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

Optimal Threshold Selection for Wavelet Transform based on Visual Quality

by Baby Vijilin, V. K. Govindan
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 19
Year of Publication: 2013
Authors: Baby Vijilin, V. K. Govindan
10.5120/14272-2346

Baby Vijilin, V. K. Govindan . Optimal Threshold Selection for Wavelet Transform based on Visual Quality. International Journal of Computer Applications. 81, 19 ( November 2013), 25-28. DOI=10.5120/14272-2346

@article{ 10.5120/14272-2346,
author = { Baby Vijilin, V. K. Govindan },
title = { Optimal Threshold Selection for Wavelet Transform based on Visual Quality },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 19 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 25-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number19/14272-2346/ },
doi = { 10.5120/14272-2346 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:29.591323+05:30
%A Baby Vijilin
%A V. K. Govindan
%T Optimal Threshold Selection for Wavelet Transform based on Visual Quality
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 19
%P 25-28
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wavelet transform technique has been used for image compression targeting high visual quality reconstructed images even with high compression ratio. A visual quality measure such as Picture Quality Scale (PQS), which correlates well with the subjective Mean Opinion Score (MOS) may be employed on the compressed image for the quantizer to select the optimum dynamic threshold. The use of optimum threshold permits the removal of redundant information, thus leading to better compression performance with acceptable picture quality. The Results obtained with the proposed approach of threshold selection is compared with the existing technique and the performance and it is found to be better in all of the cases of images or wavelets.

References
  1. CUI Huimin, ZHAO Ruimei, HOU Yanli, Improved Threshold Denoising Method Based on Wavelet Transform, Elsevier, Physics Procedia 33 ( 2012 ) 1354 – 1359,2012.
  2. G. Andria,F. Attivissimo,G. Cavone,N. Giaquinto,A. M. L. Lanzolla Linear filtering of 2D wavelet coefficients for denoising ultrasound medical images Elsevier, SciVerse Science Direct, Measurement 45(2012)1792– 1800,2012.
  3. D. L. Donoho, De-Noising by Soft Threshold, IEEE Trans. Info. Theory 43,pp. 933-936, 1993.
  4. D. L. Donoho and I. M. Johnstone, Adapting to unknown smoothness via wavelet shrinkage, Journal of American Statistical Assoc. , Vol. 90, no. 432, pp. 1200-1224, Dec. 1995.
  5. S. Grace Chang, Bin Yu and M. Vattereli, Adaptive Wavelet Threshold for Image Denoising and Compression, IEEE Trans. for Multiple Noisy Image Copies, IEEE Trans. Image Processing, vol. 9, pp. 1631- 1635, Sept. 2000.
  6. S. Grace Chang, Bin Yu and M. Vattereli, Wavelet Threshold for Multiple Noisy Image Copies, IEEE Trans. Image Processing, vol. 9, pp. 1631- 1635, Sept. 2000.
  7. S. Grace Chang, Bin Yu and M. Vattereli, Spatially Adaptive Wavelet Threshold with Context Modeling for Image Denoising,, IEEE Trans. Image Processing, vol. 9, pp. 1522-1530, Sept. 2000.
  8. Daubechies, Ten Lectures on Wavelets, Vol. 61 of Proc. CBMS-NSF Regional Conference Series in Applied Mathematics. Philadelphia, PA: SIAM, 1992.
  9. Fei Xiaoa, Yungang Zhanga "A Comparative Study on Thresholding Methods in Waveletbased Image Denoising" Elsevier, Procedia Engineering 15 (2011) 3998 – 4003,2011.
  10. M. L. Hilton and R. T. Ogden Data Analytic Wavelet Threshold Selection in 2-D Signal Denoising" IEEE Transactions on signal processing, vol. 45, no. 2, february 1997.
  11. Weszka, J. S. ; Nagel, R. N. ; Rosenfeld, Threshold Selection Technique "Computers,IEEE Transactions on ,Volume C-23, Issue 12, Dec. 1974 Page(s):1322 - 1326
  12. Marc Antonini, Michel Barlaud, "Image Coding Using Wavelet Transform" IEEE Transactions on Image Processing, Vol. 1, No. 2, April 1992. pp. 205-220
  13. S. Mallat, "A theory for multiresolution signal decomposition: The wavelet representation", IEEE Transactions Pattern Analysis Machine Intelligence, Vol II pp. 674-693, 1989.
  14. Miyahara, M. ,Kotani, K. , Algazi, V. , "Objective picture quality scale (PQS) for image coding" IEEE Transactions on Communications, Vol. 46 , Issue: 9 ,Sep 1998, pp. 1215-1226.
  15. N. W. Lewis and J. A. Alnatt "Subjective quality of television pictures with multiple impairments" Electron, Lett. ,vol. ,1,pp. 187-188,July
  16. Method for the subjective assessment of the quality of television pictures,CCIR Rec. 500-2,1982.
  17. "Advanced methods for the evaluation of television picture quality" in proc. , Mosiac workshop, Eindhoven,The Netherlands, 1995.
  18. Makoto Miyahara, Kazunori Kotani, and V. Ralph Algazi. Objective picture quality Scale(PQS) for image coding IEEE Ttransactions on communications, vol. 46, no. 9, september 1998.
Index Terms

Computer Science
Information Sciences

Keywords

Image Compression Optimum Threshold Visual quality Wavelet Transform

Powered by PhDFocusTM