Document Type : Review Article

Author

Abstract

Motion estimation (ME) is a part of video codecs which results in further compression of video data. But it requires a huge amount of computations. To overcome this drawback, there have been offered too many techniques yet. In this paper with the aid of fuzzy inference, an efficient algorithm is devised. The proposed algorithm exploits spatial correlation as well as temporal correlation among motion vectors. This algorithm uses fuzzy rules to determine the initial motion vector. After that, a local search around initial vector is carried out. In order to decrease the complexity of the algorithm, a look-up table is used. In this table, defuzzified values are stored. Also, to further reduction of complexity, few computations are performed in the proposed algorithm for stationary and quasi stationary blocks. To determine which block can be regarded as stationary or quasi stationary block, a simple comparison with a predefined threshold is done. The experimental results show that the proposed algorithm performs better than other fast block matching algorithms in terms of picture quality and computational complexity.  

Keywords

[1] Richardson; Iain E.G. Video Codec Design, England: John Wiley & Sons Ltd, (2002)
[2] Ghanbari, Mohammad. Video Coding, an Introduction to Standard Codecs, London: IEE Series, (1999)
[3] Nam, Jae Yeal, et al; “New Fast Search Algorithm for Block Matching Motion Estimation Using Temporal and Spatial Correlation of Motion Vector”, IEEE Trans. Consumer Electronics, Vol. 46, No. 4, pp. 934-42, (2000):
[4] Gharavi, H., and Mills, Mike; “Block Matching Motion Estimation-New Results”, IEEE Trans.Circuits Sys, 37, No. 5, pp. 649-51, (1990)
[5] Chen, Mei-Juan et al, “A New Block-Matching Criterion for Motion Estimaton”, IEEE Trans. Circuits. Sys. Video Technol, Vol. 5, No. 3, (1995): 231-6.
[6] Sorwar, Golam, Manzurand Murshed and Laurence S. Dooley; “A Fully Adaptive Distance-Dependent Thresholding Search (FADTS) Algorithm for Performance Management Motion Estimation”, IEEE Trans. Circuits Sys. Video Technol., Vol. 17, No. 4, pp. 429-40, (2007)
[7] Jain, J and A. Jain; “Displacement Measurement and its Application in Interframe Image Coding” IEEE Trans. Commun., COMM-29, pp. 1799-1808, (1981)
[8] T. Koga, et al.; “Motion Compensated Interframe Coding for Video Conferencing”, Paper presented at National Telecommunication Conference, New Orleans, LA, (November 1981)
[9] Po, Lai-Man and Wing-Chung Ma; “A Novel Four-Step Search Algorithm for Fast Block Motion Estimation”, IEEE Trans. Circuits Syst. Video Techno., Vol. 6, No. 3, pp. 313-17, (1996)
[10] Tham, Jo Yew et al; “A Novel Unrestricted Center-Biased Diamond Search Algorithm for Block Motion Estimation”, IEEE Trans. Circuits Syst. Video Technol., Vol. 8, No. 4, pp.: 369-77, (1998)
[11] L.P. Chau, and C. Zhu, “A Fast Octagon Based Search Algorithm for Motion Estimation”, Elsevier science, Signal Processing journal, Vol. 83, No. 3, pp. 671-75, (2003)
[12] Chen, Pei-Yin and Jer Min Jou, “An Efficient Blocking Matching Algorithm Based on Fuzzy Reasoning” IEEE Trans Syst, Man, Cybern.-Part B, Vol. 31, No. 2, pp. 253-59, (2001)
[13] Soroushmehr, S.M.Reza, Shadrokh Samavi and Shahram Shirani, “Block Matching Algorithm Based on Local Codirectionality of Blocks”, Paper presented at the IEEE International Conference on Multimedia and Expo (ICME), New York, (June 2009)
[14] Ahmad, Ishfaq et al, “A Fast Adaptive Motion Estimation Algorithm”, IEEE Trans. Circuits Sys. Video Technol., Vol. 16, No. 3, pp. 420-38, (2006)
[15] Tourapis, A. M., O. C. Au, and M. L. Liou, “Fast Block-Matching Motion Estimation Using Predictive Motion Vector Field Adaptive Search Technique (PMVFAST)”, ISO/IEC JTC1/SC29/WG11 MPEG2000/M5866, Noordwijkerhout, The Netherlands, (March 2000)
[16] Tsai, Jang-Jer and Hsueh-Ming Hang, “Modeling of Pattern-Based Block Motion Estimation and its Application”, IEEE Trans. Circuits Sys. Video Technol., Vol. 19, No. 1, pp. 108-13, (2009)