Ramesh K, Chandrika V. S, Praveena P, Pazhanimuthu C and Ravindran S, Department of EEE, Jayam College of Engineering and Technology, India
Online First : 30 December 2020
Publisher Name : IJAICT India Publications, India.
Print ISBN : 978-81-950008-0-7
Online ISBN : 978-81-950008-1-4
Page :237-245
Abstract
This paper presents the research on video compression for videos by developing a multi rate wavelet lifting scheme method which works better for both colour and grayscale videos along with Enhanced Adaptive Rood Search with Integral Projections for motion Estimation. In wavelet lifting scheme sampling is performed at different rates at the upper and lower branches. It is a powerful alternative to traditional convolution involving forward and inverse filter banks with the total amount of arithmetic computations required is substantially lesser. The ratio used is 3:2 for the upper branch and 3:1 for lower branch of lifting scheme, more low frequency coefficients are preserved as compared to high frequency coefficients to have a better picture quality with a small compromise in compression ratio. The Listless speck has been used as the Encoder and an Enhanced Adaptive Rood Search technique has been developed for motion Estimation as it improved over the problem with Adaptive Rood Search which does not consider the diagonal direction. The proposed method has produced better compression results with quality and reduced latency than the existing ones as validated in the experimentation.
Keywords
Enhanced Adaptive Roodsearch, Listless speck Multirate, Sub-bands, wavelet lifting scheme.
Cite this article
Ramesh K, Chandrika V. S, Praveena P, Pazhanimuthu C and Ravindran S, “Multi-rate Sampling Wavelet Lifting Scheme Based Video Compression with Enhanced Adaptive Rood Search Integral Projections”, Innovations in Information and Communication Technology, pp. 237-245, December 2020.
Copyright
© 2020 Ramesh K, Chandrika V. S, Praveena P, Pazhanimuthu C and Ravindran S. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
