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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2000695


Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation


Author(s):  Xiao YANG, Chun YIN, , Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU

Affiliation(s):  School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; more

Corresponding email(s):   yinchun.86416@163.com, chunyin@uestc.edu.cn

Key Words:  Hypervelocity impact damage, Defect detection, Gaussian mixture model, Image segmentation


Xiao YANG, Chun YIN, , Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU. Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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author="Xiao YANG, Chun YIN, , Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU",
journal="Frontiers of Information Technology & Electronic Engineering",
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number="-1",
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year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000695"
}

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%T Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation
%A Xiao YANG
%A Chun YIN
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%A Sara DADRAS
%A Guangyu LEI
%A Xutong TAN
%A Gen QIU
%J Journal of Zhejiang University SCIENCE C
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%D 1998
%I Zhejiang University Press & Springer
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A1 - Xutong TAN
A1 - Gen QIU
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DOI - 10.1631/FITEE.2000695


Abstract: 
To detect spacecraft damage caused by hypervelocity impact, we propose an advanced spacecraft defect extraction algorithm based on infrared imaging detection. The gaussian mixture model is used to classify the temperature change characteristics in the sampled data of the infrared video stream and reconstruct the image to obtain the infrared reconstructed image (IRRI) reflecting the defect characteristics. The designed segmentation objective function is used to ensure the effectiveness of image segmentation results for noise removal and detail preservation, while taking into account the complexity of IRRI, that is, the required trade-offs are different. Therefore, a multi-objective optimization algorithm is introduced to achieve balance between detail retention and noise removal, and the MOEA/D algorithm is used for optimization to ensure the accuracy of damage segmentation. The experimental results of the algorithm verify the effectiveness of the study.

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