CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Review of HVS-based Image Compression Methods

by Hanadi Ahmed Hakami, Arwa Darwish Alzughaibi, Zenon Chaczko
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 6
Year of Publication: 2015
Authors: Hanadi Ahmed Hakami, Arwa Darwish Alzughaibi, Zenon Chaczko
10.5120/ijca2015907437

Hanadi Ahmed Hakami, Arwa Darwish Alzughaibi, Zenon Chaczko . Review of HVS-based Image Compression Methods. International Journal of Computer Applications. 131, 6 ( December 2015), 1-5. DOI=10.5120/ijca2015907437

@article{ 10.5120/ijca2015907437,
author = { Hanadi Ahmed Hakami, Arwa Darwish Alzughaibi, Zenon Chaczko },
title = { Review of HVS-based Image Compression Methods },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 6 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number6/23450-2015907437/ },
doi = { 10.5120/ijca2015907437 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:26:31.042156+05:30
%A Hanadi Ahmed Hakami
%A Arwa Darwish Alzughaibi
%A Zenon Chaczko
%T Review of HVS-based Image Compression Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 6
%P 1-5
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Digital images can be compressed by using data compression processes with the aim of lessening image data redundancy and save or send out an efficient form of data. This is not an easy task because large volumes of data comprise an original image, requiring huge memory allocation and inconvenient transmission. In this paper, the Human Visual System-based Image Compression is reviewed based on set criteria. Specifically, the characteristics, compression techniques and wavelet-based compression are discussed.

References
  1. Wang Aili, Zhang Ye, and G U Yanfeng. SAR Image Compression using HVS Model. pages 1–4, 2006.
  2. Pierre Mathieu Barlaud and Ingrid Daubechies Antonini Marc Michel. Image coding using the wavelet transform. In Image Processing, IEEE Transactions on 1, pages 205–220, 1992.
  3. I H¨ontsch and L J Karam. Locally adaptive perceptual image coding. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 9(9):1472–1483, 2000.
  4. F Koch, S A E Lewis, S V Chernikov, and J R Taylor. Broadband Raman gain characterisation in various optical fibres. Electron Lett, 37(24):1437–1439, 2001.
  5. S.P. Voukelatos and J.J. Soraghan. Very low bit-rate color video coding using adaptive subband vector quantization with dynamic bit allocation. IEEE Transactions on Circuits and Systems for Video Technology, 7(2):424–428, 1997.
  6. Fahmi Kammoun and Mohamed Salim Bouhlel. A Perceptual Image Coding method of High Compression Rate. International Journal of Computer, Information, Systems and Control Engineerin, 1(9):46–50, 2007.
  7. Andrew P. Bradley. A wavelet visible difference predictor. IEEE Transactions on Image Processing, 8(5):717–730, 1999.
  8. M J Nadenau, J Reichel, and M Kunt. Wavelet-based color image compression: Exploiting the contrast sensitivity function. IEEE Transactions on Image Processing, 12(1):58–70, 2003.
  9. Zherzghuu Yu. Perceptual Coding of Digital Images. Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP ’04. 2004., 11(2):1167–1172, 2004.
  10. B Y F W Campbell and J G Robson. Application of Fourier Analysis to the Visibility of Gratings. October, pages 551–566, 1968.
  11. John J Soraghan. with application to progressive image transmission. 13:135–143, 1998.
  12. James S. Walker. Wavelet based image compression. Transforms and Data Compression, 79, 2001.
  13. Brian A. Wandell. Foundations of Vision. 1995.
Index Terms

Computer Science
Information Sciences

Keywords

Image Compression HVS Characteristics Wavelet Based Image Compression

Powered by PhDFocusTM