Design and implement of a space-borne sun glint polarization parameter computing system

Li Yuhao; Ji Feng; Qiu Zhenwei; Chen Feinan; Li Zhuoran; Chi Gaojun; Chen Jingjing; Hu Yadong; Li Mengfan

doi:10.12086/oee.2024.240002

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Li Y H, Ji F, Qiu Z W, et al. Design and implement of a space-borne sun glint polarization parameter computing system[J]. Opto-Electron Eng, 2024, 51(4): 240002. doi: 10.12086/oee.2024.240002

Citation:

Li Y H, Ji F, Qiu Z W, et al. Design and implement of a space-borne sun glint polarization parameter computing system[J]. Opto-Electron Eng, 2024, 51(4): 240002. doi: 10.12086/oee.2024.240002

Design and implement of a space-borne sun glint polarization parameter computing system

1.
School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei, Anhui 230009, China
2.
Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China

Fund Project: Project supported by Equipment Pre-research Project (305090306), and Dreams Foundation of Jianghuai Advance Technology Center Fund (2023-ZM01K011)

More Information

^*Corresponding author: feinan123@aiofm.ac.cn

Received Date 23 January 2024

Revised Date 23 February 2024

Accepted Date 26 February 2024

Published Date 25 April 2024

Abstract

Abstract

Sun glint is a significant confounding factor in passive optical remote sensing images. To mitigate this issue, a polarizer is typically incorporated in front of the remote sensor, leveraging the linear polarization characteristics of sun glint. The suppression effects depend on the relative position of the sun and the remote sensor, as well as the directions of polarizers. In this paper, we introduce a novel onboard system for the real-time computation of Sun glint polarization parameters, devised specifically for a spaceborne atmospheric correction instrument. Utilizing three channel polarization images (at 0°, 60°, and 120°) in the 670 band of the spaceborne atmospheric correction, we calculate the sun glint parameters and compared them against the 6S radiation transfer model, excluding image pixels heavily influenced by the could. The system is implemented using the V5 series Field Programmable Gate Array (FPGA) as the hardware platform, and the High-Level Synthesis Tool (HLS) as the software platform. The performance of the system is verified through a simple laboratory experiment, which demonstrates a calculation deviation within 0.5°. In terms of computational efficiency, the system processes a 25x25 pixel dataset in 19.47281 ms using a 100 MHz clock, with the highest resource utilization rate reaching 41%.
- sun glint /
- field programmable gate array /
- polarization measurement /
- hardware acceleration

