高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于大尺度双边SIFT的SAR图像同名点自动提取方法

王山虎 尤红建 付琨

王山虎, 尤红建, 付琨. 基于大尺度双边SIFT的SAR图像同名点自动提取方法[J]. 电子与信息学报, 2012, 34(2): 287-293. doi: 10.3724/SP.J.1146.2011.00568
引用本文: 王山虎, 尤红建, 付琨. 基于大尺度双边SIFT的SAR图像同名点自动提取方法[J]. 电子与信息学报, 2012, 34(2): 287-293. doi: 10.3724/SP.J.1146.2011.00568
Wang Shan-Hu, You Hong-Jian, Fu Kun. An Automatic Method for Finding Matches in SAR Images Based on Coarser Scale Bilateral Filtering SIFT[J]. Journal of Electronics & Information Technology, 2012, 34(2): 287-293. doi: 10.3724/SP.J.1146.2011.00568
Citation: Wang Shan-Hu, You Hong-Jian, Fu Kun. An Automatic Method for Finding Matches in SAR Images Based on Coarser Scale Bilateral Filtering SIFT[J]. Journal of Electronics & Information Technology, 2012, 34(2): 287-293. doi: 10.3724/SP.J.1146.2011.00568

基于大尺度双边SIFT的SAR图像同名点自动提取方法

doi: 10.3724/SP.J.1146.2011.00568
基金项目: 

国家863计划项目(2007AA120302)资助课题

An Automatic Method for Finding Matches in SAR Images Based on Coarser Scale Bilateral Filtering SIFT

  • 摘要: 针对SIFT应用于SAR图像同名点自动提取的问题,该文提出了一种新的基于各向异性尺度空间的同名点提取方法。该方法首先基于双边滤波器建立图像的各向异性尺度空间,在滤除斑点噪声的同时保留了图像细节;然后利用SIFT在大尺度上检测并描述特征,弱化了斑点噪声对匹配的影响;最后采用双向匹配策略建立同名点,提高了正确匹配的概率。该方法在保持同名点精度的同时增加了同名点的数量。通过不同时相、不同极化、不同波段以及不同视角下的SAR图像同名点提取实验,验证了该方法的优越性和适应性。
  • Tuytelaars T and Mikolajczyk K. Local invariant feature detectors: a survey[J]. Computer Graphics and Vision, 2007, 3(3): 177-280.[2] Mikolajczyk K and Schmid C. A performance evaluation of local descriptors[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(10): 1615-1630.[3] Lowe D G. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2): 91-110.[4] Liu C, Yuen J, and Torralba A. SIFT flow: dense correspondence across scenes and its applications[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(5): 978-994.[5] Lei H and Zhen L. Feature-based image registration using the shape context[J]. International Journal of Remote Sensing, 2010, 31(8): 2169-2177.[6] Martin V, Mar fill R, and Bandera A. Affine image region detection and description [J]. Journal of Physical Agents, 2010, 4(1): 45-54.[7] Gupta R, Patil H, and Mittal A. Robust order-based methods for feature description[C]. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, USA, 2010: 334-341.[8] Pele O and Werman M. The quadratic-chi histogram distance family[C]. The 11th European Conference on Computer Vision (ECCV 2010), Crete, Greece, 2010: 749-762.[9] Li Q L, Wang G Y, Liu J G, et al.. Robust scale-invariant feature matching for remote sensing image registration[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(2): 287-291.[10] 陈尔学, 李增元, 田昕, 等. 尺度不变特征变换法在SAR影响匹配中的应用[J]. 自动化学报, 2008, 34(8): 861-868.Chen Er-xue, Li Zeng-yuan, Tian Xin, et al.. Application of scale invariant feature transform to SAR image registration[J]. Acta Automatic Sinica, 2008, 34(8): 861-868.[11] Tomasi C and Manduchi R. Bilateral filtering for gray and color images[C]. Proc. International Conference on Compute Vision, Bombay, India, 1998: 839-846.[12] Peroma P and Malik J. Scale space and edge detection using anisotropic diffusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-637.
  • 加载中
计量
  • 文章访问数:  2974
  • HTML全文浏览量:  112
  • PDF下载量:  1045
  • 被引次数: 0
出版历程
  • 收稿日期:  2011-06-13
  • 修回日期:  2011-09-13
  • 刊出日期:  2012-02-19

目录

    /

    返回文章
    返回