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http://dx.doi.org/10.9717/kmms.2015.18.4.437

A Fast Motion Estimation Algorithm using Adaptive Search According to Importance of Search Ranges  

Kim, Tae Hwan (Dept. of IT Convergence and Applications Eng., Pukyong National University)
Kim, Jong Nam (Dept. of IT Convergence and Applications Eng., Pukyong National University)
Jeong, Shin Il (Dept. of Information and Communication Eng., Pukyong National University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.4, 2015 , pp. 437-442 More about this Journal
Abstract
Voice activity detection is very important process that voice activity separated form noisy speech signal for speech enhance. Over the past few years, many studies have been made on voice activity detection, but it has poor performance in low signal to noise ratio environment or fickle noise such as car noise. In this paper, it proposed new voice activity detection algorithm using ensemble variance based on wavelet band entropy and soft thresholding method. We conduct a survey in a lot of signal to noise ratio environment of car noise to evaluate performance of the proposed algorithm and confirmed performance of the proposed algorithm.
Keywords
Motion Estimation; Adaptive Search; Partial Distortion Elimination; Matching Criteria;
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1 F. Dufaus and F. Moscheni, “Motion Estimation Techniques for Digital TV: A Review and a New Contribution,” Proceeding of IEEE, Vol. 83, No. 3, pp. 858-876, 1995.   DOI
2 M.Z. Coban and R.M. Mersereau, “A Fast Exhaustive Search Algorithm for Rate-Constrained Motion Estimation,” IEEE Transactions on Image Processing, Vol. 7, No. 7, pp. 769-773, 1998.   DOI
3 J. Kim and T. Choi, “Adaptive Matching Scan Algorithm based on Gradient Magnitude for Fast Full search in Motion Estimation,” IEEE Transactions on Consumer Electronics, Vol. 45, No. 3pp. 762-772, 1999.   DOI
4 J. Lu, K. Wu, and J. Lin, “Fast Full Search in Motion Estimation by Hierarchical use of Minkowski’s Inequality (HUMI),” Pattern Recognition, Vol. 31, No. 7, pp. 945-952, 1998.   DOI
5 W. Li and E. Salari, “Successive Elimination Algorithm for Motion Estimation,” IEEE Transactions on Image Processing, Vol. 4, No. 1, pp. 105-107, 1995.   DOI
6 H. Wang and R. Mersereau, “Fast Algorithms for the Estimation of Motion Vectors,” IEEE Transactions on Image Processing, Vol. 8, No. 3, pp. 435-438, 1999.   DOI
7 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, Vol. 9, No. 3, pp. 501-504, 2000.   DOI
8 T.G. Ahn, Y.H. Moon, and J.H. Kim, “Fast Full-Search Motion Estimation based on Multilevel Successive Elimination Algorithm,” IEEE Transactions on Circuits and System for Video Technology, Vol. 14, No. 11, pp. 1265-1269, 2004.   DOI
9 J. Kim, S. Byun, Y. Kim, and B. Ahn, “Fast Full Search Motion Estimation Algorithm Using Early Detection of Impossible Candidate Vectors,” IEEE Transactions on Signal Processing, Vol. 50, No. 9, pp. 2355-2365, 2002.   DOI
10 H.264/AVC reference software, http://iphome.hhi.de/suehring/tml/download/old_jm/, (accessed Nov. 2, 2014)
11 유태경, 문광석, 김종남, "서브블록 부분 계수 적응제거를 통한 고속 움직임 추정 알고리즘," 한국멀티미디어학회논문지, 제12권, 제4호, pp. 483-491, Apr. 2009.
12 S. Jin and H. Lee, "Fast Partial Distortion Elimination Algorithm based on Hadamard Probability Model," IEE Electron. Letters, Vol. 44, No. 1, pp. 17-19, 2008.   DOI
13 F. Cheng and S. Sun, “New Fast and Efficient Two-Step Search algorithm for Block Motion Estimation,” IEEE Transactions on Circuits System for Video Technology, Vol. 9, No. 7, pp. 977-983, 1999.   DOI
14 C. Zhu, X. Lin, and L. Chau, “Hexagon Based Search Pattern for Fast Block Motion Estimation,” IEEE Transactions on Circuits System for Video Technology, Vol. 12, No. 7, pp. 349-355, 2002.   DOI