CFP last date
20 May 2024
Reseach Article

Image Denoising using K-SVD Algorithm based on Gabor Wavelet Dictionary

by Wael Khedr, Rehab Ali, Fawzan Ismail
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 2
Year of Publication: 2012
Authors: Wael Khedr, Rehab Ali, Fawzan Ismail
10.5120/9521-3926

Wael Khedr, Rehab Ali, Fawzan Ismail . Image Denoising using K-SVD Algorithm based on Gabor Wavelet Dictionary. International Journal of Computer Applications. 59, 2 ( December 2012), 30-33. DOI=10.5120/9521-3926

@article{ 10.5120/9521-3926,
author = { Wael Khedr, Rehab Ali, Fawzan Ismail },
title = { Image Denoising using K-SVD Algorithm based on Gabor Wavelet Dictionary },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 2 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 30-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number2/9521-3926/ },
doi = { 10.5120/9521-3926 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:05:03.519822+05:30
%A Wael Khedr
%A Rehab Ali
%A Fawzan Ismail
%T Image Denoising using K-SVD Algorithm based on Gabor Wavelet Dictionary
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 2
%P 30-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image denoising problem can be addressed as an inverse problem. One of the most recent approaches to solve an inverse problem is a sparse decomposition over overcomplete dictionaries. In sparse representation, images are represented as a linear combination of dictionary atoms. In this paper, we propose an algorithm for image denoising based on Orthogonal Matching Pursuit (OMP) for determining sparse representation over Gabor Wavelet adaptive dictionary by K-SVD algorithm. The results of this algorithm have more efficiency of image recovery than using DCT dictionary.

References
  1. Aharon, M. , Elad, M. ,and Bruckstein , A. ,2006 The K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representation. In IEEE Transactions on Signal Processing, vol. 54, no. 11, pp. 4311–4322.
  2. Breen, P. 2009 Algorithms for Sparse Approximation. year 4 project school of mathematics University of Edinburgh.
  3. Davis ,G. , Mallat, S. and Zhang, Z. 1994 Adaptive time-frequency decompositions , Opt. Eng. , vol. 33, no. 7, pp. 2183–91.
  4. Donoho, L. , Elad, M. and Temlyakov, V. 2006 Stable recovery of sparse overcomplete representations in the presence of noise. IEEE Transactions on Information Theory, 52(1):6–18.
  5. Lee. , T. S. 1996 Image representation using 2D Gabor wavelets. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(10):959–971.
  6. Mallat, S. and Zhang, Z. ,1993 Matching pursuits with time-frequency dictionaries," IEEE Trans. Signal Process. , vol. 41, no. 12, pp. 3397–3415.
  7. Pati, Y. C. , Rezaiifar, R. and Krishnaprasad, P. S. , 1993 Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition, in Conf. Rec. 27th Asilomar Conf. Signals, Syst. Comput. , 1993, vol. 1.
  8. Plumbley, M. D. , Blumensath, T. ,Daudet L. , Gribonval, R. , and Davies, M. , 2010 Sparse representations in audio and music: from coding to source separation, Proc. of the IEEE, vol. 98, no. 6.
  9. Shen, L. and Bai, L. , 2006 A review of Gabor wavelets for face recognition, Patt. Anal. Appl. : 273-292.
  10. Tropp, J. A. 2004 Greed is good: Algorithmic results for sparse approximation. IEEE Trans. Inf. Theory, vol. 50, pp. 2231–2242.
Index Terms

Computer Science
Information Sciences

Keywords

Sparse representation K-SVD Gabor wavelet dictionary and OMP