Interframe Prediction Based Stationary Block Revalidation VBSME Using Full Search and Vector-driven Techniques

Authors

  • M. Vinutha Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), Department of Electronics Engineering (VLSI Design & Technology), Nitte, Karkala, Udupi, Karnataka 574110, India, Visvesvaraya Technological University, Belagavi, Karnataka 590018, India
  • T. M. Manu Department of Electronics and Communication Engineering, KLE Institute of Technology (KLEIT), Hubballi, Karnataka 580027, India, Visvesvaraya Technological University, Belagavi, Karnataka 590018, India

DOI:

https://doi.org/10.13052/jmm1550-4646.2168

Keywords:

Motion estimation, VBSME, hardware-friendly search, real-time compression

Abstract

Full search (FS) motion estimation provides high accuracy but at high computational cost, while fast search methods introduce irregular, hardware-unfriendly patterns. This work proposes four adaptive FS-based VBSME algorithms that preserve FS regularity while reducing complexity through direction-driven search, adaptive block sizes, stationary block revalidation (SBR), and early termination using a spiral pattern.On CIF sequences, vector-driven VBSME with early termination reduces SAD computations by 53.9–-94.5%, while SBR improves PSNR by up to 1.39 dB. For 1080p video, SBR-based FS VBSME achieves higher PSNR than conventional FSBME, while SBR-based vector-driven VBSME delivers nearly 60% fewer SAD evaluations.

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Author Biographies

M. Vinutha, Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), Department of Electronics Engineering (VLSI Design & Technology), Nitte, Karkala, Udupi, Karnataka 574110, India, Visvesvaraya Technological University, Belagavi, Karnataka 590018, India

M. Vinutha received her bachelor’s degree in Electronics and Communication Engineering from Visvesvaraya Technological University, Karnataka, India, in 2012. She obtained her M.Tech. degree in Digital Electronics and Communication Systems from Visvesvaraya Technological University in 2014. She is currently pursuing her Ph.D. under Visvesvaraya Technological University, Belagavi, with KLE Institute of Technology (KLEIT), Hubli, as her recognized research center. She is working as an Assistant Professor in the Department of VLSI at NMAM Institute of Technology, Nitte. Her research interests include video compression, motion estimation algorithms, and VLSI design for multimedia applications.

T. M. Manu, Department of Electronics and Communication Engineering, KLE Institute of Technology (KLEIT), Hubballi, Karnataka 580027, India, Visvesvaraya Technological University, Belagavi, Karnataka 590018, India

T. M. Manu received his bachelor of Electronics and Communication Engineering from B.D.T. College of Engineering, Davanagere. He obtained his masters from B.V.Bhoomreddy College of Enggg., Hubli. He obtained his Doctorate from Visvesvaraya Technological University, Belgaum. He is actively involved in grooming young researchers for achieving significant contribution in their field of interest. He is an author of a great deal of research studies published at national and international journals as well as conference proceedings. His research interests include digital signal processing, video compression, and embedded systems.

References

Richardson, I.E., The H.264 Advanced Video Compression Standard (Wiley Publishing, New York, 2010).

G. J. Sullivan and T. Wiegand, “Video Compression – From Concepts to the H.264/AVC Standard”, Proceedings of the IEEE 93, 18–31 (2005).

Dong, X., Wen, J., “A pixel-based outlier-free motion estimation algorithm for scalable video quality enhancement”, Front. Comput. Sci. 9, 729–740 (2015).

Xuan Jing and Lap-Pui Chau, “An efficient three-step search algorithm for block motion estimation”, IEEE Transactions on Multimedia 6, 435–438 (2004).

Reoxiang Li, Bing Zeng and M. L. Liou, “A new three-step search algorithm for block motion estimation”, IEEE Transactions on Circuits and Systems for Video Technology 4, 438–442 (1994).

Lai-Man Po and Wing-Chung Ma, “A novel four-step search algorithm for fast block motion estimation”, IEEE Transactions on Circuits and Systems for Video Technology 6, 313–317 (1996).