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References

[1]	Kay S, Hedley J D, Lavender S. Sun glint correction of high and low spatial resolution images of aquatic scenes: a review of methods for visible and near-infrared wavelengths[J]. Remote Sens, 2009, 1(4): 697−730. doi: 10.3390/rs1040697 CrossRef Google Scholar
[2]	Wang M H, Bailey S W. Correction of sun glint contamination on the SeaWiFS ocean and atmosphere products[J]. Appl Opt, 2001, 40(27): 4790−4798. doi: 10.1364/AO.40.004790 CrossRef Google Scholar
[3]	Mobley C D. Polarized reflectance and transmittance properties of windblown sea surfaces[J]. Appl Opt, 2015, 54(15): 4828−4849. doi: 10.1364/AO.54.004828 CrossRef Google Scholar
[4]	Hieronymi M. Polarized reflectance and transmittance distribution functions of the ocean surface[J]. Opt Express, 2016, 24(14): A1045−A1068. doi: 10.1364/OE.24.0A1045 CrossRef Google Scholar
[5]	Fougnie B, Frouin R, Lecomte P, et al. Reduction of skylight reflection effects in the above-water measurement of diffuse marine reflectance[J]. Appl Opt, 1999, 38(18): 3844−3856. doi: 10.1364/AO.38.003844 CrossRef Google Scholar
[6]	刘志刚, 周冠华. 太阳耀光的偏振分析[J]. 红外与毫米波学报, 2007, 26(5): 362−365. doi: 10.3321/j.issn:1001-9014.2007.05.011 CrossRef Google Scholar Liu Z G, Zhou G H. Polarization of sun glint[J]. J Infrared Millimeter Waves, 2007, 26(5): 362−365. doi: 10.3321/j.issn:1001-9014.2007.05.011 CrossRef Google Scholar
[7]	Zhao H J, Ji Z, Zhang Y, et al. Mid-infrared imaging system based on polarizers for detecting marine targets covered in sun glint[J]. Opt Express, 2016, 24(15): 16396−16409. doi: 10.1364/OE.24.016396 CrossRef Google Scholar
[8]	Avrahamy R, Milgrom B, Zohar M, et al. Improving object imaging with sea glinted background using polarization method: analysis and operator survey[J]. IEEE Trans Geosci Remote Sens, 2019, 57(11): 8764−8774. doi: 10.1109/TGRS.2019.2922827 CrossRef Google Scholar
[9]	张卫国. 海面太阳耀光背景下的偏振探测技术[J]. 中国光学, 2018, 11(2): 231−236. doi: 10.3788/co.20181102.0231 CrossRef Google Scholar Zhang W G. Application of polarization detection technology under the background of sun flare on sea surface[J]. Chin Opt, 2018, 11(2): 231−236. doi: 10.3788/co.20181102.0231 CrossRef Google Scholar
[10]	朱鹤骞, 曲宏松. 海面背景耀光的自适应抑制系统[J]. 光学学报, 2022, 42(12): 1201006. doi: 10.3788/AOS202242.1201006 CrossRef Google Scholar Zhu H Q, Qu H S. Adaptive suppression system of sea background flare[J]. Acta Opt Sin, 2022, 42(12): 1201006. doi: 10.3788/AOS202242.1201006 CrossRef Google Scholar
[11]	Wang M S, Qiu S, Jin W Q, et al. Automatic suppression method for water surface glints using a division of focal plane visible polarimeter[J]. Sensors, 2023, 23(17): 7446. doi: 10.3390/s23177446 CrossRef Google Scholar
[12]	于新宇. 星载偏振光谱相机sCMOS成像系统设计[D]. 桂林: 桂林电子科技大学, 2023: 1–67. Google Scholar Yu X Y. Design of sCMOS imaging system for space-borne polarization spectral camera[D]. Guilin: Guilin University of Electronic Technology, 2023: 1–67. Google Scholar
[13]	Born M, Wolf E. Principles of Optics[M]. 5th ed. New York: Pergamon Press, 1975. Google Scholar
[14]	Reda I, Andreas A. Corrigendum to “Solar position algorithm for solar radiation applications” [Solar Energy 76 (2004) 577–589][J]. Sol Energy, 2007, 81(6): 838. doi: 10.1016/j.solener.2007.01.003 CrossRef Google Scholar
[15]	Cox C, Munk W. Measurement of the roughness of the sea surface from photographs of the Sun’s glitter[J]. J Opt Soc Am, 1954, 44(11): 838−850. doi: 10.1364/JOSA.44.000838 CrossRef Google Scholar
[16]	Kotchenova S Y, Vermote E F. Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II. Homogeneous Lambertian and anisotropic surfaces[J]. Appl Opt, 2007, 46(20): 4455−4464. doi: 10.1364/AO.46.004455 CrossRef Google Scholar
[17]	陈震霆, 孙晓兵, 汪俊锋, 等. 近红外偏振辐射卫星数据的海洋耀光动态检测[J]. 遥感学报, 2019, 23(2): 215−229. doi: 10.11834/jrs.20197072 CrossRef Google Scholar Chen Z T, Sun X B, Wang J F, et al. Dynamic detection of ocean glint from near-infrared polarized radiation satellite data[J]. J Remote Sens, 2019, 23(2): 215−229. doi: 10.11834/jrs.20197072 CrossRef Google Scholar
[18]	Remer L A, Kaufman Y J, Tanré D, et al. The MODIS aerosol algorithm, products, and validation[J]. J Atmos Sci, 2005, 62(4): 947−973. doi: 10.1175/JAS3385.1 CrossRef Google Scholar
[19]	Toubbe B, Bailleul T, Deuze J L, et al. In-flight calibration of the POLDER polarized channels using the Sun's glitter[J]. IEEE Trans Geosci Remote Sens, 1999, 37(1): 513−524. doi: 10.1109/36.739104 CrossRef Google Scholar
[20]	Bicheron P, Leroy M, Hautecoeur O, et al. Enhanced discrimination of boreal forest covers with directional reflectances from the airborne polarization and directionality of Earth reflectances (POLDER) instrument[J]. J Geophys Res Atmos, 1997, 102(D24): 29517−29528. doi: 10.1029/97JD01330 CrossRef Google Scholar
[21]	钱鸿鹄. 多角度偏振成像仪实验室全视场偏振定标[D]. 合肥: 中国科学技术大学, 2017: 1–100. Google Scholar Qian H H. Laboratory full field of view polarization calibration of directional polarimetric camera[D]. Hefei: University of Science and Technology of China, 2017: 1–100. Google Scholar
[22]	侯梦雨, 李正强, 谢一凇, 等. 国产卫星多角度偏振传感器的光谱特征云检测方法研究[J]. 大气与环境光学学报, 2022, 17(6): 598−612. doi: 10.3969/j.issn.1673-6141.2022.06.002 CrossRef Google Scholar Hou M Y, Li Z Q, Xie Y S, et al. Research on spectral feature cloud detection method of directional polarimetric camera on Chinese satellite[J]. J Atmos Environ Opt, 2022, 17(6): 598−612. doi: 10.3969/j.issn.1673-6141.2022.06.002 CrossRef Google Scholar
[23]	程前, 高欣健, 高隽, 等. 基于邻域约束的大气偏振模式生成网络[J]. 光电工程, 2022, 49(6): 210423. doi: 10.12086/oee.2022.210423 CrossRef Google Scholar Cheng Q, Gao X J, Gao J, et al. A generative method for atmospheric polarization modelling based on neighborhood constraint[J]. Opto-Electron Eng, 2022, 49(6): 210423. doi: 10.12086/oee.2022.210423 CrossRef Google Scholar
[24]	Kastner R, Matai J, Neuendorffer S. Parallel programming for FPGAs[Z]. arXiv: 1805.03648, 2018. https://doi.org/10.48550/arXiv.1805.03648. Google Scholar
[25]	Volder J E. The CORDIC trigonometric computing technique[J]. IRE Trans Electron Comput, 1959, EC-8(3): 330−334. doi: 10.1109/TEC.1959.5222693 CrossRef Google Scholar

