基于光场理论的场景仿真
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摘要
成像系统仿真对光学遥感器的论证、设计和在轨性能预估具有重要意义。场景作为遥感的对象,其特性的表征和模拟对仿真结果有直接影响。场景特性难以全面表征,针对光学遥感及其应用最为关键的几何、光谱和辐射特性,提出一种基于光场理论的数字场景仿真方法。以包含空间坐标、方向、波长、强度的全光函数作为数字场景仿真的表征参数,建立了涵盖太阳直射、天空漫射和背景反射等因素的数字场景入射辐照度场模型,以及考虑方向反射特性的数字场景出射辐亮度场模型,并基于简单场景对模型进行分析和验证。该方法能够为成像系统仿真及新型载荷研制提供包含多种特性的数字场景模型。
The simulation of the imaging system is very important to the demonstration, design and performance forecast of the optical remote sensing detector. As the remote sensing object, characterization and modelling of the scene will affect the simulation results directly. Aiming at the crucial geometry,spectrum and radiance characters, a digital scene modelling method based on the optical field theory was proposed. Using the plenoptic function comprised of geometrical coordinates, direction, spectrum and intensity, irradiance field onto the scene surface was modelled including the direct solar radiance, skylight radiance and reflected background radiance. With directional reflectance character of the surface, radiance field leaving the scene surface was also modelled. A simple small 3D scene was created to validate these models. The proposed method will provide digital scene model with multiple characters for the imaging system simulation and the new-style detector development.
The simulation of the imaging system is very important to the demonstration, design and performance forecast of the optical remote sensing detector. As the remote sensing object, characterization and modelling of the scene will affect the simulation results directly. Aiming at the crucial geometry,spectrum and radiance characters, a digital scene modelling method based on the optical field theory was proposed. Using the plenoptic function comprised of geometrical coordinates, direction, spectrum and intensity, irradiance field onto the scene surface was modelled including the direct solar radiance, skylight radiance and reflected background radiance. With directional reflectance character of the surface, radiance field leaving the scene surface was also modelled. A simple small 3D scene was created to validate these models. The proposed method will provide digital scene model with multiple characters for the imaging system simulation and the new-style detector development.
引文
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[2]Grau E,Gastellu-Etchegorry J P.Radiative transfer modeling in the Earth-Atmosphere system with DART model[J].Remote Sens Environ,2013,139:149-170.
[3]Borner A.Simulation opto-electronic systems for remote sensing with SENSOR[C]//SPIE,2003,4881:472-483.
[4]Ambeau B L,Gerace A D,Montanaro M,et al.The characterization of a DIRSIG simulation environment to support the inter-calibration of spaceborne sensors[C]//SPIE,2016,99720M:1-9.
[5]Xiao Qing,Li Min.A study on the transformation of airborne remote sensing image to spaceborne remote sensing image[J].Journal of Beijing Normal University(Natural Sciences),2007,43(3):234-240.(in Chinese)肖青,李敏.机载光学图像至卫星光学图像转换方法研究[J].北京师范大学学报(自然科学版),2007,43(3):234-240.
[6]Liu Xiao,Yi Weining,Qiao Yanli,et al.Satellite borne optical remote sensor imaging simulation based on lowaltitude remote sensing system[J].Infrared and Laser Engineering,2014,43(1):217-225.(in Chinese)刘晓,易维宁,乔延利,等.基于低空遥感系统的星载光学遥感器成像仿真[J].红外与激光工程,2014,43(1):217-225.
[7]Borner A,Wiest L,Keller P,et al.SENSOR:a tool for the simulation of hyperspectral remote sensing systems[J].ISPRS Photog Remote Sens,2001,55:299-312.
[8]Goodenough A A,Brown S D.DIRSIG 5:core design and implementation[C]//SPIE,2012,83900H:1-9.
[9]Gastellu-Etchegorry J P,Martin E,Gascon F.DART:a 3D model for simulating satellite images and studying surface radiation budget[J].Int J Remote Sens,2004,25(1):73-96.
[10]Landy M,Movshon J A.Computational Models of Visual Processing[M].Cambridge:MIT Press,1991:3-20.
[11]Schott J R.Remote Sensing:the Image Chain Approach[M].New York:Oxford University Press,2007.
[12]Wang Gang,Yu Bingxi.Study on scientific visualization of earth remote sensing based on imagery simulation[J].Journal of System Simulation,2002,14(6):756-760.(in Chinese)王刚,俞秉熙.基于图像仿真的对地遥感过程科学可视化研究[J].系统仿真学报,2002,14(6):756-760.
