An Efficient DWT and Tucker Decomposition with H.264 Video Compression for Multimedia Applications
N. Sardar Basha1, A. Rajesh2
1N.Sardar Basha, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram (Tamil Nadu), India.
2A.Rajesh, C Abdul Hakeem College of Engineering & Technology, Vellore (Tamil Nadu), India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 06 September 2019 | PP: 495-500 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F11010886S19/19©BEIESP | DOI: 10.35940/ijeat.F1101.0886S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In last thirty years, there has been so much of intensive research has been carried out on video compression techniques and now it has become mature and used in a large number of applications. In this paper, we are trying to present video compression using H.264 compression with Tucker decomposition. The largest Kn sub-tensors and their eigenvectors with run length encoding to compress the frames in the video was obtained by implementing tucker decomposition of tensor. DWT is used to separate each frames into sub-images and TD on DWT coefficient to compact the energy of sub-images. The obtained experimental results supported that our proposed method yields higher compression ratio with good PSNR.
Keywords: DWT, Tensors, Tucker Decomposition, H.264 and Multimedia Applications.
Scope of the Article: Ubiquitous Multimedia Computing