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基于最大化對(duì)齊度的多模態(tài)圖像自動(dòng)配準(zhǔn)

王東峰,  鄒謀炎

王東峰, 鄒謀炎. 基于最大化對(duì)齊度的多模態(tài)圖像自動(dòng)配準(zhǔn)[J]. 電子與信息學(xué)報(bào), 2003, 25(6): 755-762.
引用本文: 王東峰, 鄒謀炎. 基于最大化對(duì)齊度的多模態(tài)圖像自動(dòng)配準(zhǔn)[J]. 電子與信息學(xué)報(bào), 2003, 25(6): 755-762.
Wang Dongfeng, Zou Mouyan . Automatic registration of multi-modal images based on the maximization of the alignment metric[J]. Journal of Electronics & Information Technology, 2003, 25(6): 755-762.
Citation: Wang Dongfeng, Zou Mouyan . Automatic registration of multi-modal images based on the maximization of the alignment metric[J]. Journal of Electronics & Information Technology, 2003, 25(6): 755-762.

基于最大化對(duì)齊度的多模態(tài)圖像自動(dòng)配準(zhǔn)

Automatic registration of multi-modal images based on the maximization of the alignment metric

  • 摘要: 該文討論圖像配準(zhǔn)的廣義定義并提出一種新的圖像配準(zhǔn)準(zhǔn)則對(duì)齊度。對(duì)齊度能夠正確地反映兩幅不同灰度屬性的圖像是否配準(zhǔn),并且將圖像配準(zhǔn)歸結(jié)為對(duì)齊度的最大化。新準(zhǔn)則可以用來(lái)配準(zhǔn)多模態(tài)圖像包括灰度屬性差異很大的圖像。該文應(yīng)用多分辨率方法和Powell方向族搜索法來(lái)最大化對(duì)齊度。因此,用該方法可以自動(dòng)地處理圖像配準(zhǔn)問(wèn)題,不需要定義地標(biāo)點(diǎn)或特征點(diǎn)。多模態(tài)醫(yī)學(xué)圖像和遙感圖像的自動(dòng)配準(zhǔn)的例子說(shuō)明了該文方法的有效性。
    Abstract: This paper discusses the generalized definition of image registration and proposes a new measure of image registration-the Alignment Metric(AM). This metric can effectively describe the degree of match of two images with different gray level properties. As a result, the problem of image registration is turned into the maximization of the AM. The new criterion can be used to register multi-modal images including the images with different gray level properties. The Powells direction set method with multi-resolution is used to search for a global maximum of the AM. The images can then be registered automatically without the need of the previously located control points or landmark points. Experiments using multi-modal medical and remote sensing images demonstrate the effectiveness of the method.
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  • A.羅申菲爾特,A.C.卡克著,余英林等譯,數(shù)字圖像處理,北京,人民郵電出版社,1982,第1,2章.[2]M. Svedlow, C. D. McGillem, P. E. Anuta, Experimental examination of similarity measures and preprocessing methods used for image registration, Symposium on Machine Processing of Remotely Sensed Data, Purdue University, Indiana, June 1976, 4A-9.[3]P.A. Viola, W. M. Wells Ⅲ, Alignment by maximization of mutual information, Proc. 5th Int.Conf. Computer Vision, Boston, MA, June, 1995, 16-23.[4]P.A. Viola, W. M. Wells Ⅲ. Alignment by maximization of mutual information, International Journal of Computer Vision, 1997, 24(2), 137-154.[5]A. Collignon, F. Maes, D. Delaere, D. Vandermeulen, P. Suetens, G. Marchal, Automated multimodality image registration based on information theory, Proc. of the Information Processing in Medical Imaging Conference, Norwell, MA: Kluwer, 1995, 263-274.[6]Jsien P. W. Pluim, J. B. Antoine, Max A. Viergever, Image registration by maximization of combined mutual information and gradient information, IEEE Trans. on Medical Imaging, 2000,19(8), 809-814.[7]Philippe Thevenaz, Michael Unser, Optimization of mutual information for multiresolution image registration, IEEE Trans. on Image Processing, 2000, 9(12), 2083-2098.[8]S. Alliney, Spatial registration of multispectral and multitemporal digital imagery using fastFourier transform techniques, IEEE Trans. on Pattern Analysis and Machine Intelligence, 1993,15(5), 499-504.[9]S. Alliney, C. Morandi, Digital image registration using projections, IEEE Trans. on Pattern Analysis and Machine Intelligence, 1986, 8(2), 222-233.[10]B.S. Reddy, B.N. Chatterji, An FFT-based technique for translation, rotation, and scale-invariant image registration, IEEE Trans. on Image Processing, 1996, 5(8), 1266-1271.[11]J. Flusser, T. Suk, A moment-based approach to registration of images with affine geometric distortion, IEEE Trans. on Geoscience and Remote Sensing, 1994, 32(2), 382-387.[12]H. Li, B.S. Manjunath, S. K. Mitra, A contour-based approach to multisensor image registration, IEEE Trans. on Image Processing, 1995, 4(3), 320-334.[13]A. Goshtasby, G. C. Stockman, C. V. Page, A region-based approach to digital image registration with subpixel accuracy, IEEE Trans. on Geoscience and Remote Sensing, 1986, GE-24(3), 390-399.[14]L.G. Brown, A survey of image registration techniques, ACM Computing Surveys, 1992, 24(4),325-376.[15]A. D. Ventura, A. Rampini, R. Schettini, Image registration by recognition of corresponding structures, IEEE Trans. on Geoscience and Remote Sensing, 1990, 28(3), 305-314.[16]W.H. Press, S. A. Teukolsky, W. T. Vetterling, B. P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, Cambridge University Press, Cambridge, U.K., 1988, 309-317.
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出版歷程
  • 收稿日期:  2002-01-15
  • 修回日期:  2002-04-15
  • 刊出日期:  2003-06-19

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