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Research Article | Open Access |

Novel Intra-Prediction Framework for H.264 Video Compression using Decision and Prediction Mode

Author 1: Pradeep Kumar N.S. Author 2: H.N. Suresh
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 4 · Published 2017

DOI: https://doi.org/10.14569/IJACSA.2017.080409

Abstract

With the increasing usage of multimedia contents and advancement of the communication devices (along with services), there is a heavy demand of an effective multimedia compression protocol. In this regards, H.264 has been proven to be an effective video compression standard; however, its computational complexity associated with out and various other issues has been impediment towards mainstream of research towards compression. Therefore, we present a novel framework that enhances the capability of H.264 compression method by emphasizing on accomplishing the cost effectiveness of computational operation during intra-prediction mode. A simple and novel encoding mechanism has been formulated using H.264/AVC using decision mode of macro block as well as selection of prediction mode exclusively for intra-prediction in H.264/AVC. The study outcome is found to offer a superior signal quality as compared to conventional H.264 encoding mechanism.

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How to Cite this Article

N.S., P. K., & Suresh, H. (2017). Novel Intra-Prediction Framework for H.264 Video Compression using Decision and Prediction Mode. International Journal of Advanced Computer Science and Applications, 8(4). https://doi.org/10.14569/IJACSA.2017.080409

N.S., Pradeep Kumar, and H.N. Suresh. "Novel Intra-Prediction Framework for H.264 Video Compression using Decision and Prediction Mode." International Journal of Advanced Computer Science and Applications, vol. 8, no. 4, 2017, https://doi.org/10.14569/IJACSA.2017.080409.

@article{N.S.2017,
  title     = {Novel Intra-Prediction Framework for H.264 Video Compression using Decision and Prediction Mode},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {4},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Pradeep Kumar N.S. and H.N. Suresh},
  doi       = {10.14569/IJACSA.2017.080409},
  url       = {https://doi.org/10.14569/IJACSA.2017.080409}
}

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