[13]Xiao Liang,Wu Huizhong,Liu Yang,et al.Modeling and simulation of digital scene image synthesis[J].Acta Armamentarii,2005,26(1):113-117.(in Chinese)肖亮,吴慧中,刘扬,等.数字景像匹配图模拟生成的建模与仿真[J].兵工学报,2005,26(1):113-117.
[14]Schott J R,Kuo D,Brown S,et al.Prediction of observed image spectra using synthetic image generation models[C]//SPIE,1997,3118:81-93.
[15]Ma Xiaoshan,Meng Xin,Yang Zhen,et al.Analysis and modeling of atmosphere influence on space-based optical remote sensing imaging simulation[J].Infrared and Laser Engineering,2014,43(1):226-231.(in Chinese)马晓珊,孟新,杨震,等.天基光学遥感成像仿真中大气影响分析与模拟[J].红外与激光工程,2014,43(1):226-231.
[16]Rengarajan R,Schott J R.Modeling of forest canopy BRDF using DIRSIG[C]//SPIE,2016,98401F:1-14.
[2]Grau E,Gastellu-Etchegorry J P.Radiative transfer modeling in the Earth-Atmosphere system with DART model[J].Remote Sens Environ,2013,139:149-170.
[3]Borner A.Simulation opto-electronic systems for remote sensing with SENSOR[C]//SPIE,2003,4881:472-483.
[4]Ambeau B L,Gerace A D,Montanaro M,et al.The characterization of a DIRSIG simulation environment to support the inter-calibration of spaceborne sensors[C]//SPIE,2016,99720M:1-9.
[5]Xiao Qing,Li Min.A study on the transformation of airborne remote sensing image to spaceborne remote sensing image[J].Journal of Beijing Normal University(Natural Sciences),2007,43(3):234-240.(in Chinese)肖青,李敏.机载光学图像至卫星光学图像转换方法研究[J].北京师范大学学报(自然科学版),2007,43(3):234-240.
[6]Liu Xiao,Yi Weining,Qiao Yanli,et al.Satellite borne optical remote sensor imaging simulation based on lowaltitude remote sensing system[J].Infrared and Laser Engineering,2014,43(1):217-225.(in Chinese)刘晓,易维宁,乔延利,等.基于低空遥感系统的星载光学遥感器成像仿真[J].红外与激光工程,2014,43(1):217-225.
[7]Borner A,Wiest L,Keller P,et al.SENSOR:a tool for the simulation of hyperspectral remote sensing systems[J].ISPRS Photog Remote Sens,2001,55:299-312.
[8]Goodenough A A,Brown S D.DIRSIG 5:core design and implementation[C]//SPIE,2012,83900H:1-9.
[9]Gastellu-Etchegorry J P,Martin E,Gascon F.DART:a 3D model for simulating satellite images and studying surface radiation budget[J].Int J Remote Sens,2004,25(1):73-96.
[10]Landy M,Movshon J A.Computational Models of Visual Processing[M].Cambridge:MIT Press,1991:3-20.
[11]Schott J R.Remote Sensing:the Image Chain Approach[M].New York:Oxford University Press,2007.
[12]Wang Gang,Yu Bingxi.Study on scientific visualization of earth remote sensing based on imagery simulation[J].Journal of System Simulation,2002,14(6):756-760.(in Chinese)王刚,俞秉熙.基于图像仿真的对地遥感过程科学可视化研究[J].系统仿真学报,2002,14(6):756-760.
[13]Xiao Liang,Wu Huizhong,Liu Yang,et al.Modeling and simulation of digital scene image synthesis[J].Acta Armamentarii,2005,26(1):113-117.(in Chinese)肖亮,吴慧中,刘扬,等.数字景像匹配图模拟生成的建模与仿真[J].兵工学报,2005,26(1):113-117.
[14]Schott J R,Kuo D,Brown S,et al.Prediction of observed image spectra using synthetic image generation models[C]//SPIE,1997,3118:81-93.
[15]Ma Xiaoshan,Meng Xin,Yang Zhen,et al.Analysis and modeling of atmosphere influence on space-based optical remote sensing imaging simulation[J].Infrared and Laser Engineering,2014,43(1):226-231.(in Chinese)马晓珊,孟新,杨震,等.天基光学遥感成像仿真中大气影响分析与模拟[J].红外与激光工程,2014,43(1):226-231.
[16]Rengarajan R,Schott J R.Modeling of forest canopy BRDF using DIRSIG[C]//SPIE,2016,98401F:1-14.