Comparative analysis of video compression mechanisms using 3D-DWT based video encoding along with EZW Online publication date: Mon, 10-Jul-2017
by V.R. Satpute; K.D. Kulat; A.G. Keskar
International Journal of Computational Vision and Robotics (IJCVR), Vol. 7, No. 4, 2017
Abstract: In this paper, two compression mechanisms based on 3D-discrete wavelet transform (DWT) and 2D embedded zero wavelet (EZW) are proposed and compared depending on the mathematical parameters, i.e., peak signal-to-noise ratio (PSNR) and compression ratio (CR). In this paper, we are using Haar wavelet decomposition for compression, as it has shown improved compression in recent years when used along with the techniques like EZW, SPIHT, etc. Haar wavelet is chosen because of its ease implementation and has inherent properties and EZW is chosen for compression. We apply EZW with frame-by-frame basis on the encoded video as EZW is meant for 2D-data only. Here we are adding the extra blocks for video encoding and decoding before and after the existing compression technique, i.e., EZW. So, these mechanisms are very easy to implement by just adding the extra blocks of encoding and decoding.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Vision and Robotics (IJCVR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook