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使用局部色调映射匹配异源图像 被引量:1

Using local tone mapping to match multi-sensor images
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摘要 色调映射是一种适用于亮度和对比度变化的快速图像匹配方法。由于异源图像间存在复杂的灰度变换关系,直接采用色调映射方法进行匹配的成功率通常难以满足应用需求。为了提高匹配成功率,本文提出基于子区弱切片变换的局部色调映射异源图像匹配方法。首先将实时图划分为不重叠的子区,对每个子区进行直方图均衡化和弱切片变换,通过局部色调映射计算子区与基准图的距离系数图。融合全部距离系数图得到图像匹配结果。实验结果表明,该方法匹配成功率高于现有的色调映射方法,且计算时间仅略高于现有方法,优于异源图像匹配中常用的互信息方法。 Tone mapping is an efficient image matching algorithm adaptive to brightness and contrast variation.Due to the complex and nonconforming relation between multi-sensor images,tone mapping can hardly be directly used on multi-sensor images to achieve satisfactory results.To improve the matching rate,the local tone mapping algorithm is proposed,which includes the following steps:Firstly,the template map is divided into nonoverlapping blocks.,Then,each block is processed through histogram equalization and weak slice transform.Next,the distance maps are calculated for every block by local tone mapping.Finally,the matching result is obtained by fusion all these distance maps.Experimental results show that,the matching rate of local tone mapping significantly outperforms tone mapping and mutual information,while its computation time is slightly longer than that of the tone mapping and less than that of the mutual information.
出处 《国防科技大学学报》 EI CAS CSCD 北大核心 2014年第3期32-35,共4页 Journal of National University of Defense Technology
基金 国家重点基础研究发展计划资助项目(973计划)(2013CB733100)
关键词 图像处理 图像匹配 异源图像 局部色调映射 image processing image matching multi-sensor images local tone mapping
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参考文献12

  • 1Kim Y S, Lee J H, Ra J B. Multi-sensor image registration based on intensity and edge orientation information[ J ]. Pattern Recognition ,2008, 41 ( 11 ) : 3356 -3365.
  • 2Pan C, Zhang Z, Yan H, et al. Muhisource data registration based on NURBS description of contours [ J ]. International Journal of Remote Sensing, 2008, 29(2) : 569 -591.
  • 3Wegner J D, Soergel U. Registration of SAR mad optical images containing bridges over land [ C ]//Proceedings of the EARSeL Symposium: Remote Sensing-New Challenges of High Resolution, 2008.
  • 4苏娟,林行刚,刘代志.一种基于结构特征边缘的多传感器图像配准方法[J].自动化学报,2009,35(3):251-257. 被引量:33
  • 5Pluim J P W, Maintz J B A, Viergever M A. Mutual- information-based registration of medical images : a survey[ J ]. IEEE Transactions on Medical Imaging, 2003, 22 (8): 986 -1004.
  • 6Kovesi P. Image features from phase congruency [ J ]. VIDERE : Journal of computer vision research, 1999, 1 (3) : 1 -26.
  • 7Keller Y, Averbuch A. Multisensor image registration via implicit similarity[ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28 (5) : 794 - 801.
  • 8李壮,杨夏,雷志辉.基于空间子区一致性的异源图像匹配方法[J].国防科技大学学报,2011,33(1):31-34. 被引量:8
  • 9Parmehr E G, Zhang C, Fraser C S. Automatic registration of muhi-source data using mutual information[ J]. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012,1 - 7 : 305 - 308.
  • 10Hel-Or Y,Hel-Or H, David E. Fast template matctling in non- linear tone - mapped images [ C ]//Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2011 : 1355 - 1362.

二级参考文献12

  • 1Li H, Manjunath B S, Mitra S K. A contour-based approach to multisensor image registration. IEEE Transactions on Image Processing, 1995, 4(3): 320-334.
  • 2Dare P, Dowman I. An improved model for automatic feature-based registration of SAR and SPOT images. ISPRS Journal of Photogrammetry and Remote Sensing. 2001, 56(1): 13-28.
  • 3Hong T D, Schowengerdt R A. Automated precise registration of radar and optical satellite images. In: Proceedings of SPIE Conference on Applications of Digital Image Processing. San Diego, USA: IEEE, 2003. 88-96.
  • 4Shekhar C, Govindu V, Chellappa R. Multisensor image registration by feature consensus. Pattern Recognition, 1999, 32(1): 39--52.
  • 5Middelmann W, Pepelka V, Thoennessen U. Registration of multiaspect InSAR images. In: Proceedings of SPIE Conference on Algorithms for Synthetic Aperture Radar Imagery. Orlando, USA: SPIE, 2003, 98-109.
  • 6Yao J C, Kian L G. A refined algorithm for multisensor image registration based on pixel migration. IEEE Transactions on Image Processing, 2006, 15(7): 1839-1847.
  • 7Keller Y, Averbuch A. Multisensor image registration via implicit similarity. IEEE Transactions on Pattern Analysis and Mt~chine Intelligence, 2006, 28(5): 794-801.
  • 8Kruger W. Robust and efficient map-to-image registration with line segments. Machine Vision and Applications, 2001, 13(1): 38-50.
  • 9He X C, Yung N H C. Curvature scale space corner detector with adaptive threshold and dynamic region of support. In: Proceedings of the 17th International Conference on Pattern Recognition. Cambridge, UK: IEEE, 2004. 791-794.
  • 10Bentoutou Y, Taleb N, Kpalma K, Ronsin J. An automatic image registration for applications in remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(9): 2127-2137.

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