结合分割和改进SIFT的不同波段SAR图像配准

doi:10.3969/j.issn.1009-086x.2018.03.006

现代防御技术 ›› 2018, Vol. 46 ›› Issue (3): 41-47.DOI: 10.3969/j.issn.1009-086x.2018.03.006

结合分割和改进SIFT的不同波段SAR图像配准

王延钊^{1, 2}, 李彬³, 崔剑¹, 占必超¹

1.北京遥感设备研究所, 北京 100854;
2.火箭军工程大学初级指挥学院, 陕西西安 710025;
3.中国人民解放军31001部队, 北京 100094

出版日期:2018-05-30 发布日期:2020-10-22
作者简介:王延钊(1992-), 男, 江苏连云港人。硕士生, 主要从事SAR图像配准研究。
通信地址:710025 陕西省西安市灞桥区同心路2号4503分队 E-mail:wyzhao1874@foxmail.com

Image Segmentation and Improved SIFT for SAR Image Registration of Different Bands

WANG Yan-zhao^{1, 2}, LI Bin³, CUI Jian¹, ZHAN Bi-chao¹

1.Beijing Institute of Remote Sensing Equipment, Beijing 100854, China;
2.Rocket Force University of Engineering, Elementary Command College, Shaanxi Xi' an 710025, China;
3.PLA, No.31001 Troop, Beijing 100094, China

Online:2018-05-30 Published:2020-10-22

摘要/Abstract

摘要： 针对不同波段SAR图像配准问题,提出一种结合阈值分割和改进SIFT描述子的配准方法。该方法首先基于改进的二维交叉熵进行图像分割,通过形态学处理获得图像的稳定区域;然后利用Sobel算子改进特征点梯度幅值和方向的计算,并通过优化的梯度位置方向直方图(GLOH)特征生成新的关键点描述子;最后采用距离比和快速抽样一致(FSC)算法获得最佳匹配点对,完成图像配准。实验结果表明,该方法在提升算法效率的同时,可以获得较高的配准精度。

关键词: 图像配准, 尺度不变特征, 二维交叉熵, 阈值分割, 梯度位置方向直方图, 快速抽样一致

Abstract: An accurate registration method on the basis of threshold segmentation and optimized scale-invariant feature transform (SIFT) feature descriptor is proposed for synthetic aperture radar (SAR) images with different bands. Improved 2D cross entropy is adopted for image segmentation, and stable regions are detected with morphological processing. Sobel operator is adopted to compute the gradient magnitudes and orientations of SIFT feature points detected in stable regions. The gradient location orientation hologram (GLOH) is optimized for a more practical use in extraction of a new feature descriptor. The distance ratio and fast sample consensus (FSC) algorithm are introduced to obtain the best match result. Experimental results show that the proposed method can improve the efficiency of the algorithm while achieving high registration accuracy.

Key words: image registration, scale-invariant feature transform, two-dimensional cross entropy, threshold segmentation, gradient location orientation hologram(GLOH), fast sample consensus

中图分类号:

王延钊, 李彬, 崔剑, 占必超. 结合分割和改进SIFT的不同波段SAR图像配准[J]. 现代防御技术, 2018, 46(3): 41-47.

WANG Yan-zhao, LI Bin, CUI Jian, ZHAN Bi-chao. Image Segmentation and Improved SIFT for SAR Image Registration of Different Bands[J]. Modern Defense Technology, 2018, 46(3): 41-47.

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结合分割和改进SIFT的不同波段SAR图像配准

Image Segmentation and Improved SIFT for SAR Image Registration of Different Bands

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