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Reseach Article

Web based Modified Video Decoding for Mobile Application

by Ronik Doshi, Poorva Waingankar, Sangeeta Joshi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 15
Year of Publication: 2015
Authors: Ronik Doshi, Poorva Waingankar, Sangeeta Joshi
10.5120/ijca2015906280

Ronik Doshi, Poorva Waingankar, Sangeeta Joshi . Web based Modified Video Decoding for Mobile Application. International Journal of Computer Applications. 126, 15 ( September 2015), 19-23. DOI=10.5120/ijca2015906280

@article{ 10.5120/ijca2015906280,
author = { Ronik Doshi, Poorva Waingankar, Sangeeta Joshi },
title = { Web based Modified Video Decoding for Mobile Application },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 15 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number15/22628-2015906280/ },
doi = { 10.5120/ijca2015906280 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:17:31.953083+05:30
%A Ronik Doshi
%A Poorva Waingankar
%A Sangeeta Joshi
%T Web based Modified Video Decoding for Mobile Application
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 15
%P 19-23
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Videos are the most useful and only approach to represent audiovisual information. Today all the communication approaches are working with such kind of media. The problem with such kind of media is its large size. Data is required to be stored in the database or to be transferred over communication medium. Size of video always affects the efficiency. Video compression is required to save the storage space as well as time for transmission & reception. By using effective compression techniques video size is reduced thereby reduction in cost of data usage for mobile applications.

References
  1. Xin Jin, “Content Similarity Based Earl Skip Mode Decision for Low Power Surveillance video compression”, Proceedings of the 4th International Symposium on communication, Control and Signal Processing, pp.1-4, SCCSP 2010.
  2. M. Abdoli, “the Impact of View Spacing in Multi-view Video Compression Efficiency”, 2010 Seventh International Conference on Information Technology.pp.1314-1315, 2010.
  3. Jelte Peter Vink, “No-Reference Metric Design with Machine Learning for Local Video Compression Artifact Level”, IEEE Journal of Selected Topics in Signal Processing.Vol.5, Issue-2, pp.1932-4553, 2010.
  4. Nam Ling, “Expectations and Challenges for Next Generation Video Compression”, pp.2339-2344, 2010 IEEE.
  5. G.Suresh,“A Low Complex Scalable Spatial Adjacency ACC-DCT Based Video Compr -ession Method”, 2010Second International conference on Computing, Communication and Networking Technologiespp.4244,
  6. Yu-Cheng Fan, “Three-Dimensional Depth Map Motion Estimation and Compensation for 3D Video Compression”, Vol-47, Issue-3, pp.691-695, 2011.
  7. Jelte Peter Vink, “Local Estimation of Video Compression Artifacts”, International Conf-erence on Consumer Electronics (ICCE), pp.247-248, 2011.
  8. Fernando Pereira,“video compres-sion: an Evolving Technology for Better User Experiences”.2011.
  9. ZHU Xiao-dong, “Research on Scalable Coding Technology Application in Video Compression Based on H.264 Standard”, pp.5052-5055, 2011.
  10. Suman Deb Roy, “A Multi- Layer Key Stream Based Approach for Joint Encry -ption and Compression of H.264 Video”, pp.1-6, 2011.
  11. MPEG-4 Multimedia for our Time”R. Koenen, IEEE Spectrum, Feb. 1999, pp. 26-33
  12. Xiao-lin Chen, “Design of UAV Vide Compression System Based on H.264 Encoding Algorithm”, International Conference on Electronic & Mechanical Engineering and Information T echnolo-gy.Vol-5, pp.2619-2622, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

DCT DWT PSNR