Avinash Nayak

Work place: Ajay Binay Institute of Technology, Odisha, India

E-mail: nayak.av@gmail.com


Research Interests: Image Processing, Image Compression, Computer systems and computational processes


Nayak A. was born in Cuttack, Orissa, India on June 20th 1981. Nayak is now working as lecturer in the Department of Electronics and Telecommunication, Ajay Binay Institute of Technology, Cuttack. He received his B.E. degree in Electronics & TeleCommunication in 2003 from CVRCE, M. Tech in Electronics & TeleCommunication from KIIT University, India in 2012. He has over 8 years of experience in teaching and research in Electronics & Communication engineering. His research interest includes signal and image processing. He is a member of ISTE(INDIA).

Author Articles
Evaluation and Comparison of Motion Estimation Algorithms for Video Compression

By Avinash Nayak Bijayinee Biswal S. K. Sabut

DOI: https://doi.org/10.5815/ijigsp.2013.10.02, Pub. Date: 8 Aug. 2013

Video compression has become an essential component of broadcast and entertainment media. Motion Estimation and compensation techniques, which can eliminate temporal redundancy between adjacent frames effectively, have been widely applied to popular video compression coding standards such as MPEG-2, MPEG-4. Traditional fast block matching algorithms are easily trapped into the local minima resulting in degradation on video quality to some extent after decoding. In this paper various computing techniques are evaluated in video compression for achieving global optimal solution for motion estimation. Zero motion prejudgment is implemented for finding static macro blocks (MB) which do not need to perform remaining search thus reduces the computational cost. Adaptive Rood Pattern Search (ARPS) motion estimation algorithm is also adapted to reduce the motion vector overhead in frame prediction. The simulation results showed that the ARPS algorithm is very effective in reducing the computations overhead and achieves very good Peak Signal to Noise Ratio (PSNR) values. This method significantly reduces the computational complexity involved in the frame prediction and also least prediction error in all video sequences. Thus ARPS technique is more efficient than the conventional searching algorithms in video compression.

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