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

Image Compression via Modified TiBS Algorithm to Achieve High Compression Rate

by Pravin B. Pokle, Narendra G. Bawane
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 78 - Number 13
Year of Publication: 2013
Authors: Pravin B. Pokle, Narendra G. Bawane
10.5120/13585-1346

Pravin B. Pokle, Narendra G. Bawane . Image Compression via Modified TiBS Algorithm to Achieve High Compression Rate. International Journal of Computer Applications. 78, 13 ( September 2013), 32-37. DOI=10.5120/13585-1346

@article{ 10.5120/13585-1346,
author = { Pravin B. Pokle, Narendra G. Bawane },
title = { Image Compression via Modified TiBS Algorithm to Achieve High Compression Rate },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 78 },
number = { 13 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume78/number13/13585-1346/ },
doi = { 10.5120/13585-1346 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:30.351616+05:30
%A Pravin B. Pokle
%A Narendra G. Bawane
%T Image Compression via Modified TiBS Algorithm to Achieve High Compression Rate
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 13
%P 32-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent times the integration of video, audio and data in telecommunication devices has revolutionized communication world. It has proven to be useful to almost every industry: the corporate world, entertainment industry, multimedia, education and even at home. The major problems associated with these applications are the high data rates, high bandwidth and large memory required for storage and computing resources. Even with faster internet speed, throughput rates and advanced network infrastructure, there are major bottlenecks to transfer such high volume data through the network due to bandwidth limitations. There is a need to develop compression techniques in order to make the best use of available bandwidth. Thus storage and compression of these high resolution images plays a vital role in such applications to conserve the energy and processor's computational resources. This paper presents a lightweight modified TiBS algorithm for image compression and storage. The proposed modified compression method operates on a 3x3 block and is based on pixel removal technique. The results shows that proposed method provides a maximum compression of 33% which is more than that achievable by standard TiBS algorithm.

References
  1. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, "Wireless Sensor Networks: A Survey", Computer Networks 38(4)(2002) 393–422.
  2. Ferrigno L, Marano S, Paciello V, Pietrosanto A. Pietrosanto. Balancing computational and transmission power consumption in wireless image sensor networks. International Conference on Virtual Environments, Human- Computer Interfaces, and Measures Systems. Italy. 2005: 61–66
  3. Shantanu D. Rane and Guillermo Sapiro, Member, IEEE,"Evaluation of JPEG-LS, the New Lossless and Controlled-Lossy Still Image Compression Standard, for Compression of High-Resolution Elevation Data", IEEE Transactions on Geoscience and Remote sensing, VOL. 39, NO. 10, Oct. 2001
  4. Med Lassaad KADDACHI, Adel SOUDANI, Ibtihel NOUlRA, Vincent LECUlRE and Kholdoun TORKI "Efficient hardware solution for low power and adaptive image-compression in WSN", 978-1-4244-8157-6110, ICECS 2010, IEEE. Zhang, Y. Z. , Xu, C. , Wang, W. T. , & Chen, L. B. Performance Analysis and architecture design for EBCOT encoder in JPEG2000. IEEE Transactions on Circuits and Systems for Video Technology, 17(10), 1336–1347. -2007.
  5. C. Duran-Faundez, V. Lecuire, "Error resilient image communication with chaotic pixel interleaving for wireless camera sensors", Workshop on Real-World Wireless Sensor Networks (REALWSN 2008), ACM, Glasgow, Scotland (2008), pp. 21–25.
  6. Cristian Duran-Faundez, Vincent Lecuire, Francis Lepage, "Tiny block-size coding for energy-efficient image compression and communication in wireless camera sensor networks", Signal Processing: Image Communication 26 (2011) 466–481. 2011 Elsevier
  7. Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE Transactions on Image Processing, Vol. 13, no. 4, 2004.
  8. B. Goossens, A. Pizurica, and W. Philips, "Removal of correlated noise by modeling the signal of interest in the wavelet domain," IEEE Trans. Image Process. , vol. 18, no. 6, pp. 1153–1165, Jun. 2009.
  9. R. C. Gonzalez and R. E. Woods, "Digital Image Processing", 2nd Ed. , Prentice Hall, 2004.
  10. Wallace, G. K. "The JPEG Still Picture Compression Standard", Comm. ACM, vol. 34, no. 4, April 1991, pp. 30- 44.
  11. Grzegorz, P. (2005). Ahigh-performance architecture for embeddedblock coding in JPEG 2000. IEEE Transactions on Circuits and Systems for Video Technology, 15(9), 1182–1191.
Index Terms

Computer Science
Information Sciences

Keywords

Image compression DWT DCT TiBS (tiny block-size encoding) Huffman RLE.

Powered by PhDFocusTM