Bijayinee Biswal

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



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


Biswal B. was born in Keonjhar, Orissa, India on November 10th 1985. Biswal is now working as lecturer in the Department of Electronics and Telecommunication, Ajay Binay Institute of Technology, Cuttack. She received her B. Tech degree in Electronics &Telecommunication Engineering in 2007 from ABIT, M. Tech in Electronics and Communication Engineering from IIT, Kharagpur, India in 2013. She has 6 years of experience in teaching and research in the field of Electronics & Communication engineering. Her research interest includes communication, signal and image processing. She is a member of Orissa Information Technology Society and ISTE, India

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

By Avinash Nayak Bijayinee Biswal S. K. Sabut

DOI:, 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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