一种适用于SAR图像配准的改进SIFT算法
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  • 英文篇名:An improved SIFT algorithm for SAR image registration
  • 作者:迟英朋 ; 刘畅
  • 英文作者:CHI Yingpeng;LIU Chang;Institute of Electronics, Chinese Academy of Sciences;University of Chinese Academy of Sciences;
  • 关键词:图像配准 ; SIFT算法 ; ROEWA算子 ; OTSU算法
  • 英文关键词:image registration;;SIFT algorithm;;ROEWA operator;;OTSU algorithm
  • 中文刊名:ZKYB
  • 英文刊名:Journal of University of Chinese Academy of Sciences
  • 机构:中国科学院电子学研究所;中国科学院大学;
  • 出版日期:2019-03-14
  • 出版单位:中国科学院大学学报
  • 年:2019
  • 期:v.36
  • 基金:国家重点研发计划项目(2017YFB0503001)资助
  • 语种:中文;
  • 页:ZKYB201902009
  • 页数:8
  • CN:02
  • ISSN:10-1131/N
  • 分类号:118-125
摘要
针对SAR图像特点,在传统SIFT算法的基础上,结合ROEWA和OTSU算法,提出一种改进的SIFT算法。该方法首先通过ROEWA和OTSU算法分别检测图像的边缘区域和阴影区域,再与SIFT算法相融合检测特征点、寻找匹配点并计算变换矩阵实现图像配准。与原算法相比,该方法消除了DoG算子的边缘响应和阴影的影响,使提取到的特征点更加精确,可提高正确匹配率,增强算法的稳定性,并提升图像配准的精度。
        In view of the features of SAR images, we propose an improved SIFT algorithm based on the traditional SIFT algorithm combined with the ROEWA and OTSU algorithms. The algorithm firstly detects the edge region and shadow area of the image by using ROEWA and OTSU algorithms, respectively. Then, the feature points are fused by using SIFT algorithm to find the matching points and calculate the transformation matrix for image registration. Compared with the original algorithm, this method eliminates the influences of the edge response of the DoG operator and the shadow, makes the extraction of feature points more accurate, and enhances the correct matching rate, the stability of the algorithm, and the accuracy of image registration.
引文
[1] 李孚煜, 叶发茂. 基于SIFT的遥感图像配准技术综述[J]. 国土资源遥感, 2016, 28(2):14-20.
    [2] 徐颖, 周焰. SAR图像配准方法综述[J]. 地理空间信息, 2013, 11(3):63-66.
    [3] Chatelain F, Tourneret J Y, Inglada J, et al. Bivariate gamma distributions for image registration and change detection[J]. IEEE Transactions on Image Processing, 2007, 16(7):1 796.
    [4] Argyriou V, Tzimiropoulos G. Frequency domain subpixel registration usingHOG phase correlation[J]. Computer Vision & Image Understanding, 2016, 155:70-82.
    [5] Suo Z, Li Z, Bao Z. Multi-channel SAR-GMTI method robust to Coregistration Error of SAR Images[J]. Aerospace & Electronic Systems IEEE Transactions on, 2010, 46(4):2 035-2 043.
    [6] 阿布来提·依布拉音, 王治强, 刘薇, 高慧婷. 基于Hough直线检测的深度图像配准方法[J]. 中国科学院研究生院学报, 2013, 30(1):112-116.
    [7] Suri S, Reinartz P. Mutual-information-based registration ofTerraSAR-X and ikonos imagery in urban areas[J]. IEEE Transactions on Geoscience & Remote Sensing, 2010, 48(2):939-949.
    [8] 苏娟, 李彬, 王延钊. 一种基于封闭均匀区域的SAR图像配准方法[J]. 电子与信息学报, 2016, 38(12):3 282-3 288.
    [9] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2):91-110.
    [10] Hossein-Nejad Z, Nasri M. An adaptive image registration method based on SIFT features and RANSAC transform[J]. Computers & Electrical Engineering, 2016. 62:524-537.
    [11] 王茜, 宁纪锋, 曹宇翔,等. 基于SIFT算法的无人机遥感图像拼接技术[J]. 吉林大学学报(信息科学版), 2017, 35(2):188-197.
    [12] Zhong H, Zhang J, Liu G. Robust polarimetric SAR despeckling based on nonlocal means and distributed Lee filter[J]. IEEE Transactions on Geoscience & Remote Sensing, 2014, 52(7):4 198-4 210.
    [13] Fj?rtoft R, Lopès A, Marthon P, et al. An optimal multiedge detector for SAR image segmentation[J]. IEEE Transactions on Geoscience & Remote Sensing, 1998, 36(3):793-802.
    [14] 刘夯, 何政伟, 赵银兵, 等. SAR图像ROEWA边缘检测器的改进[J]. 遥感学报, 2017, 21(2):273-279.
    [15] Bangare S L, Dubal A, Bangare P S, et al. Reviewing Otsu's method for image thresholding[J]. International Journal of Applied Engineering Research, 2015, 10(9):21 777-21 783.
    [16] 赵夫群, 周明全, 耿国华, 等. 基于GA-Otsu法的图像阈值分割及定量识别[J]. 吉林大学学报(工学版), 2017, 47(3):959-964.
    [17] Liu X, Tian Z, Lu Q, et al. A new affine invariant descriptor framework in shearlets domain for SAR image multiscale registration[J]. AEU - International Journal of Electronics and Communications, 2013, 67(9):743-753.