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Algorithm for Haze Determination Using Digital Camera Images

机译:数码相机图像雾度确定算法

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An algorithm for haze determination was developed based on the atmospheric optical properties to determine the concentration of particulate matter with diameter less than 10 micrometers (PM10). The purpose of this study was to use digital camera images to determine the PM10 concentration. This algorithm was developed based on the relationship between the measured PM10 concentration and the reflected components from a surface material and the atmosphere. A digital camera was used to capture images of dark and bright targets at near and far distances from the position of the targets. Ground-based PM10 measurements were carried out at selected locations simultaneously with the digital camera images acquisition using a DustTrak~(TM) meter. The PCI Geomatica version 9.1 digital image processing software was used in all image-processing analyses. The digital colour images were separated into three bands namely red, green and blue for multi-spectral analysis. The digital numbers (DN) for each band corresponding to the ground-truth locations were extracted and converted to radiance and reflectance values. Then the atmospheric reflectance was related to the PM10 using the regression algorithm analysis. The proposed algorithm produced a high correlation coefficient (R) and low root-mean-square error (RMS) between the measured and estimated PM10. This indicates that the technique using the digital camera images can provide a useful tool for air quality studies.
机译:根据大气光学特性开发了一种雾度测定算法,以测定直径小于10微米(PM10)的颗粒物浓度。这项研究的目的是使用数码相机图像确定PM10浓度。该算法是基于测得的PM10浓度与表面材料和大气层反射成分之间的关​​系而开发的。使用数码相机在距目标位置近和远的距离处捕获黑暗和明亮目标的图像。地面PM10的测量是在选定的位置进行的,同时使用DustTrakTM仪采集数码相机的图像。在所有图像处理分析中均使用了PCI Geomatica 9.1版数字图像处理软件。将数字彩色图像分为三个波段,即红色,绿色和蓝色,以进行多光谱分析。提取与真实位置相对应的每个波段的数字(DN),并将其转换为辐射度和反射率值。然后,使用回归算法分析,将大气反射率与PM10相关。所提出的算法在测量和估计的PM10之间产生了高相关系数(R)和低均方根误差(RMS)。这表明使用数码相机图像的技术可以为空气质量研究提供有用的工具。

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