Electronics and Electrical Engineering and Control

SAR image registration algorithm based on echo information of overlapping subaperture

  • Zheng YE ,
  • Daiyin ZHU ,
  • Di WU
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  • 1.College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
    2.Key Laboratory of Radar Imaging and Microwave Photonics,Ministry of Education,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
E-mail: yz1994@nuaa.edu.cn

Received date: 2022-04-07

  Revised date: 2022-04-25

  Accepted date: 2022-07-04

  Online published: 2022-07-21

Supported by

Aeronautical Science Foundation of China(20182052013)

Abstract

Synthetic Aperture Radar (SAR) image registration is the process of finding the geometric transformation relationship between multiple SAR images to calibrate different images to a unified spatial coordinate system. When traditional optical image registration methods, such as Scale-Invariant Feature Transform (SIFT) combined with Random Sample Consensus (RANSAC) algorithm, are used for SAR image registration, the registration performance is greatly affected by the interference of multiplicative speckle noise. In this paper, a SAR image registration algorithm is proposed based on the echo information of overlapping subaperture. In the imaging processing of the complex echo data, using the phase information and the subaperture autofocusing algorithm, highly correlated overlapping subaperture images are obtained. The multiimage registration methods are used to achieve the subaperture image registration within and between imaging apertures, so as to improve the accuracy of SAR image registration. The processing results of the measured data of several different scenes show that the proposed algorithm has more homonymous points, fewer mismatched point pairs, and smaller root mean square error than the SIFT + RANSAC algorithm. Moreover, the proposed algorithm is more robust to speckle noise, and thereby gains the improved registration performance.

Cite this article

Zheng YE , Daiyin ZHU , Di WU . SAR image registration algorithm based on echo information of overlapping subaperture[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(8) : 327254 -327254 . DOI: 10.7527/S1000-6893.2022.27254

References

1 WANG F, WU Y, ZHANG Q, et al. Unsupervised change detection on SAR images using triplet Markov field model[J]. IEEE Geoscience and Remote Sensing Letters201310( 4): 697- 701.
2 邓炜, 赵荣椿. 基于小波变换的SAR图像相干斑噪声消除方法研究[J]. 信号处理200117( 1): 86- 90, 71.
  DENG W, ZHAO R C. The study on coherent speckle reduction in SAR image using wavelet[J]. Signal Processing200117( 1): 86- 90, 71 (in Chinese).
3 许斌, 雷斌, 孙韬, 等. 一种多特征匹配的可见光与SAR图像配准算法[J]. 遥感信息201833( 3): 85- 90.
  XU B, LEI B, SUN T, et al. A multi-feature matching algorithm for visible light and SAR images registration[J]. Remote Sensing Information201833( 3): 85- 90 (in Chinese).
4 XU P F, ZHANG L, YANG K Y, et al. Nested-SIFT for efficient image matching and retrieval[J]. IEEE MultiMedia201320( 3): 34- 46.
5 SEDAGHAT A, EBADI H. Remote sensing image matching based on adaptive binning SIFT descriptor[J]. IEEE Transactions on Geoscience and Remote Sensing201553( 10): 5283- 5293.
6 LOWE D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision200460( 2): 91- 110.
7 DELLINGER F, DELON J, GOUSSEAU Y, et al. SAR-SIFT: A SIFT-like algorithm for SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing201553( 1): 453- 466.
8 孙明超, 马天翔, 宋悦铭, 等. 基于相位特征的可见光和SAR遥感图像自动配准[J]. 光学 精密工程202129( 3): 616- 627.
  SUN M C, MA T X, SONG Y M, et al. Automatic registration of optical and SAR remote sensing image based on phase feature[J]. Optics and Precision Engineering202129( 3): 616- 627 (in Chinese).
9 XING M D, JIANG X W, WU R B, et al. Motion compensation for UAV SAR based on raw radar data[J]. IEEE Transactions on Geoscience and Remote Sensing200947( 8): 2870- 2883.
10 王颖, 高云芳, 李青山, 等. FMCW SAR相位梯度自聚焦算法研究[J]. 中国电子科学研究院学报20094( 6): 651- 655.
  WANG Y, GAO Y F, LI Q S, et al. Research on phase gradient autofocus algorithm for FMCW SAR[J]. Journal of China Academy of Electronics and Information Technology20094( 6): 651- 655 (in Chinese).
11 武昕伟, 朱兆达, 朱岱寅. 相位梯度自聚焦算法在条带模式SAR中的应用[J]. 数据采集与处理200217( 4): 437- 440.
  WU X W, ZHU Z D, ZHU D Y. Phase gradient autofocus algorithm for stripmap SAR autofocus[J]. Journal of Data Acquisition & Processing200217( 4): 437- 440 (in Chinese).
12 MIKOLAJCZYK K, SCHMID C. A performance evaluation of local descriptors[C]∥ IEEE Transactions on Pattern Analysis Machine Intelligence, 200527( 10): 1615- 1630.
13 FISCHLER M A, BOLLES R C. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography[J]. Communications of the ACM198124( 6): 381- 395.
14 KE Y, SUKTHANKAR R. PCA-SIFT: A more distinctive representation for local image descriptors[C]∥ Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE Press, 2004: 511- 517.
15 MA J Y, ZHOU H B, ZHAO J, et al. Robust feature matching for remote sensing image registration via locally linear transforming[J]. IEEE Transactions on Geoscience and Remote Sensing201553( 12): 6469- 6481.
16 MOREIRA A. An improved multi-look technique to produce SAR imagery[C]∥ IEEE International Conference on Radar. Piscataway: IEEE Press, 2002: 57- 63.
17 BURNS B L, CORDARO J T. SAR image-formation algorithm that compensates for the spatially variant effects of antenna motion[C]∥ SPIE’s International Symposium on Optical Engineering and Photonics in Aerospace Sensing. Proc SPIE 2230Algorithms for Synthetic Aperture Radar Imagery, 1994: 14- 24.
18 DOERRY A W. Synthetic aperture radar processing with polar formatted subapertures[C]∥ Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers. Piscataway: IEEE Press, 1994: 1210- 1215.
19 李浩林, 陈露露, 张磊, 等. 相位梯度自聚焦在FFBP聚束SAR处理中的应用[J]. 西安电子科技大学学报201441( 3): 26- 32.
  LI H L, CHEN L L, ZHANG L, et al. Phase gradient autofocus within FFBP flow for spotlight SAR processing[J]. Journal of Xidian University201441( 3): 26- 32 (in Chinese).
20 曾文锋, 李树山, 王江安. 基于仿射变换模型的图像配准中的平移、旋转和缩放[J]. 红外与激光工程200130( 1): 18- 20, 17.
  ZENG W F, LI S S, WANG J A. Translation, rotation and scaling changes in image registration based affine transformation model[J]. Infrared and Laser Engineering200130( 1): 18- 20, 17 (in Chinese).
21 张红蕾, 宋建社, 翟晓颖. 一种基于二维最大熵的SAR图像自适应阈值分割算法[J]. 电光与控制200714( 4): 63- 65, 69.
  ZHANG H L, SONG J S, ZHAI X Y. A 2D maximum-entropy based self-adaptive threshold segmentation algorithm for SAR image processing[J]. Electronics Optics & Control200714( 4): 63- 65, 69 (in Chinese).
22 BERIZZI F, CORSINI G. Autofocusing of inverse synthetic aperture radar images using contrast optimization[J]. IEEE Transactions on Aerospace and Electronic Systems199632( 3): 1185- 1191.
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