引次数: 0
出版历程
  • 收稿日期:  2003-06-25
  • 修回日期:  2003-09-25
  • 刊出日期:  2004-11-19

目录

    /

    返回文章
    返回