Open AccessAn Efficient DWT and Tucker Decomposition with H.264 Video Compression for Multimedia Applications
Author(s) -
N. Sardar Basha,
C. Saraswathi,
A. Rajesh,
Abdul Hakeem
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1101.0886s19
Subject(s) - tucker decomposition , compression (physics) , data compression , computer science , decomposition , video compression picture types , compression ratio , computer vision , uncompressed video , encoding (memory) , image compression , artificial intelligence , computer graphics (images) , tensor (intrinsic definition) , mathematics , tensor decomposition , video processing , image (mathematics) , image processing , video tracking , engineering , materials science , geometry , ecology , automotive engineering , composite material , biology , internal combustion engine
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.