IEICE TRANSACTIONS on Information
Algorithm-Hardware Co-Design of Real-Time Edge Detection for Deep-Space Autonomous Optical Navigation
Summary :
Optical navigation (OPNAV) is the use of the on-board imaging data to provide a direct measurement of the image coordinates of the target as navigation information. Among the optical observables in deep-space, the edge of the celestial body is an important feature that can be utilized for locating the planet centroid. However, traditional edge detection algorithms like Canny algorithm cannot be applied directly for OPNAV due to the noise edges caused by surface markings. Moreover, due to the constrained computation and energy capacity on-board, light-weight image-processing algorithms with less computational complexity are desirable for real-time processing. Thus, to fast and accurately extract the edge of the celestial body from high-resolution satellite imageries, this paper presents an algorithm-hardware co-design of real-time edge detection for OPNAV. First, a light-weight edge detection algorithm is proposed to efficiently detect the edge of the celestial body while suppressing the noise edges caused by surface markings. Then, we further present an FPGA implementation of the proposed algorithm with an optimized real-time performance and resource efficiency. Experimental results show that, compared with the traditional edge detection algorithms, our proposed one enables more accurate celestial body edge detection, while simplifying the hardware implementation.
- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.10 pp.2047-2058
- Publication Date
- 2020/10/01
- Publicized
- 2020/06/15
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2020PCP0002
- Type of Manuscript
- Special Section PAPER (Special Section on Picture Coding and Image Media Processing)
- Category
Authors
Hao XIAO
HeFei University of Technology,Chengdu
Yanming FAN
Nanjing University of Aeronautics and Astronautics
Fen GE
Chengdu,Nanjing University of Aeronautics and Astronautics
Zhang ZHANG
HeFei University of Technology
Xin CHENG
HeFei University of Technology
Keyword
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Hao XIAO, Yanming FAN, Fen GE, Zhang ZHANG, Xin CHENG, "Algorithm-Hardware Co-Design of Real-Time Edge Detection for Deep-Space Autonomous Optical Navigation" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 10, pp. 2047-2058, October 2020, doi: 10.1587/transinf.2020PCP0002.
Abstract: Optical navigation (OPNAV) is the use of the on-board imaging data to provide a direct measurement of the image coordinates of the target as navigation information. Among the optical observables in deep-space, the edge of the celestial body is an important feature that can be utilized for locating the planet centroid. However, traditional edge detection algorithms like Canny algorithm cannot be applied directly for OPNAV due to the noise edges caused by surface markings. Moreover, due to the constrained computation and energy capacity on-board, light-weight image-processing algorithms with less computational complexity are desirable for real-time processing. Thus, to fast and accurately extract the edge of the celestial body from high-resolution satellite imageries, this paper presents an algorithm-hardware co-design of real-time edge detection for OPNAV. First, a light-weight edge detection algorithm is proposed to efficiently detect the edge of the celestial body while suppressing the noise edges caused by surface markings. Then, we further present an FPGA implementation of the proposed algorithm with an optimized real-time performance and resource efficiency. Experimental results show that, compared with the traditional edge detection algorithms, our proposed one enables more accurate celestial body edge detection, while simplifying the hardware implementation.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020PCP0002/_p
Copy
@ARTICLE{e103-d_10_2047,
author={Hao XIAO, Yanming FAN, Fen GE, Zhang ZHANG, Xin CHENG, },
journal={IEICE TRANSACTIONS on Information},
title={Algorithm-Hardware Co-Design of Real-Time Edge Detection for Deep-Space Autonomous Optical Navigation},
year={2020},
volume={E103-D},
number={10},
pages={2047-2058},
abstract={Optical navigation (OPNAV) is the use of the on-board imaging data to provide a direct measurement of the image coordinates of the target as navigation information. Among the optical observables in deep-space, the edge of the celestial body is an important feature that can be utilized for locating the planet centroid. However, traditional edge detection algorithms like Canny algorithm cannot be applied directly for OPNAV due to the noise edges caused by surface markings. Moreover, due to the constrained computation and energy capacity on-board, light-weight image-processing algorithms with less computational complexity are desirable for real-time processing. Thus, to fast and accurately extract the edge of the celestial body from high-resolution satellite imageries, this paper presents an algorithm-hardware co-design of real-time edge detection for OPNAV. First, a light-weight edge detection algorithm is proposed to efficiently detect the edge of the celestial body while suppressing the noise edges caused by surface markings. Then, we further present an FPGA implementation of the proposed algorithm with an optimized real-time performance and resource efficiency. Experimental results show that, compared with the traditional edge detection algorithms, our proposed one enables more accurate celestial body edge detection, while simplifying the hardware implementation.},
keywords={},
doi={10.1587/transinf.2020PCP0002},
ISSN={1745-1361},
month={October},}
Copy
TY - JOUR
TI - Algorithm-Hardware Co-Design of Real-Time Edge Detection for Deep-Space Autonomous Optical Navigation
T2 - IEICE TRANSACTIONS on Information
SP - 2047
EP - 2058
AU - Hao XIAO
AU - Yanming FAN
AU - Fen GE
AU - Zhang ZHANG
AU - Xin CHENG
PY - 2020
DO - 10.1587/transinf.2020PCP0002
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2020
AB - Optical navigation (OPNAV) is the use of the on-board imaging data to provide a direct measurement of the image coordinates of the target as navigation information. Among the optical observables in deep-space, the edge of the celestial body is an important feature that can be utilized for locating the planet centroid. However, traditional edge detection algorithms like Canny algorithm cannot be applied directly for OPNAV due to the noise edges caused by surface markings. Moreover, due to the constrained computation and energy capacity on-board, light-weight image-processing algorithms with less computational complexity are desirable for real-time processing. Thus, to fast and accurately extract the edge of the celestial body from high-resolution satellite imageries, this paper presents an algorithm-hardware co-design of real-time edge detection for OPNAV. First, a light-weight edge detection algorithm is proposed to efficiently detect the edge of the celestial body while suppressing the noise edges caused by surface markings. Then, we further present an FPGA implementation of the proposed algorithm with an optimized real-time performance and resource efficiency. Experimental results show that, compared with the traditional edge detection algorithms, our proposed one enables more accurate celestial body edge detection, while simplifying the hardware implementation.
ER -
English
