Laser & Optoelectronics Progress, Volume. 57, Issue 6, 062803(2020)

Fast Registration of Visible light and Synthetic Aperture Radar Images

Zhihua Xie1,2、**, Jinghong Liu1、*, Hui Sun1,2, and Jiaqi Peng3
Author Affiliations
  • 1Department of Airborne Optical Imaging and Measurement, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3First Military Representative Office in Changchun, Changchun, Jilin 130033, China
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    Aim

    ing at the problem of high complexity and low processing speed of heterologous image registration algorithms, a fast registration algorithm of visible light and synthetic aperture radar (SAR) images is proposed. In the image preprocessing stage, the redundant information in visible light and SAR images is removed, and two different types of images are filtered respectively with Gauss low-pass filter and non-local mean filter (NLM) algorithms. Then, the multi-scale Harris method is used to detect and extract feature points, and the gradient position orientation histogram (GLOH) method is used to construct descriptors of feature points. Finally, the feature points in the original image are reconstructed based on the feedback mechanism, and the actual position of the feature points to be matched in the original image is got, so as to complete the reconstruction and matching of the feature points in the original image. The experimental results show that compared with scale invariant feature transform-modification (SIFT-M) method, this algorithm significantly reduces the running time while maintaining the average registration accuracy of more than 80%, and has important application value.

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    Zhihua Xie, Jinghong Liu, Hui Sun, Jiaqi Peng. Fast Registration of Visible light and Synthetic Aperture Radar Images[J]. Laser & Optoelectronics Progress, 2020, 57(6): 062803

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Aug. 14, 2019

    Accepted: Aug. 28, 2019

    Published Online: Mar. 6, 2020

    The Author Email: Xie Zhihua (xiezhihua17@mails.ucas.ac.cn), Liu Jinghong (liu1577@126.com)

    DOI:10.3788/LOP57.062803

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