Abstract
Aiming at the requirements of auto-filtering of ISAR images of space targets, a hierarchical evaluation method of ISAR image quality based on fusion features is proposed. Firstly, the overall texture, detail intensity, and signal-to-noise ratio of ISAR image are extracted, and the comprehensive features representing ISAR image quality are formed after normalization and fusion. Then, the image quality evaluation sample database is established. Combined with the manual grading evaluation results, the image quality evaluation model is trained by SVM machine learning algorithm. This method combines the advantages of subjective and objective evaluation and can realize the rapid and accurate classification of space target ISAR images.
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References
Zhou, Y.J., Ma, Y., Zhang, L., et al.: Review of on-orbit state estimation of space targets with radar imagery. J. Radars 10(4), 607–621 (2021). https://doi.org/10.12000/JR21086
Niu, W., Guo, S.P., Shi, J.L., et al.: Quality assessment for adaptive optics image post-processing by LoG domain matching. Infrared Laser Eng. 47(11), 1–9 (2018). https://doi.org/10.3788/IRLA201847.1111005
Zhang, D.T.: Research and Implementation of Image Quality Assessment for Spatial Images. Master's thesis of Beijing Jiaotong University, P1-P6 (2017)
Huang, L., Wang, Y., Jin, S.: A qualitative evaluation approach for ISAR image performance. Radar Sci. Technol. 15(1), 43–49 (2017). https://doi.org/10.3969/j.issn.1672-2337.2017.01.008
Ju, Y.W., Zhang, Y.: Research on ISAR image quality evaluation. Syst. Eng. Electronics 37(2), 297–303 (2015). https://doi.org/10.3969/j.issn.1001-506X.2015.02.11
Wang, M., Liu, Z., Song, Y.Q.: Research on LBP texture feature extraction based on noise immunity. Comput. Digital Eng. 48(11), 2739–2742 (2020). https://doi.org/10.3969/j.issn.1672-9722.2020.11.039
Han, H.T.: The study of accurate registration and related technology for spatial objects. Grad. School Natl. Univ. Defense Technol. 11, P15–P17 (2012)
Li, H.L., Ma, Y.F.: Target recognition method based on multi feature fusion and hybrid kernel SVM. J. Shenyang Univ. Technol. 40(4), 441–446 (2018). https://doi.org/10.7688/j.issn.1000-1646.2018.04.15
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Zhang, J. (2023). ISAR Image Quality Grade Evaluation of Space Targets Based on Fusion Feature. In: Kountchev, R., Nakamatsu, K., Wang, W., Kountcheva, R. (eds) Proceedings of the World Conference on Intelligent and 3-D Technologies (WCI3DT 2022). Smart Innovation, Systems and Technologies, vol 323. Springer, Singapore. https://doi.org/10.1007/978-981-19-7184-6_5
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DOI: https://doi.org/10.1007/978-981-19-7184-6_5
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