多目标无人机微型凝视高光谱成像仪辐射校正
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摘要
微型凝视高光谱成像仪可以同时获取两个空间维度和一个光谱维度图像,且仅记录整个高光谱图像的外方位元素而不是记录每一帧图像的外方位元素,避免了扫描时的几何不稳定性,有效解决了小型线扫式高光谱成像仪成像几何变形大的问题,适合于姿态不稳定小型无人机负载平台。目前,研究大多集中于线扫式高光谱成像仪辐射校正方法。凝视型高光谱成像仪应用时间较短,国内外没有较为成熟的数据处理研究,阻碍了无人机微型凝视高光谱成像系统的应用。本文研究了无人机载微型凝视高光谱成像仪辐射响应线性度特性和辐射响应变异性的校正方法,并定量评估该方法的有效性。结果表明,辐射响应变异性校正前,高光谱图像存在明显的渐晕效应和条带现象,校正后,不同波段中像元的辐射响应变异系数显著下降,且渐晕效应和图像条带明显减少。本文提出了基于多目标辐射定标方法,并通过比较定标后的高光谱图像光谱与地面光谱仪实测地物光谱来验证辐射定标的精度。结果表明,多目标辐射定标方法的定标结果表现出更好的效果,特别对于近红外波段,与光谱仪实测的地物反射率差异较小。
Mini snapshot high spectrometer can get images with two spatial dimensions and one spectral dimension at the same time,and the exterior orientation elements of the whole hyper spectral images instead of each frame,which can avoid geometric instability when scanning and can solve the large geometric deformation problem of push broom high spectrometer. So mini snapshot high spectrometer is suitable for small unmanned aerial vehicle platform. At present,the research mainly focus on radiometric correction of push broom high spectrometer. The application time of snapshot high spectrometer is relatively short,and the research on image processing is not adequate which has hampered wider use of this system. In this paper,the radiation response linearity and radiation response variability of mini snapshot high spectrometer load on UAV have been studied. At the same time,the correction method of radiation response variability has been studied,and the effectiveness of this method is assessed. The results show that before radiation response variability correction,there are the obvious vignetting effect and banding phenomenon on hyperspectral images,the radiation response variability coefficient after correction declines significantly,and the vignetting effect and banding phenomenon obviously decrease. The algorithm of multi-target radiometric calibration has been researched on,and the radiometric calibration accuracy is verified according to comparing the hyperspectral image spectrum calibrated with measured spectrum by ASD spectrometer. The results show that the radiometric calibration effect of multi target radiometric calibration algorithm is better,especially for near infrared band,the reflectance after calibrating is almost same as one measured by ASD spectrometer.
Mini snapshot high spectrometer can get images with two spatial dimensions and one spectral dimension at the same time,and the exterior orientation elements of the whole hyper spectral images instead of each frame,which can avoid geometric instability when scanning and can solve the large geometric deformation problem of push broom high spectrometer. So mini snapshot high spectrometer is suitable for small unmanned aerial vehicle platform. At present,the research mainly focus on radiometric correction of push broom high spectrometer. The application time of snapshot high spectrometer is relatively short,and the research on image processing is not adequate which has hampered wider use of this system. In this paper,the radiation response linearity and radiation response variability of mini snapshot high spectrometer load on UAV have been studied. At the same time,the correction method of radiation response variability has been studied,and the effectiveness of this method is assessed. The results show that before radiation response variability correction,there are the obvious vignetting effect and banding phenomenon on hyperspectral images,the radiation response variability coefficient after correction declines significantly,and the vignetting effect and banding phenomenon obviously decrease. The algorithm of multi-target radiometric calibration has been researched on,and the radiometric calibration accuracy is verified according to comparing the hyperspectral image spectrum calibrated with measured spectrum by ASD spectrometer. The results show that the radiometric calibration effect of multi target radiometric calibration algorithm is better,especially for near infrared band,the reflectance after calibrating is almost same as one measured by ASD spectrometer.
引文
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[15]韩杰,谢勇.星载多相机拼接成像传感器在轨辐射定标方法[J].测绘学报,2017,46(11),1830-1840.
[16]张过,李立涛.遥感25号无场化相对辐射定标[J].测绘学报,2017,46(8):1009-1016.
[2] ZHANG C,KOVACS J M. The application of small unmanned aerial systems for precision agriculture:a review[J]. Precision Agriculture,2012,13(6):693-712.
[3] HABIB A,HAN Y,XIONG W,et al. Automated orthorectification of UAV-based hyperspectral data over an agricultural field using frame RGB imagery[J]. Remote Sensing,2016,8(10):796.
[4] SCHIMA R,MOLLENHAUER H,GRENZDORFFER G,et al. Imagine all the plants:evaluation of a light-field camera for on-site crop growth monitoring[J]. Remote Sensing,2016,8(10):823.
[5] FENG W,ZHANG H Y,ZHANG Y S,et al. Remote detection of canopy leaf nitrogen concentration in winter wheat by using water resistance vegetation indices from in-situ hyperspectral data[J]. Field Crops Research,2016,198:238-246.
[6] CONTIU S,GROZA A. Improving remote sensing crop classification by argumentation-based conflict resolution in ensemble learning[J]. Expert Systems with Applications,2016,64:269-286.
[7]童庆禧,张兵,张立福.中国高光谱遥感的前沿与进展[J].遥感学报,2016,20(5):689-707.
[8]张春雷,向阳.基于大气吸收带的超光谱成像仪光谱定标技术研究[J].光谱学与光谱分析,2012,32(1):268-272.
[9]毕凯,李英成,丁晓波,等.轻型无人机航摄技术现状及发展趋势[J].测绘通报,2015(3):27-31.
[10]林宗坚,解雯雯,苏国中.宽角相机低空航测精度分析[J].测绘学报,2014,43(10):991-997.
[11] KARPEL N,SCHECHNER Y Y. Portable polarimetric underwater imaging system with a linear response[J].Proc Spie,2004,5432:106-115.
[12] ZHENG Y,YU J,KANG S B,et al. Single-image vignetting correction using radial gradient symmetry[C]∥2008 IEEE Conference on Computer Vision and Pattern Recognition.[S.l.]:IEEE,2008.
[13] GOLDMAN D B,CHEN J H. Vignette and exposure calibration and compensation[C]∥Tenth IEEE International Conference on Computer Vision.[S. l.]:IEEE,2005.
[14]张志杰,张浩,常玉光,等.Landsat系列卫星光学遥感辐射定标方法综述[J].遥感学报,2015,19(5):719-732.
[15]韩杰,谢勇.星载多相机拼接成像传感器在轨辐射定标方法[J].测绘学报,2017,46(11),1830-1840.
[16]张过,李立涛.遥感25号无场化相对辐射定标[J].测绘学报,2017,46(8):1009-1016.