Overview

Overview

In passive optical remote sensing, the phenomenon of sun glint presents a substantial challenge in the acquisition and processing of high-quality images. Sun glint is the specular reflection from surfaces like water. Water bodies are characterized by low reflectivity, which classifies them as dark targets within the context of remote sensing. The radiation of sun glint is usually dozens of times higher than the target's radiation, and is easy to cause sensor saturation, leading to serious interference with the detection target. The current methods for suppressing solar glint in remote sensing imagery are mainly conducted on the ground. However, these approaches are often reactive rather than preventive and may not be suitable for real-time applications. According to Fresnel's law, the vertical component of sun glint is usually greater than the parallel component. In space, to mitigate this issue, a polarizer is typically incorporated in front of the remote sensor, leveraging the linear polarization characteristics of sun glint. The suppression effects depend on the relative position of the sun and the remote sensor, as well as the directions of polarizers. With the rapid development of satellite technology, the traditional method of installing parallel linear polarizers is difficult to meet our requirements. So, to suppress sun glint accurately and timely, we introduce a novel onboard system for the real-time computation of Sun glint polarization parameters, devised specifically for a spaceborne atmospheric correction instrument. Utilizing three channel polarization images (at 0°, 60°, and 120°) in the 670 nm band of the space-borne atmospheric correction, we calculate the sun glint parameters and compare them against the 6S radiation transfer model, excluding image pixels heavily influenced by the cloud. The system is implemented using the V5 series Field Programmable Gate Array (FPGA) as the hardware platform, and the High-Level Synthesis Tool (HLS) as the software platform. By utilizing the Cordic algorithm, converting data to appropriate datatypes, and implementing pipeline unrolling methods, we achieve a balanced trade-off between speed and resource allocation. A simple experiment was built to verify the system in the laboratory. The experiments performed that the calculation deviation is within 0.5°, calculating the 25 pixels×25 pixels data costs 19.47281 ms in 100 MHz clock, and the highest resource utilization rate accounts for 41%, meeting the requirements of the accuracy, real-time performance, and resource consumption.