A Survey on Image Denoising based on Wavelet Transform

Authors

  • Jyotsna Sardar  Department of CSE, OP Jindal University, Raigarh, Chhattisgarh, India
  • Pradeep Rusiya  Department of CSE, OP Jindal University, Raigarh, Chhattisgarh, India

Keywords:

Genetic Algorithm, Image Denoising, Threshold, Wavelet Transform, Gaussian Noise

Abstract

The processing of images results in a huge amount of noise in the processed image inevitably.Hence, it is required to apply image denoising techniques to improve quality of the image.So far many algorithms have been proposed under different conditions to achieve better performance.These algorithms consist of some filtering and threshold parameters. Because of higher performance rate of Wavelet Transform method,it has been used widely. In this paper, we are going to go through image denoising techniques and focus mainly on the wavelet transform method used for denoising image.

References

  1. H. Zhang, Aria Nosratinia, and R. O. Wells, Jr.,"Image denoising via wavelet-domain spatially adaptive FIR Wiener filtering", in IEEE Proc. Int. Conf. Acoust., Speech, Signal Processing, Istanbul, Turkey, June2000.
  2. H. Guo, J. E. Odegard, M. Lang, R. A. Gopinath, I.W. Selesnick, and C. S. Burrus, "Wavelet based speckle reduction with application to SAR based ATD/R," First Int'l Conf. on Image Processing, vol. 1, pp. 75-79, Nov. 1994.
  3. Andrea Polesel, Giovanni Ramponi, And V. John Mathews, "Image Enhancement Via Adaptive Unsharp Masking" IEEE Transactions On Image Processing, Vol. 9, No. 3, March 2000, Pp505-509.
  4. G. Y. Chen, T. D. Bui And A. Krzyzak, Image Denoising Using Neighbouring wavelet Coefficients, Icassp ,Pp917-920.
  5. Donoho.D.L,Johnstone.I.M, "Ideal spatial adaptation via wavelet shrinkage", Biometrika,81,pp.425-455,1994.
  6. Gao Zhing, Yu Xiaohai, "Theory and application of MATLAB Wavelet analysis tools", National defense industry publisher,Beijing,pp.108-116, 2004.
  7. P. Coupe, J. V. Manjon, M. Robles and D. L. Collins, "Adaptive multiresolution non-local means filter for three-dimensional magnetic resonance image denoising", IET Image Processing, vol. 6, no. 5, (2012), pp. 558-568.
  8. G. S. Pai and C. V. Jiji, "A stochastic image denoising algorithm using 3-D block filtering under a non-local means framework", ACM International Conference Proceeding Series, 2012, Proceedings - 8th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2012, (2012).
  9. D. –N. Barak, A. Stern, Y. Yitzhak and N. Kopeika, "Infrared image denoising by non-local means filtering. Source: Proceedings of SPIE - The International Society for Optical Engineering", 8399, Visual Information Processing XXI, (2012).

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-06-30

Issue

Volume 3, Issue 5, May-June-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Jyotsna Sardar, Pradeep Rusiya, " A Survey on Image Denoising based on Wavelet Transform" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.1089-1092, May-June-2018.