Novel Technique for Image Denoising Using Adaptive Haar Wavelet Transformation
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DOI: https://doi.org/10.15866/irecos.v10i10.7636
Abstract
Additive noise is a serious problem as it degrades the quality of the image. It is often required to reconstruct the original image by suppressing noise even before it is processed. This procedure is known as image de-noising. Many de-noising techniques have been proposed in the recent past which are unique in their approach to filtering noise. Wavelets have evolved as one of the excellent tools for such de-nosing problems. In this paper one such technique which is referred to as adaptive HAAR wavelet (HW) is employed. The proposed technique produced dominant results when compared with other existing techniques and standard HW.
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Anil K. Jain. Fundamentals of Digital Image Processing. India: Dorling indersley Pvt. Ltd., licensees of Pearson Education in Sour Asia, 2008, pp. 298-314.
Dongwook Cho. Image Denoising Using Wavelet Transforms. Germany: VDM Verlag Dr. Muller Aktiengesellschaft Co. 2008. p. 13.
A. Buades, B. Coll, and J. M. Morel. “A review of image denoising algorithms, with a new one.” Multiscale Model. Simul., Vol. 4, No. 2, pp. 490-530, Jul. 2005.
http://dx.doi.org/10.1137/040616024
I. Daubechies, Ten lectures on wavelets, Proceedings CBMS-NSF Regional Conference Series in Applied Mathematics, SIAM, vol. 61, 1992.
http://dx.doi.org/10.1006/jath.1994.1093
M. Vetterli, J. Kovacevic, Wavelets and subband coding, Englewood Cliffs, NJ, Prentice Hall, 1995.
J.N.Ellinas, M.S.Sangriotis, Modern Techniques of Image Compression, 2nd Conference of « Archipelagos Technologies », Piraeus, April 2002.
C.S.Burrus, R.A.Gopinath, H.Guo, “Introduction to Wavelets and Wavelet Transforms”, Prentice Hall, 1998, pp. 2-18.
http://dx.doi.org/10.1016/b978-0-12-174590-5.50024-1
G. Strang, T. Nguyen, “Wavelets and Filter Banks”, Wellesley,1997.
http://dx.doi.org/10.1109/icassp.2002.1005973
David L. Donoho and Iain M. Johnstone. “Adapting to Unknown Smoothness via Wavelet Shrinkage.” Journal of the American Statistical Association, Vol. 90, No. 432, pp. 1200-1224, Dec. 1995.
http://dx.doi.org/10.1080/01621459.1995.10476626
David L. Donoho. “De-noising by soft-thresholding.” IEEE Trans. on Information Theory, Vol 41, No. 3, May 1995.
http://dx.doi.org/10.1109/18.382009
David L. Donoho. “Unconditional bases are optimal bases for data compression and for statistical estimation.” Applied and Computational Harmonic Analysis, Vol. 1, No. 1, pp. 100-115, Dec. 1993.
http://dx.doi.org/10.1006/acha.1993.1008
D.L. Donoho, I.M. Johnstone, Wavelet shrinkage: Asymptopia, J.R. Stat. Soc., series B, vol. 57, no. 2, pp. 301-369, 1995.
Matlab Wavelet Toolbox User’s Guide, MathWorks, 1996.
Stephane G. Mallat. “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, No. 7, Jul. 1989.
http://dx.doi.org/10.1109/34.192463
M. K. Michak, Igor Kozintsev, Kannan Ramchandran, and Pierre Moulin. “Low-Complexity Image Denoising Based on Statistical Modeling of Wavelet Coefficients.” IEEE Signal Processing Letters, Vol. 6, No. 12, pp. 300-302, Dec. 1999.
http://dx.doi.org/10.1109/97.803428
Javier Portilla, Vasily Strela, Martin J. Wainwright, and Eero P. Simoncelli. “Image Denoising Using Scale Mixtures of Gaussian in the Wavelet Domain.” IEEE Transactions on Image Processing, Vol. 12, No. 11, pp. 1338-1351, Nov. 2003.
http://dx.doi.org/10.1109/tip.2003.818640
Jens Krommweh. “Tetrolet Transform: A New Adaptive Haar Wavelet algorithm for Sparse Image Representation.” Research paper, Department of Mathematics, University of Duisburg-Essen, Germany, 2009.
http://dx.doi.org/10.1016/j.jvcir.2010.02.011
Jin Wang, Yanwen Guo, Yiting Ying, Yanli Liu, and Qunsheng Peng. “Fast non-local Algorithm for Image Denoising.” IEEE International conference on Image Processing, pp. 1429-1432, Oct. 2006.
http://dx.doi.org/10.1109/icip.2006.312698
S. Grace Chang, Bin YU, and Martin Vetterli. “AdaptiveWavelet Thresholding for Image Denoising and Compression.” IEEE Transactions on Image Processing, Vol. 9, No. 9, pp. 1532-1546, Sep. 2000.
http://dx.doi.org/10.1109/83.862633
N. G. Kingsbury. “Complex wavelets for shift invariant analysis and filtering of signals.” Journal of Applied and Computational Harmonic Analysis, Vol. 10, No. 3, pp. 234-253, May 2001.
http://dx.doi.org/10.1006/acha.2000.0343
Rajathi, G.M., Rangarajan, R., A new dual tree wavelet based image denoising using fuzzy shrink and lifting scheme, (2013) International Review on Modelling and Simulations (IREMOS), 6 (2), pp. 668-675.
Subrahmanyam, C., Venkata Rao, D., Usha Rani, N., Implementation of no reference distortion patch features image quality assessment algorithm based on human visual system, (2014) International Journal on Communications Antenna and Propagation (IRECAP), 4 (5), pp. 195-201.
http://dx.doi.org/10.15866/irecap.v4i5.4166
Udaya Kumar, N., Krishna Rao V., E., Madhavi Latha, M., Multi Directional Wavelet Filter Based Region of Interest Compression for Low Resolution Images, (2015) International Journal on Communications Antenna and Propagation (IRECAP), 5 (2), pp. 54-62.
http://dx.doi.org/10.15866/irecap.v5i2.4554
Wang, K., Liao, R., Yang, L., Yuan, L., Wu, F., Duan, L., Nonnegative matrix factorization aided principal component analysis for high-resolution partial discharge image compression in transformers, (2013) International Review of Electrical Engineering (IREE), 8 (1), pp. 479-490.
Wojtaszczyk, P. A Mathematical Introduction to Wavelets. Cambridge University press, Cambridge, U.K, 1997.
http://dx.doi.org/10.1017/cbo9780511623790
Meyer, Y. Wavelets: their past and their future, Progress in Wavelet Analysis and its Applications. Gif-sur-Yvette, pp 9-18, 1993.
Morlet, J.; Arens, G.; Fourgeau, E. and Giard, D. Wave propagation and sampling theory, Part1: Complex signal land scattering in multilayer media. Journal of Geophysics, 47: 203-221, 1982.
http://dx.doi.org/10.1190/1.1441328
Strang, G. Wavelets and Dilation Equations: A brief introduction. SIAM Review, 31: 614-627, 1989.
http://dx.doi.org/10.1137/1031128
Walnut, D.F. An Introduction to Wavelet Analysis. Birkhäuser, Boston, 2001.
Wells, R.O. Parametrizing Smooth Compactly Supported Wavelets. Transform American Mathematical Society, 338(2): 919-931, 1993.
http://dx.doi.org/10.1090/s0002-9947-1993-1107031-8
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