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一種基于小波域的運(yùn)動(dòng)估計(jì)方法

王兵,  趙榮椿,  程英蕾

王兵, 趙榮椿, 程英蕾. 一種基于小波域的運(yùn)動(dòng)估計(jì)方法[J]. 電子與信息學(xué)報(bào), 2005, 27(5): 757-761.
引用本文: 王兵, 趙榮椿, 程英蕾. 一種基于小波域的運(yùn)動(dòng)估計(jì)方法[J]. 電子與信息學(xué)報(bào), 2005, 27(5): 757-761.
Wang Bing, Zhao Rong-chun, Cheng Ying-lei. A Motion Estimation Algorithm Based on the Wavelet Domain[J]. Journal of Electronics & Information Technology, 2005, 27(5): 757-761.
Citation: Wang Bing, Zhao Rong-chun, Cheng Ying-lei. A Motion Estimation Algorithm Based on the Wavelet Domain[J]. Journal of Electronics & Information Technology, 2005, 27(5): 757-761.

一種基于小波域的運(yùn)動(dòng)估計(jì)方法

A Motion Estimation Algorithm Based on the Wavelet Domain

  • 摘要: 提出了一種基于多尺度邊緣檢測(cè)(MED)與連續(xù)小波變換(CWT)相結(jié)合的運(yùn)動(dòng)目標(biāo)估計(jì)方法。首先,利用多尺度邊緣檢測(cè)算法,得到抗噪性好、邊緣連續(xù)清晰的運(yùn)動(dòng)目標(biāo)邊緣圖像。然后,利用連續(xù)小波變換把目標(biāo)序列圖像映射到運(yùn)動(dòng)狀態(tài)參數(shù)空間。該方法同時(shí)擁有MED和CWT的優(yōu)良特性。實(shí)驗(yàn)表明,該算法是對(duì)旋轉(zhuǎn)、遮擋和有噪等復(fù)雜運(yùn)動(dòng)目標(biāo)進(jìn)行運(yùn)動(dòng)估計(jì)的有效方法。
    Abstract: This paper describes a novel motion object detection and tracking algorithm based on the Multiscale Edges Detection (MED) and Continuous Wavelet Transform (CWT). Multiscale representations are very effective for analyzing the information content of images. First, moving object multiscale edges are detected and characterized from the local maxima of a wavelet transform. Then, the CWT is used to map the input signal space to a motion parameters space. It is designed so as to possess simultaneously the properties of MED and CWT. Experimental results show that the proposed algorithm is effective with robustness for noise, rotation and occlusions.
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  • Tekalp A M著,崔之祜,江春,等譯.數(shù)字視頻處理.北京:電子工業(yè)出版社,1998:68-137.[2]Mallat S著,揚(yáng)力華,戴道清,等譯.信號(hào)處理的小波導(dǎo)引.北京:機(jī)械工業(yè)出版社,2002:142-150.[3]Magarey J, Kingsbery N G. Motion estimation using a complex-valued wavelet transform[J].IEEE Trans. on Signal Processing.1998, 46(4):1069-[4]Kingsbury N G. A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. IEEE International Conference on Image Processing, Vancouver,Canada, 2000: 1429- 1432.[5]Mujica F A, Leduc J P, Murenzi R, Smith M J T. A new motion parameter estimation algorithm based on the continuous wavelet transform[J].IEEE Trans. on Image Processing.2000, 9(5):873-[6]Mallat S, Zhong S. Characterization of signals from multiscale edges[J].IEEE Trans. on Pattern Analysis and Machine Intelligence.1992, 14(7):710-[7]Leduc J P, Mujica F, Murenzi R, Smith M. Spatio-temporal wavelet transforms for motion tracking. IEEE International Conference on Acoustics, Speech, and Signal Processing, Munich,Germany, 1997, (4): 3013 - 3016.[8]Destin M D, Murenzi R. Spatio temporal wavelets: application to the analysis of moving patterns. International Conference on Wavelets Analysis of Applications, Toulouse, France, 1993:399 - 408.[9]Antoine J P, Murenzi R. Two dimensional directional wavelets and the scale-angle representation[J].Signal Processing.1996, 52(3):259-[10]Chanbari M. The cross-search algorithm for motion estimation[J].IEEE Trans. on Communications.1990, 38(7):950-
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出版歷程
  • 收稿日期:  2003-12-25
  • 修回日期:  2004-04-20
  • 刊出日期:  2005-05-19

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