Full Text:  <298>

Summary:  <6>

CLC number: V447

On-line Access: 2023-01-21

Received: 2022-03-04

Revision Accepted: 2023-01-21

Crosschecked: 2022-06-08

Cited: 0

Clicked: 237

Citations:  Bibtex RefMan EndNote GB/T7714


Hao Wang


Huajian DENG


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Frontiers of Information Technology & Electronic Engineering 

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Camera calibration method for an infrared horizon sensor with a large field of view

Author(s):  Huajian DENG, Hao WANG, Xiaoya HAN, Yang LIU, Zhonghe JIN

Affiliation(s):  Micro-Satellite Research Center, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):  roger@zju.edu.cn

Key Words:  Infrared horizon sensor; Ultra-field infrared camera; Camera calibration

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Huajian DENG, Hao WANG, Xiaoya HAN, Yang LIU, Zhonghe JIN. Camera calibration method for an infrared horizon sensor with a large field of view[J]. Frontiers of Information Technology & Electronic Engineering , 2023, 24(9): 141-153.

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%T Camera calibration method for an infrared horizon sensor with a large field of view
%A Huajian DENG
%A Xiaoya HAN
%A Yang LIU
%A Zhonghe JIN
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%I Zhejiang University Press & Springer

T1 - Camera calibration method for an infrared horizon sensor with a large field of view
A1 - Huajian DENG
A1 - Hao WANG
A1 - Xiaoya HAN
A1 - Yang LIU
A1 - Zhonghe JIN
J0 - Frontiers of Information Technology & Electronic Engineering
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EP - 153
%@ 1869-1951
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PB - Zhejiang University Press & Springer
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Inadequate geometric accuracy of cameras is the main constraint to improving the precision of infrared horizon sensors with a large field of view (FOV). An enormous FOV with a blind area in the center greatly limits the accuracy and feasibility of traditional geometric calibration methods. A novel camera calibration method for infrared horizon sensors is presented and validated in this paper. Three infrared targets are used as control points. The camera is mounted on a rotary table. As the table rotates, these control points will be evenly distributed in the entire FOV. Compared with traditional methods that combine a collimator and a rotary table which cannot effectively cover a large FOV and require harsh experimental equipment, this method is easier to implement at a low cost. A corresponding three-step parameter estimation algorithm is proposed to avoid precisely measuring the positions of the camera and the control points. Experiments are implemented with 10 infrared horizon sensors to verify the effectiveness of the calibration method. The results show that the proposed method is highly stable, and that the calibration accuracy is at least 30% higher than those of existing methods.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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