CFP last date
20 May 2024
Reseach Article

A Novel Approach towards Video Compression for Mobile Internet using Transform Domain Technique

by Dhaval R. Bhojani, Ved Vyas Dwivedi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 10
Year of Publication: 2012
Authors: Dhaval R. Bhojani, Ved Vyas Dwivedi
10.5120/9320-3552

Dhaval R. Bhojani, Ved Vyas Dwivedi . A Novel Approach towards Video Compression for Mobile Internet using Transform Domain Technique. International Journal of Computer Applications. 58, 10 ( November 2012), 29-33. DOI=10.5120/9320-3552

@article{ 10.5120/9320-3552,
author = { Dhaval R. Bhojani, Ved Vyas Dwivedi },
title = { A Novel Approach towards Video Compression for Mobile Internet using Transform Domain Technique },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 10 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number10/9320-3552/ },
doi = { 10.5120/9320-3552 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:02:07.240191+05:30
%A Dhaval R. Bhojani
%A Ved Vyas Dwivedi
%T A Novel Approach towards Video Compression for Mobile Internet using Transform Domain Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 10
%P 29-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As the era, in the internet applications, is of mobile internet, the use of the internet on the cell-phone networks and other mobile networks is increased so much. Also the data rates available on any mobile networks are limited so that the multimedia file transfers on the mobile networks require more time and cost. To reduce the data rates required to transfer multimedia files on the mobile networks, we require one compression algorithm which gives us higher compression with easiness of implementation. So here the paper present one algorithm which is much simpler to implement, as it is based on MPEG-2 then also gives compression in considerable amount, which is comparable to MPEG-4 techniques. The algorithm is implemented on MATLAB version 7. 10. 0. 499a platform. The input to the encoder is in uncompressed '. avi' format. The testing of the compressed videos is done using MSU video quality measurement tool.

References
  1. 'MPEG Digital Video-Coding Standards', IEEE Signal Processing Magazine, September, 1997, pp. 82-100.
  2. White Paper of Axis Communication, 'H. 264 video compression standard', 2008.
  3. White Paper of Axis Communication, 'An explanation of video compression techniques', 2008.
  4. White Paper of Array Microsystems Inc. , Video compression-An Introduction', 1997.
  5. Ian Gilmour and R. Justin Davila, 'Lossless video compression for Archives: Motion JPEG2K and other options', Media Matters IIC.
  6. P. N. Tudor, 'MPEG-2 Video Compression', Electronics & Communication Engineering Journal, 1995, Paper No. 14.
  7. Aroh Barjatya, 'Block matching algorithms for Motion estimation', DIP 6620 Spring 2004 Final Project Paper
  8. MSU-Video Quality Measurement Tool 3. 0, www. compression. ru
  9. PicTools Jpeg 2000, www. jpg. com/jpeg2000
  10. MPEG-2 Description, www. mpeg. chiariglione. org/standards/mpeg-2
  11. John G. Apostolopoulos, 'Video Compression', MIT 6. 344, Springer 2004.
  12. Zhou Wang, Eero P. Simoncelli and Alan C. Bovik, 'Multi-scale structural similarity for image quality assessment', Proceeding of 37th IEEE Asilomar conferece on signals, systems and computers, 2003.
  13. Chaofeng Li and Alan Conrad Bovik, 'Content-weighted video quality assessment using a three-component image model', Journal of Electronic Imaging, 19(1), 011003, Jan-Mar 2010.
  14. Feng Xiao, 'DCT-based video quality evaluation', Final Project for EE392J, Winter 2000.
  15. Zhou Wang, Hamid Rahim Sheikh, Eero P. Simoncelli and Alan C. Bovik, 'Image quality assessment: From error visibility to structural similarity', IEEE Transactions on Image processing, Vol. 13, No. 4, April 2004.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Rood Pattern Search (ARPS) Discrete Cosine Transform (DCT) Discrete Wavelet Transform (DWT) Group of Pictures (GOP) Run Length Encoding (RLE)