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DOI: 10.14569/IJACSA.2016.071229
PDF

Low Complexity for Scalable Video Coding Extension of H.264 based on the Complexity of Video

Author 1: Mayada Khairy
Author 2: Amr Elsayed
Author 3: Alaa Hamdy
Author 4: Hesham Farouk Ali

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 12, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Scalable Video Coding (SVC) / H.264 is one type of video compression techniques. Which provided more reality in dealing with video compression to provide an efficient video coding based on H.264/AVC. This ensures higher performance through high compression ratio. SVC/H.264 is a complexity technique whereas the takes considerable time for computation the best mode of macroblock and motion estimation through using the exhaustive search techniques. This work reducing the processing time through matching between the complexity of the video and the method of selection macroblock and motion estimation. The goal of this approach is reducing the encoding time and improving the quality of video stream the efficiency of the proposed approach makes it suitable for are many applications as video conference application and security application.

Keywords: Scalable video coding; motion estimation; SVC layers; quality scalability

Mayada Khairy, Amr Elsayed, Alaa Hamdy and Hesham Farouk Ali, “Low Complexity for Scalable Video Coding Extension of H.264 based on the Complexity of Video” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071229

@article{Khairy2016,
title = {Low Complexity for Scalable Video Coding Extension of H.264 based on the Complexity of Video},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071229},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071229},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Mayada Khairy and Amr Elsayed and Alaa Hamdy and Hesham Farouk Ali}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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