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Analysis of Block Matching Algorithms for Motion Estimation in Video Data

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Machine Learning and Information Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1311))

Abstract

Demand for video data is increasing exponentially, and to cope with the growing demand of video data, various block matching techniques are designed. Video compression has been in the demand among research community. Various methods have been studied for video compression but block matching algorithms are very popular and have been very useful for video compression. This article is to review various block matching motion estimation techniques for video compression. This paper evaluates the performance of different block matching motion estimation algorithms using MAD in terms of PSNR and execution time. These block matching algorithms use different search patterns and are different from one another in search pattern and approach, and hence these algorithms have different number of points to search matching blocks. Motion estimation of blocks and objects has been very important and significant in any of the video standard. All standards for storage and compression of the video, as per the international standards, are using one of the block matching algorithms for the reduction of temporal redundancy. All the video standards from H.261 to H.264-Advanced video coding or latest H.265-High efficiency video coding are based on motion estimation techniques to reduce temporal redundancy.

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Authors and Affiliations

  1. Hartcourt Butler Technical University, Kanpur, India

    Awanish Kumar Mishra & Narendra Kohli

Authors
  1. Awanish Kumar Mishra
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  2. Narendra Kohli
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Corresponding author

Correspondence to Awanish Kumar Mishra .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Debabala Swain

  2. School of Computer Engineering, Kalinga Institute of Industrial Technology Deemed University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

  3. Oak Ridge National Laboratory, Tennessee, TN, USA

    Tushar Athawale

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Mishra, A.K., Kohli, N. (2021). Analysis of Block Matching Algorithms for Motion Estimation in Video Data. In: Swain, D., Pattnaik, P.K., Athawale, T. (eds) Machine Learning and Information Processing. Advances in Intelligent Systems and Computing, vol 1311. Springer, Singapore. https://doi.org/10.1007/978-981-33-4859-2_32

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