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 Enhancement based on Nonsubsampled Contourlet Transform using Matrix Factorization Techniques

by K. Hepsibah Persis, M.S. Heaven Dani, M. Saravanan
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 6
Year of Publication: 2015
Authors: K. Hepsibah Persis, M.S. Heaven Dani, M. Saravanan
10.5120/ijca2015905372

K. Hepsibah Persis, M.S. Heaven Dani, M. Saravanan . Image Enhancement based on Nonsubsampled Contourlet Transform using Matrix Factorization Techniques. International Journal of Computer Applications. 123, 6 ( August 2015), 35-38. DOI=10.5120/ijca2015905372

@article{ 10.5120/ijca2015905372,
author = { K. Hepsibah Persis, M.S. Heaven Dani, M. Saravanan },
title = { Image Enhancement based on Nonsubsampled Contourlet Transform using Matrix Factorization Techniques },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 6 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 35-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number6/21966-2015905372/ },
doi = { 10.5120/ijca2015905372 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:11:58.526013+05:30
%A K. Hepsibah Persis
%A M.S. Heaven Dani
%A M. Saravanan
%T Image Enhancement based on Nonsubsampled Contourlet Transform using Matrix Factorization Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 6
%P 35-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A unique method for image enhancement using the nonsubsampled Contourlet transform (NSCT) is presented here. Existing methods for image enhancement cannot capture the geometric information of images and tend to amplify noises when they are applied to noisy images since they cannot distinguish noises from weak edges. In contrast, the nonsubsampled Contourlet transform extracts the geometric information of images, which can be used to distinguish noises from weak edges. In this paper, we take the low pass subband of the \image obtained after nonsubsampled Contourlet decomposition. QR decomposition is applied on the lowest frequency subband. SVD decomposition technique is applied on the QR decomposed coefficients to obtain singular values. Therefore, changing the singular values will directly affect the illumination of the image; hence, the other information in the image will not be changed. Experimental results show the pro-posed method achieves better enhancement results than a wavelet-based image enhancement method.

References
  1. A. Laine, J. Fan, and W. Yang, “Wavelets for contrast enhancement of digital mammography,” IEEE Engineering in Medicine and Biology, pp. 536–550, September 1995.
  2. M. N. Do and M. Vetterli, “The contourlet transform: An effi-cient directional multiresolution image representation,” IEEE Trans. Image Proc., 2005, to appear.
  3. Duncan D. Po and Minh N. Do, “Directional multiscale mod-eling of images using the contourlet transform,” IEEE Trans. Image Proc., 2005, to appear.
  4. E. P. Simoncelli, W. T. Freeman, E. H. Adelson, and D. J. Heeger, “Shiftable multiscale transforms,” IEEE Trans. In-form. Th., vol. 38, no. 2, pp. 587–607, March 1992.
  5. K. V. Velde, “Multi-scale color image enhancement,” Proc. IEEE Int. Conf. on Image Proc., vol. 3, pp. 584–587, 1999.
  6. J. K. Paik, and B. S. Kang, “Contrast enhancement system using spatially adaptive histogram equalization with temporal Filtering “ IEEE Trans. Consum. Electron., vol. 44, no. 1, pp. 82Ð87, Feb 1998
  7. A. L. Cunha, J. Zhou, and M. N. Do, “The nonsubsampled contourlet transform: theory, design and applications,” IEEE Trans. Image Proc., submitted, 2005.
  8. G. Anbarjafari, and M. N. S. Jahromi, “Image equalization based on singular value decomposition” in Proc. 23rd IEEE Int. Symp. Comput. Inf. Sci., Istanbul, Turkey, Oct 2008
  9. S.Shanmugan and A. M. Breipohl, Random Signals: Detection, Estimation and Data Analysis. Hoboken, NJ: Wiley, 1998
Index Terms

Computer Science
Information Sciences

Keywords

Discrete Wavelet Transform Non Subsampled Contourlet Transform Singular Value Decomposition QR Decomposition Image Equalization.

Powered by PhDFocusTM