An efficient block matching algorithm for fast motion ESTIMATION USING COMBINED THREE STEP SEARCH AND DIAMOND SEARCH ALGORITHM
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This document presents a modified three step search algorithm for block matching motion estimation to improve video compression efficiency. It discusses existing block matching algorithms like exhaustive search, three step search, and diamond search. It then describes the proposed modified three step search algorithm in detail and shows it achieves a moderate PSNR value with reduced computational time compared to other methods.
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pp.1432-1435](https://image.slidesharecdn.com/anefficientblockmatchingalgorithmforfastmotion-141028001503-conversion-gate02/85/An-efficient-block-matching-algorithm-for-fast-motion-ESTIMATION-USING-COMBINED-THREE-STEP-SEARCH-AND-DIAMOND-SEARCH-ALGORITHM-16-320.jpg)
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Estimation", Proceeding of 2003 IEEE International Conference
on Neural Networks and Signal Processing, pp. 1262-1265,
Dec. 2003, Nanjing, China](https://image.slidesharecdn.com/anefficientblockmatchingalgorithmforfastmotion-141028001503-conversion-gate02/85/An-efficient-block-matching-algorithm-for-fast-motion-ESTIMATION-USING-COMBINED-THREE-STEP-SEARCH-AND-DIAMOND-SEARCH-ALGORITHM-17-320.jpg)
An efficient block matching algorithm for fast motion ESTIMATION USING COMBINED THREE STEP SEARCH AND DIAMOND SEARCH ALGORITHM
- 1. Presented By Santosh Kumar Chhotray National Institute of Technology, Durgapur
- 2. Introduction Video Compression Process Block Matching Algorithms Problem Definition Proposed Algorithm Simulation Result Conclusion References
- 3. Why Block Matching Algorithm? Factors affecting motion estimation Object Movement Environment movement Video Compression Process
- 5. Exhaustive Search Three Step Search Four Step Search Diamond Search
- 6. Modified Three Step Search 1. Case-1:Search at centre 2. Case-2:Search at corner 3. Case-3:Search at axis Sub_case-1:Search at corner Sub_case-2Search at axis Search for local minima
- 7. Case-1:Best possible search
- 8. Case-2:Search at corners
- 9. Case-3:Diamond Search initiated Sub_case-1: Search at corner
- 10. Case-3:Diamond Search Sub_case-2: Search at axis
- 11. Search for local minima
- 15. Moderate PSNR value Reduced computational time
- 16. [1] Shilpa P. Meher and Sanjay Talbar, ―Fast motion estimation using modified orthogonal search algorithm for video compression‖, Springer Journal ,SIViP (2010) 4:123–128. [2] Renxiang Li, Bing Zeng, and Ming L. Liou, ―A New Three-Step Search Algorithm for Block Motion Estimation‖, IEEE Trans. Circuits And Systems For Video Technology, vol 4., no. 4, pp. 438-442, August 1994 [3] Jiang li et. al. ―Bi-level video: video communication at very low bit rates‖. original work of Microsoft research china,MM01,pp.392- 401,Ottawa,Canada.2001 [4] Anil Kishore Saxena, ,"Rate Optimal Motion Estimation and Compensation in Transform Domain",ABV-IIITM Gwalior, February, 2005 [5] Amit k. Pandit, Sekhar Verma,G.S Tomar,Dheeraj Kannoujia,"Fast motion estimation using modified new block matching algorithm:MTSSDS for efficient video compression in mobile domain",CICN,Nov, 2011 [6] V.Argyriou and T.Vlachos, ―using gradient correlation for sub-pixel motion estimation of video sequence‖ in Proc2005, july2005, pp.1432-1435
- 17. [7] Shan Zhu, and Kai-Kuang Ma, ― A New Diamond Search Algorithm for Fast Block-Matching Motion Estimation‖, IEEE Trans. Image Processing, vol 9, no. 2, pp. 287-290, February 2000 [8] Yao Nie, and Kai-Kuang Ma, ―Adaptive Rood Pattern Search for Fast Block-Matching Motion Estimation‖, IEEE Trans. Image Processing,vol 11, no. 12, pp. 1442-1448, December 2002 [9] Chun-Ho Cheung, and Lai-Man Po, ―A Novel Small Cross-Diamond Search Algorithm for Fast Video Coding and Video Conferencing Applications‖, Proc. IEEE ICIP, September 2002 [10] Iain E. G. Richardson, Video Codec Design, West Sussex: John Wiley & Sons Ltd., 2002, Ch. 4, 5, & 6 [11] C. W. Lam, L. M. Po and C. H. Cheung, "A New Cross- Diamond Search Algorithm for Fast Block Matching Motion Estimation", Proceeding of 2003 IEEE International Conference on Neural Networks and Signal Processing, pp. 1262-1265, Dec. 2003, Nanjing, China