针对传统的实验室分析水体叶绿素含量操作复杂、时间耗费长、样本破坏性强,无法满足大面积、实时的现场监测需求,本文提出了一种基于激光荧光和摄像头的水体叶绿素探测装置与方法,通过激光诱导荧光技术结合摄像头图像分析监测叶绿素浓...针对传统的实验室分析水体叶绿素含量操作复杂、时间耗费长、样本破坏性强,无法满足大面积、实时的现场监测需求,本文提出了一种基于激光荧光和摄像头的水体叶绿素探测装置与方法,通过激光诱导荧光技术结合摄像头图像分析监测叶绿素浓度。分别设计了无光组和激光组对比实验,对荧光图像划分成红色、绿色、灰度和蓝色四个通道图像,计算图像的平均亮度并分析图像平均亮度与叶绿素浓度的相关性。结果表明,激光照射大大提升了图像亮度分析监测叶绿素浓度的可能性,在不同颜色通道下的叶绿素浓度与荧光图像的亮度除蓝色外均具有较强的相关性,可以选择平均误差以及标准差最低的亮度通道进行叶绿素的监测,最终实现对水体叶绿素的快速、准确、低成本监测。该方法可应用于环境监测、水资源管理和水生态研究等领域。Aiming at the traditional laboratory analysis of chlorophyll content in water bodies, which is complex, time-consuming, and destructive to samples and unable to meet the needs of large-scale and real-time field monitoring, this paper proposes a chlorophyll detection device and method based on laser fluorescence and camera technology. By combining laser-induced fluorescence technology with camera image analysis, chlorophyll concentration can be monitored. Comparative experiments between a non-light group and a laser group were designed. Fluorescence images were divided into four channel images: red, green, grayscale, and blue. The average brightness of the images was calculated, and the correlation between image brightness and chlorophyll concentration was analyzed. The results showed that laser irradiation significantly enhanced the potential for monitoring chlorophyll concentration through image brightness analysis. Chlorophyll concentration and fluorescence image brightness in different color channels, except for blue, showed a strong correlation. The bright展开更多
文摘针对传统的实验室分析水体叶绿素含量操作复杂、时间耗费长、样本破坏性强,无法满足大面积、实时的现场监测需求,本文提出了一种基于激光荧光和摄像头的水体叶绿素探测装置与方法,通过激光诱导荧光技术结合摄像头图像分析监测叶绿素浓度。分别设计了无光组和激光组对比实验,对荧光图像划分成红色、绿色、灰度和蓝色四个通道图像,计算图像的平均亮度并分析图像平均亮度与叶绿素浓度的相关性。结果表明,激光照射大大提升了图像亮度分析监测叶绿素浓度的可能性,在不同颜色通道下的叶绿素浓度与荧光图像的亮度除蓝色外均具有较强的相关性,可以选择平均误差以及标准差最低的亮度通道进行叶绿素的监测,最终实现对水体叶绿素的快速、准确、低成本监测。该方法可应用于环境监测、水资源管理和水生态研究等领域。Aiming at the traditional laboratory analysis of chlorophyll content in water bodies, which is complex, time-consuming, and destructive to samples and unable to meet the needs of large-scale and real-time field monitoring, this paper proposes a chlorophyll detection device and method based on laser fluorescence and camera technology. By combining laser-induced fluorescence technology with camera image analysis, chlorophyll concentration can be monitored. Comparative experiments between a non-light group and a laser group were designed. Fluorescence images were divided into four channel images: red, green, grayscale, and blue. The average brightness of the images was calculated, and the correlation between image brightness and chlorophyll concentration was analyzed. The results showed that laser irradiation significantly enhanced the potential for monitoring chlorophyll concentration through image brightness analysis. Chlorophyll concentration and fluorescence image brightness in different color channels, except for blue, showed a strong correlation. The bright
