A Image Denoising Method Based on Median Transform and Pyramid Decomposition

Huang Wen-tao; Bi Du-yan; Mao Bai-xin; Ma Shi-ping

Volume 26 Issue 11

Nov. 2004

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 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.

Citation:

PDF( 1448 KB)

A Image Denoising Method Based on Median Transform and Pyramid Decomposition

Received Date: 2003-06-25
Rev Recd Date: 2003-09-25
Publish Date: 2004-11-19

Abstract

Abstract

A nonlinear multiscalc pyramidal decomposition based on median transform is presented in this paper at first. Then it gives a denoising algorithm which can restore the image distorted by impidse noise and Gaussian noise. The coefficients of the image via the median pyramidal transform represent different characteristics, so the transform can effectively detach noise from image. The different noise coefficients suppression means can be adopted to remove different noise. The simulation result indicates the method is effective, and superior over other methods.

FullText(HTML)

References(1)

References

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.

Relative Articles

Supplements(0)

Cited By

Proportional views