M. Ghanbari, “The cross-search algorithm for motion estimation (image coding)”, IEEE Transactions on Communications 38, 950–953 (1990).

Chun-Ho Cheung and Lai-Man Po, “A novel cross-diamond search algorithm for fast block motion estimation”, IEEE Transactions on Circuits and Systems for Video Technology 12, 1168–1177 (2002).

Shan Zhu and Kai-Kuang Ma, “A new diamond search algorithm for fast block-matching motion estimation”, IEEE Transactions on Image Processing 9, 287–290 (2000).

Woong IL Choi, Byeungwoo Jeon and Jechang Jeong, “Fast motion estimation with modified diamond search for variable motion block sizes”, Proceedings 2003 International Conference on Image Processing (2003), pp. II-371.

Ce Zhu, Xiao Lin and Lap-Pui Chau, “Hexagon-based search pattern for fast block motion estimation”, IEEE Transactions on Circuits and Systems for Video Technology 12, 349–355 (2002).

I. Ahmad, Weiguo Zheng, Jiancong Luo and Ming Liou, “A fast adaptive motion estimation algorithm”, IEEE Transactions on Circuits and Systems for Video Technology 16, 420–438 (2006).

S. Goel, Y. Ismail and M. A. Bayoumi, “Adaptive search window size algorithm for fast motion estimation in H.264/AVC standard”, 48th Midwest Symposium on Circuits and Systems (2005), pp. 1557–1560.

Yao Nie and Kai-Kuang Ma, “Adaptive rood pattern search for fast block-matching motion estimation”, IEEE Transactions on Image Processing 11, 1442–1449 (2002).

W. Li and E. Salari, “Successive elimination algorithm for motion estimation”, IEEE Transactions on Image Processing 4, 105–107 (1995).

X. Q. Gao, C. J. Duanmu and C. R. Zou, “A multilevel successive elimination algorithm for block matching motion estimation”, IEEE Transactions on Image Processing 9, 501–504 (2000).

Lurng-Kuo Liu and E. Feig, “A block-based gradient descent search algorithm for block motion estimation in video coding”, IEEE Transactions on Circuits and Systems for Video Technology 6, 419–422 (1996).

M. Brunig and W. Niehsen, “Fast full-search block matching”, IEEE Transactions on Circuits and Systems for Video Technology 11, 241–247 (2001).

Ahn, T.G., Moon, Y.H., Kim, J.H., “Fast full-search motion estimation based on multilevel successive elimination algorithm”, IEEE Trans. Circuits Syst. Video Technol. 14, 1265–1269 (2004).

G.-L. Li and M.-J. Chen, “Fast Motion Estimation Algorithm by Finite-State Side Match for H.264 Video Coding Standard”, APCCAS 2006–2006 IEEE Asia Pacific Conference on Circuits and Systems (2006), pp. 414–417.

Han, K.H., Lee, Y.L., “Fast macro block mode decision to reduce H.264 complexity”, IEICE Trans. Fundamentals E88-A, 800–804 (2005).

Basha, S.M., Kannan, M., “Novel architecture and implementation of low power oriented full search block motion estimation”, Cluster Comput 22, 4503–4509 (2019).

Ahmad, W., Mahdavi, H. & Hamzaoglu, I. An efficient versatile video coding motion estimation hardware. J Real-Time Image Proc 21, 25 (2024). https://doi.org/10.1007/s11554-023-01402-8.

Nguyen, V.T. Motion free B-frame coding for neural video compression. arXiv preprint arXiv:2411.17160 (2024).

https://media.xiph.org/video/derf/.

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Published

2025-12-19

How to Cite

Vinutha, M. ., & Manu, T. M. . (2025). Interframe Prediction Based Stationary Block Revalidation VBSME Using Full Search and Vector-driven Techniques. Journal of Mobile Multimedia, 21(06), 1195–1220. https://doi.org/10.13052/jmm1550-4646.2168

Issue

2025: Vol 21 Iss 6

Section

Articles