We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model

by Ghadah Al-khafaji, Haider Al-mahmood
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 76 - Number 3
Year of Publication: 2013
Authors: Ghadah Al-khafaji, Haider Al-mahmood
10.5120/13230-0659

Ghadah Al-khafaji, Haider Al-mahmood . Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model. International Journal of Computer Applications. 76, 3 ( August 2013), 38-42. DOI=10.5120/13230-0659

@article{ 10.5120/13230-0659,
author = { Ghadah Al-khafaji, Haider Al-mahmood },
title = { Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 76 },
number = { 3 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 38-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume76/number3/13230-0659/ },
doi = { 10.5120/13230-0659 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:44:58.129916+05:30
%A Ghadah Al-khafaji
%A Haider Al-mahmood
%T Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 76
%N 3
%P 38-42
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

References
  1. Bramble, J. M. , Huang, H. K. and Murphy, M. D. 1988. Image Data Compression. Radiology, 23, 707-712.
  2. Wong, S. , Zaremba, L. , Gooden D. and Huang, H. K. 1995. Radiologic Image Compression – A Review. Proceedings of the IEEE, 83(2), 194-218.
  3. Shukla, J. , Alwani, M. and Tiwari, A. K. 2010. A Survey on Lossless Image Compression Methods. International Conference on Computer Engineering and Technology (ICCET), 136-141.
  4. Bhavani, S. and Thanushkodi, K. 2010. A Survey on Coding Algorithms in Medical Image Compression. International Journal on Computer Science and Engineering (IJCSE), 2(5), 1429-1434.
  5. Ferni Ukrit, M. , Umamageswari, A. and Suresh, G. R. 2011. A Survey on Lossless Compression for Medical Images. International Journal of Computer Applications (IJCA), 31(8), 47-50.
  6. Alagendran, B. and Manimurugan, S. 2012. A Survey on Various Medical Image Compression Techniques. International Journal of Soft Computing and Engineering (IJSCE), 2(1), 425-428.
  7. Venkatraman, B. , Vaithiyanathan, V. and Karthikeyan, B. 2013. Review on Lossless Image Compression Techniques for Welding Radiographic Images. Research Journal of Applied Sciences, Engineering and Technology 5(1), 167-170.
  8. Burt, P. J. and Adelson, E. H. 1983. The Laplacian Pyramid as a Compact Image Code. IEEE Transactions on Communications, 31(4), 532-540.
  9. Bramble, J. M. 1989. Comparison of Information Preserving and Information-Losing Data-Compression Algorithms for CT Images. Radiology, 170, 543-455.
  10. Heer, V. K. and Reinfelder, H. E. 1990. A Comparison of Reversible Methods for Data Compression. SPIE Medical Imaging, 1233, 254-365.
  11. Viergever, M. A. and Roos, P. 1993. Hierarchical Interpolation. IEEE Engineering in Medicine and Biology Magazine, 12(1), 48- 55.
  12. Antonini M. , Barlaud M. , Mathieu P. and Daubechies I. 1992. Image Coding using Wavelet Transform. IEEE Trans. on Image Processing, 1(2), 205–220.
  13. Sadashivappa, G. and Ananda Babu, K. , 2008. Performance Analysis of Image Coding Using Wavelets. International Journal of Computer Science and Network Security, 8(10), 144-151.
  14. Grigorios D. , Zervas N. , Sklavos N. and Costas E. 2008. Design Techniques and Implementation of Low Power High-Throughput Discrete Wavelet Transform Tilters for JPEG 2000 Standard. WASET , International Journal of Signal Processing 4(1), 36-43.
  15. Das, M. and Burgett, S. 1993. Lossless Compression of Medical Images Using Two Dimensional Multiplicative Autoregressive Models. IEEE Transactions on Medical Imaging, 12(4), 721-726.
  16. George, L. E. and Sultan, B. 2011. Image Compression Based on Wavelet, Polynomial and Quadtree. Journal of Applied Computer Science & Mathematics, 11(5), 15-20.
  17. Ghadah, Al-K. and George, L. E. . 2013. Fast Lossless Compression of Medical Images based on Polynomial. International Journal of Computer Applications, 70(15),28-32.
Index Terms

Computer Science
Information Sciences

Keywords

Medical images lossless image compression multiresolution coding and polynomial representation

Powered by PhDFocusTM