Volume 43 Issue 5
Nov.  2023
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Article Navigation >  Chinese Journal of Space Science  > 2023  >  43(5): 840-852 Open Access
WANG Rui, BAO Lili, CAI Yanxia. Image Feature Extraction and Matching of Augmented Solar Images in Space Weather. Chinese Journal of Space Science, 2023, 43(5): 840-852 doi: 10.11728/cjss2023.05.2022-0064
Citation: WANG Rui, BAO Lili, CAI Yanxia. Image Feature Extraction and Matching of Augmented Solar Images in Space Weather. Chinese Journal of Space Science, 2023, 43(5): 840-852 doi: 10.11728/cjss2023.05.2022-0064
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Image Feature Extraction and Matching of Augmented Solar Images in Space Weather

doi: 10.11728/cjss2023.05.2022-0064 cstr: 32142.14.cjss2023.05.2022-0064
  • 1.

    State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049

  • 3.

    Key Laboratory of Science and Technology on Environment Space Situation Awareness, Chinese Academy of Sciences, Beijing 100190

Funds:  Supported by the Key Research Program of the Chinese Academy of Sciences (ZDRE-KT-2021-3)
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    Abstract
  • Augmented solar images were used to research the adaptability of four representative image extraction and matching algorithms in space weather domain. These include the scale-invariant feature transform algorithm, speeded-up robust features algorithm, binary robust invariant scalable keypoints algorithm, and oriented fast and rotated brief algorithm. The performance of these algorithms was estimated in terms of matching accuracy, feature point richness, and running time. The experiment result showed that no algorithm achieved high accuracy while keeping low running time, and all algorithms are not suitable for image feature extraction and matching of augmented solar images. To solve this problem, an improved method was proposed by using two-frame matching to utilize the accuracy advantage of the scale-invariant feature transform algorithm and the speed advantage of the oriented fast and rotated brief algorithm. Furthermore, our method and the four representative algorithms were applied to augmented solar images. Our application experiments proved that our method achieved a similar high recognition rate to the scale-invariant feature transform algorithm which is significantly higher than other algorithms. Our method also obtained a similar low running time to the oriented fast and rotated brief algorithm, which is significantly lower than other algorithms.

     

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