| 多光谱低空遥感图像光照辐射度校正 |
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| 引用本文： | 汪沛,张俊雄,兰玉彬,周志艳,罗锡文.多光谱低空遥感图像光照辐射度校正[J].农业工程学报,2014,30(19):199-206. |
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| 作者姓名： | 汪沛 张俊雄 兰玉彬 周志艳 罗锡文 |
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| 作者单位： | 1. 华南农业大学工程学院，广州 510642; 华南农业大学南方农业机械与装备关键技术教育部重点实验室，广州 510642
2. 中国农业大学工学院,北京,100083 |
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| 基金项目： | 十二五国家863计划项目（SS2013AA100303，2012AA101901-3） |
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| 摘 要： | 为了提高受云层阴影影响的遥感图像的信息提取准确度,该文以水稻小区试验过程中为进行氮素水平检测而采集的低空机载高分辨率多光谱遥感图像为对象,对受云层阴影影响的高光谱图像进行光谱校正,从而提高氮素水平检测的精度。试验中采用机载的双摄像机同步采集可见光和近红外的水稻遥感图像,并将两摄像机的图像进行几何校正后合成得到彩红外(color infrared,CIR)光谱图像;同时在图像采集区域布置3块不同反射率的1.2 m×1.2 m标定靶,利用便携式光谱仪测定标定靶的反射光谱曲线,并统计标定靶在图像中各通道的亮度均值。以标定靶在晴天无云和有云图像中的亮度值为节点,对G、R和近红外(near infrared,NIR)通道分别建立分段的线性变换模型进行校正。为验证校正精度,在遥感图像中分别选择大田水稻、小区试验田块和裸地3个不同区域的图像的G、R和NIR通道像素亮度均值及归一化植被指数(normalized differential vegetation index,NDVI)作为评价指标。试验结果表明,和传统的整体线性变换相比,采用分段线性变换校正具有较高精度,G、R和NIR通道校正后的平均误差为8.6%,9.1%和11.7%,NDVI平均误差为11.5%,有效提高了阴影条件下的遥感图像的信息提取精度,提高了受云层影响遥感图像的利用率。研究为低空遥感的图像校正提供了参考。
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| 关 键 词： | 遥感 监测 图像处理 多光谱图像 光谱校正 光照辐射度 氮素监测 去云 |
| 收稿时间： | 2014/2/26 0:00:00 |
| 修稿时间： | 2014/9/26 0:00:00 |
Radiometric calibration of low altitude multispectral remote sensing images |
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| Wang Pei,Zhang Junxiong,Lan Yubin,Zhou Zhiyan and Luo Xiwen.Radiometric calibration of low altitude multispectral remote sensing images[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(19):199-206. |
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| Authors: | Wang Pei Zhang Junxiong Lan Yubin Zhou Zhiyan and Luo Xiwen |
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| Institution: | 1. College of Engineering, South China Agricultural University, Guangzhou 510642, China2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China;3. College of Engineering, China Agricultural University, Beijing 100083, China;1. College of Engineering, South China Agricultural University, Guangzhou 510642, China2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China;1. College of Engineering, South China Agricultural University, Guangzhou 510642, China2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China;1. College of Engineering, South China Agricultural University, Guangzhou 510642, China2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China |
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| Abstract: | |
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| Keywords: | remote sensing monitoring image processing multispectral image spectral calibration radiometric nitrogen detection cloud removal |
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