Home   >   CSC-OpenAccess Library   >    Manuscript Information
Use of Discrete Sine Transform for A Novel Image Denoising Technique
Malini Sasikumar, Moni R S
Pages - 204 - 213     |    Revised - 01-06-2014     |    Published - 01-07-2014
Volume - 8   Issue - 4    |    Publication Date - July 2014  Table of Contents
Denoising, Multiresolution, Image Transform, Discrete Sine Transform, Sub Bands.
In this paper, we propose a new multiresolution image denoising technique using Discrete Sine Transform. Wavelet techniques have been in use for multiresolution image processing. Discrete Cosine Transform is also extensively used for image compression. Similar to the Discrete Wavelet and Discrete Cosine Transform it is now found that Discrete Sine Transform also possess some good qualities for image processing; specifically for image denoising. Algorithm for image denoising using Discrete Sine Transform is proposed with simulation works for experimental verification. The method is computationally efficient and simple in theory and application.
1 Google Scholar 
2 CiteSeerX 
3 Scribd 
4 SlideShare 
5 PdfSR 
A.Buades, B.Coll and J.Morel “A review of image denoising algorithm with a new one”Multiscale modeling simulation ,Vol. 4, Issue. 2, pp490-530, 2005.
A.K.Jain, Fundamentals of Digital Image Processing ,PHI, India, 1995.
A.L..Pogam, H.Hanzouli, M.Halt, C.C.L.Rost and D.Visvikis “Denoising of PET images by combining wavelets and curvelets for improved preservation of resolution and quantization”Medical Imaging Analysis, Vol.17, Issue 3, pp877-891, Dec.2013.
A.Pizuria, W.Philips, I.Lemahieu and Acheroy “A versatile wavelet domain noise filtering technique for medical imaging” IEEE Transactions on medical imaging, Vol.22, Issue 3, pp323-331, 2003.
Denver, I.K.Fodor, and C.Kamath “Denoising through wavelet shrinkage, an empirical study”, Electronic Imaging, Vol.12, pp151-160, 2003.
J.Starck, E.J.Cande and D.L.Donho “The curvelet transform for image denoising”, IEEE Transactions on Image Processing, Vol.11, Issue 6, pp 670-684, June 2002.
L.Dhang, W. Dong D.Zhang and G.Shi “Two stage image denoising by principal component analysis with local pixel grouping” Pattern Recognition, Vol.43, pp1531-1549, 2010.
Lizy Abraham, M.Sasikumar “Unsupervised building extraction from high resolution satellite images irrespective of roof top structures” International Journal of Image Processing (IJIP),vol.6, Issue.4, pp 219-232, Aug. 2012.
M. Zhang and B.K.Gunturk “Multiresolution Bilateral filter for image denoising”, IEEE Transactions on Image Processing, Vol.17, No.12,pp 2324-2333, Dec.2008.
M.Do, M.Vitterli “The Contourlet transform: an efficient directional multiresolution image representation” IEEE Transactions on Image Processing, Vol. 14. Issue 12, pp2091-2106,2005.
P.Chatterjee and P.Milanfar, “Is Denoising Dead”, IEEE Transactions on Image Processing,vol.19, No.4, pp. 895-910, Apr. 2010.
R.C.Gonzalez, R.E.Woods, “Digital Image Processing” Pearson, 3rd Edition, India, 2009.
Rajeesh, R.S.Moni, S.Palanikumar and T.Gopalakrishnan “Noise reduction in Magnetic Resonance Images using Wave atom shrinkage” International Journal of Image Processing(IJIP) Vol.4, Issue 2, pp 131-141, Jun 2010.
S. Zhang and M.A. Karim “A new impulse detector for switching median filters”,IEEE Signal Processing Letters, Vol.9, No.11, pp 360-363, Nov.2002.
S.Esakirajan, T.Veerakumar,A.N.Subramanyan and C.H.PremChand “Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter”, IEEE Signal Processing Letters , Vol. 18, No.5, 11287-290, May 2011.
S.G.Chang, B.Yu, V.M.Vitterli, “Adaptive wavelet thresholding for image denoising and compression”, IEEE Trans. Image Processing, Vol.9, No.9, pp. 1532-1546., Sep.2000.
S.Mallat, “A theory of multi resolution signal decomposition, the wavelet representation”,IEEE Transactions Pattern Anal Machine intelligence, Vol.PAM1-11, pp. 674-693., Jul 1989.
Sung-Jea and Y. H. Lee “Center weighted median filters and their applications to image enhancement” IEEE Transactions on circuits and systems , Vol.38, No.9, pp984-993,Sep.1991.
T.R.Vijayakumar, P.T.Vanathi, P.K.Kanagasabhapathy “Fast and efficient algorithm for removal of Gaussian noise in digital images” IAENG International Journal of computer Science, 37:1, Feb.2010.
T.S.Huang and G.Y.Tang “A fast two-dimensional Median Filtering algorithm” IEEE Transactions on Acoustics, speech and signal processing, ASSP-27, pp13-18, 1979.
V.P.S.Naidu, “Discrete cosine Transform based Image Fusion”, Defence Science Journal,Vol.60, No.1, pp.48-54., Jan.2010.
Z.Yang and M.D.Fox, “Speckle reduction and structure enhancement by multichannel median boosted anisotropic diffusion”, EURASIP J. Appl. Signal processing, Vol.2004,issue. 1, pp2492-2502, Jan.2004.
Mr. Malini Sasikumar
Marian Engineering College - India
Dr. Moni R S
Marian Engineering College - India