CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Image Denoising based on MAP Estimation using Dual Tree Complex Wavelet Transform

by M Ramanjaneya Rao, P Ramakrishna
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 110 - Number 4
Year of Publication: 2015
Authors: M Ramanjaneya Rao, P Ramakrishna
10.5120/19306-0755

M Ramanjaneya Rao, P Ramakrishna . Image Denoising based on MAP Estimation using Dual Tree Complex Wavelet Transform. International Journal of Computer Applications. 110, 4 ( January 2015), 19-24. DOI=10.5120/19306-0755

@article{ 10.5120/19306-0755,
author = { M Ramanjaneya Rao, P Ramakrishna },
title = { Image Denoising based on MAP Estimation using Dual Tree Complex Wavelet Transform },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 110 },
number = { 4 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume110/number4/19306-0755/ },
doi = { 10.5120/19306-0755 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:45:30.957570+05:30
%A M Ramanjaneya Rao
%A P Ramakrishna
%T Image Denoising based on MAP Estimation using Dual Tree Complex Wavelet Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 110
%N 4
%P 19-24
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wavelet shrinkage is a standard technique for image denoising. Using the good directionality and shift invariance properties of dual tree complex wavelet transform, a new algorithm for image denoisinig is proposed. In this algorithm, the decomposed coefficients combined with the bivariate shrinkage model for the estimation of coefficients in high frequency sub bands and Bayesian shrinkage method is applied in order to remove the noise in highest frequency sub-band coefficients. The experimental results are compared with the existing shrinkage methods Visu and Bayes shrinkage methods in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).

References
  1. Survey of Image Denoising Techniques by Mukesh C. Motwani, Mukesh C. Gadiya, Rakhi C. Motwani, Frederick C. Harris, Jr.
  2. Massimo Fierro, Ho-Gun Ha, and Yeong-Ho Ha, "Noise Reduction Based on Partial Reference, Dual-Tree Complex Wavelet Transform Shrinkage", IEEE Transactions on Image Processing, vol. 22, no. 5, pp. 1859-1872, 2013.
  3. W. Selesnick, R. G. Baraniuk, and N. G. Kingsbury, ?The dual-tree complex wavelet transform—A coherent framework for multiscale signal and image processing, ? IEEE Signal Processing. Mag. , vol. 22, no. 6, pp. 123–151, Nov. 2005.
  4. Mr. R. K. Sarawale, Dr. Mrs. S. R. Chougule, " Image denoising using dual-tree complex dwt and double-density dual-tree complex dwt", International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, Issue 6, June 2013.
  5. Rajesh Kumar Rai , Jyoti Asnani and T. R. Sontakke , "Review of Shrinkage Techniques for Image Denoising", International Journal of Computer Applications (0975 – 8887) Volume 42– No. 19, March 2012.
  6. Sachin D Ruikar and Dharmpal D Doye, "Wavelet Based Image Denoising Technique", International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 2, No. 3, March 2011. Levent S¸endur, and Ivan W. Selesnick, "Bivariate Shrinkage Functions for Wavelet-Based Denoising Exploiting Interscale Dependency", IEEE Transactions On Signal Processing, Vol. 50, No. 11, pp. 2744-2756, November 2002.
  7. Levent S¸endur, and Ivan W. Selesnick, "Bivariate Shrinkage Functions for Wavelet-Based Denoising Exploiting Interscale Dependency", IEEE Transactions On Signal Processing, Vol. 50, No. 11, pp. 2744-2756, November 2002.
  8. Complex wavelet transforms and their applications, M. Phill thesis by Panchamkumar D Shukla.
  9. Yusra A. Y. Al-Najjar, Dr. Der Chen Soong, "Comparison of Image Quality Assessment: PSNR, HVS, SSIM, UIQI", International Journal of Scientific & Engineering Research, Volume 3, Issue 8, August-2012.
  10. B. Chinnarao, M. Madhavilatha , "Improved Image De noising Algorithm using Dual Tree Complex Wavelet Transform", International Journal of Computer Applications (0975 – 8887) Volume 44– No20, April 2012 .
  11. Devanand Bhonsle, Sandeepa Dewangan, "Comparative Study of dual-tree complex wavelet transform and double density complex wavelet transform for Image Denoising Using Wavelet-Domain" International Journal of Scientific and Research Publications, vol. 2, Issue 7, pp. 1-5,July 2012.
  12. Image denoising using dual tree statistical models for complex wavelet transform coefficient magnitudes by P. R. Hill, A. Achin, D. R. Bull and M. E. Al-Mualla.
  13. Mrs. Ritu Chouhan, Prof. Vikas Gupta, Arpita Rani Vaishnava, " Wavelet Based Color Image Denoising through a Bivariate Pearson Distribution" , International Journal on Recent and Innovation Trends in Computing and Communication ISSN 2321 – 8169 Volume: 1 Issue: 4 , April 2013.
  14. Rudra Pratap Singh Chauhan, Sanjay Singh and Sanjeev Kumar Shah, "A Practical Approach of Complex Dual Tree DWT for Image Quality Improvement and De-noising", International Journal of Modern Engineering Research (IJMER) Vol. 1, Issue. 2, pp-632-636.
Index Terms

Computer Science
Information Sciences

Keywords

Dual Tree Complex wavelet transform (DTCWT) Bivariate shrinkage Bayes shrinkage Peak signal to noise ratio (PSNR) Structural similarity index (SSIM)

Powered by PhDFocusTM