Abstract
Accurate motion estimation between frames is important for drastically reducing data redundancy in video coding. However, advanced motion estimation methods are computationally intensive and their execution in real time usually requires a parallel implementation. In this paper, we investigate the parallel implementation of such a motion estimation technique. Specifically, we present a parallel algorithm for motion estimation based on the bilinear transformation on the well-known parallel model of the hypercube network and formally prove the time and the space complexity of the proposed algorithm. We also show that the parallel algorithm can also run on other hypercubic networks, such as butterfly, cube-connected-cycles, shuffle-exchange or de Bruijn network with only constant slowdown.
Highlights
Motion estimation plays an important role in reducing the data redundancy typically existing between successive frames of a video and it is always included in any video compression scheme (Sayood 2012; Rao et al 2014; Chiariglione 2012)
We have presented a parallel algorithm for motion estimation for video coding based on the bilinear transformation
The algorithm runs on the the parallel model of the hypercube which has been widely used for parallel algorithm design in the literature
Summary
Motion estimation plays an important role in reducing the data redundancy typically existing between successive frames of a video and it is always included in any video compression scheme (Sayood 2012; Rao et al 2014; Chiariglione 2012). Inaccurate motion estimation increases the prediction error and more bits should be allocated for storing or transmitting this information. For this low-bit rate setting, simple block-matching motion estimation is not adequate due to its simplistic assumption about the motion of the objects in a video. The motion at all the pixels of each block is the same, more precisely, purely translational and it can be described by only one vector per block This assumption is not realistic and as a result, simple block-matching motion estimation algorithms fail to identify the actual movement in a video especially when there is complex object movement in the scene
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
