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推扫式双相机高光谱成像系统设计与试验

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高光谱成像(HSI)是一种应用日益广泛的无损检测技术,HSI数据同时包含样品的空间与光谱信息,可用于表征物质性质的空间分布特征或快速获取内部异质性较强样品的性质特征.但受传感器以及光学器件材料性能和成本制约,单个高光谱相机仅能覆盖有限的光谱波段范围,但物质性质信息往往蕴含在不同波段的光谱中,导致使用单个相机监测物质性质的种类和精度受限.因此本文设计并搭建了一套推扫式双相机HSI系统,该系统在波段400~1 000 nm和1 000~2 500 nm的实际最小分辨率为140.31 μm和222.72 µm,光谱分辨率分别为2.8 nm和12 nm,共计有464个工作波段.使用C#和XAML语言编写了用户友好型数据采集软件MySpec HSI,可实现双相机HSI数据的便捷采集.为评估所搭建的推扫式双相机HSI系统性能,利用该系统对一组玉米样品冠层进行成像,建立了玉米冠层叶片生物量、叶绿素含量和全氮含量的偏最小二乘回归监测模型.基于可见近红外单相机的生物量、叶绿素含量和全氮含量监测模型的R2C分别为0.567、0.773和0.653,RMSEP分别为0.52 g、2.5和0.301%;基于短波红外单相机的生物量、叶绿素含量和全氮含量监测模型的R2C分别为0.566、0.719和0.652,RMSEP分别为0.53 g、2.8和0.309%,除叶绿素含量监测的可见近红外波段表现出略微优势外,其他情况二者的监测精度相当,表明基于任一单相机HSI均可实现玉米冠层叶片生物量、叶绿素含量和全氮含量监测.而基于双相机的生物量、叶绿素含量和全氮含量监测模型的R2C分别高达0.670、0.822和0.683,与单相机模型相比提升幅度最高分别为18%、14%和5%,RMSEP分别低至0.46 g、2.0和0.258%,与单相机模型相比降低幅度最高分别为13%、27%和17%,表明融合双相机HSI数据能有效提高玉米冠层叶片性质的监测精度.
Design and Test of Push-Broom Dual-camera Hyperspectral Imaging System
Hyperspectral imaging(HSI)is an increasingly utilized non-destructive testing technology that simultaneously captures spatial and spectral information of samples,making it suitable for characterizing the spatial distribution of material properties or quickly obtaining the properties of highly heterogeneous samples.However,due to the limitations imposed by sensor and optical material performance and cost,a single hyperspectral camera can only cover a limited spectral range,while the material property information is often distributed across different spectral bands.This limits the types and accuracy of material property monitoring when using a single camera.A push-broom dual-camera HSI system was designed and constructed.The system achieved a minimum spatial resolution of 140.31 pm and 222.72 pm in the spectral ranges of 400~1 000 nm and 1 000~2 500 nm,respectively,with spectral resolutions of 2.8 nm and 12 nm,covering a total of 464 working bands.A user-friendly data acquisition software,MySpec HSI,was developed by using C#and XAML to facilitate convenient dual-camera HSI data collection.To evaluate the performance of the constructed push-broom dual-camera HSI system,it was used to image the canopy of maize samples,and partial least squares regression models were established for monitoring biomass,chlorophyll,and total nitrogen content in maize canopy leaves.The R2 values of the biomass,chlorophyll,and total nitrogen content monitoring models based on a visible-near-infrared(VNIR)single camera were 0.567,0.773,and 0.653,respectively,with RMSEP values of 0.52 g,2.5,and 0.301% .For the shortwave-infrared(SWIR)single camera,the RC2 values were 0.566,0.719,and 0.652,with RMSEP values of 0.53 g,2.8,and 0.309% .Except for a slight advantage in chlorophyll monitoring by the VNIR band,the monitoring accuracy of the other properties was comparable between the two bands,indicating that either single-camera HSI can achieve biomass,chlorophyll,and nitrogen content monitoring of maize canopy leaves.However,the dual-camera model demonstrated superior performance,with RC2 values for biomass,chlorophyll,and total nitrogen content reaching 0.670,0.822,and 0.683,respectively,representing improvements of up to 18%,14%,and 5% compared with that of the single-camera models.The RMSEP values were decreased to 0.46 g,2.0,and 0.258%,respectively,showing reductions of up to 13%,27%,and 17% compared with that of the single-camera models,indicating that integrating dual-camera HSI data effectively enhanced the accuracy of monitoring maize canopy leaf properties.

maize canopyhyperspectral imagingpush-broom imagingdual-camera system

史卓林、杨增玲、任朝霞、于涞源、王凌龙、黄圆萍、韩鲁佳

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中国农业大学工学院,北京 100083

玉米冠层 高光谱 推扫成像 双相机系统

2024

农业机械学报
中国农业机械学会 中国农业机械化科学研究院

农业机械学报

CSTPCD北大核心
影响因子:1.904
ISSN:1000-1298
年,卷(期):2024.55(z1)