空间目标自适应光学图像椭圆部件检测

寇鹏; 智帅峰; 程耘; 刘永祥

doi:10.37188/CO.2021-0208

Volume 15 Issue 3

May 2022

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Chinese Optics > 2022 > 15(3): 454-463.

KOU Peng, ZHI Shuai-feng, CHENG Yun, LIU Yong-xiang. Detection of elliptical components in adaptive optical image of space target[J]. Chinese Optics, 2022, 15(3): 454-463. doi: 10.37188/CO.2021-0208

Citation:

KOU Peng, ZHI Shuai-feng, CHENG Yun, LIU Yong-xiang. Detection of elliptical components in adaptive optical image of space target[J]. Chinese Optics, 2022, 15(3): 454-463. doi: 10.37188/CO.2021-0208

KOU Peng, ZHI Shuai-feng, CHENG Yun, LIU Yong-xiang. Detection of elliptical components in adaptive optical image of space target[J]. Chinese Optics, 2022, 15(3): 454-463. doi: 10.37188/CO.2021-0208

Citation:

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Detection of elliptical components in adaptive optical image of space target

doi: 10.37188/CO.2021-0208

KOU Peng^{1, 2
,},
ZHI Shuai-feng^1
,,
CHENG Yun^1
,,
LIU Yong-xiang^{1
,
,}

1.
School of Electronic Science, University of Defense Science and Technology, Changsha 410073, China
2.
Xi’an Satellite Control Center, Xian 710600, China

Funds: Supported by National Natural Science Foundation of China (No. 61921001, No. 61801484)

More Information

Corresponding author: lyx_bible@sina.com
Received Date: 03 Dec 2021
Rev Recd Date: 04 Jan 2022
Accepted Date: 01 Mar 2022

Available Online: 01 Mar 2022

Publish Date: 20 May 2022

Abstract

Abstract

In order to identify the elliptical components of space target, an ellipse detection method based on adaptive optical image is proposed. Firstly, the RL(Richardson-Lucy) method is used to restore the adaptive optics image. Next, the Arc-Support Line Segments (ASLS) method is used to detect the ellipse of the restored image. To tackle the problems of “arc segment over segmentation” and “semantic information difference” caused by Canny edge extraction, an improved edge extraction algorithm based on Multiscale Combinatorial Grouping (MCG) is proposed. Finally, for some false ellipses produced by using verification methods such as goodness measurement, a variety of geometric constraint measurement are comprehensively used to effectively eliminate the false ellipse. The experimental results show that the detection error of ellipse center point, the semi-major axis error and the direction angle error are less than 3 pixels, 4 pixels and 3 degrees, respectively. When the overlap area threshold is 0.65, the accuracy rate of this algorithm is 85.7%, the recall rate is 93.3% and the F value is 0.893. Our method is better than the traditional ellipse detection algorithms.
- adaptive optical image,
- space target,
- elliptical part detection,
- arc-support segment,
- multiscale combinatorial grouping

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References(24)

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