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Color Visualization System for Near-Infrared Multispectral Images

机译:用于近红外多光谱图像的彩色可视化系统

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摘要

In this paper, we analyze a color visualization system for multispectral images belonging to the near-infrared region (NIR, 800-1000 nm). Samples with the same appearance in the visible region can differ in the NIR and can be differentiated by taking into account the extra information included in this region. Using a multispectral system, five different images of textile samples with varying spectral reflectance are obtained. The aim of the study is to analyze how the monochromatic images or spectral bands of the samples (with only a few shades of gray) should be combined in order to obtain a false pseudocolored image (with a large range of different colors). With the color image, it is possible to discriminate clearly between different objects. In order to achieve this separation, it is necessary to define a color space representation. In this paper, several possible combinations based on different methods are presented. The pseudocolored images are then visualized on a calibrated CRT monitor. Finally, the color differences between samples are evaluated using several parameters. The methods which provide the best results in terms of visual discrimination are based on PCA analysis.
机译:在本文中,我们分析了属于近红外区域(NIR,800-1000 nm)的多光谱图像的彩色可视化系统。在可见光区域具有相同外观的样品的NIR可能不同,并且可以通过考虑此区域中包含的额外信息来区分它们。使用多光谱系统,可获得具有变化的光谱反射率的纺织品样品的五个不同图像。该研究的目的是分析样品的单色图像或光谱带(只有少量灰色阴影)应如何组合,以获得假的伪彩色图像(具有大范围的不同颜色)。利用彩色图像,可以清楚地区分不同的物体。为了实现这种分离,有必要定义一个颜色空间表示。在本文中,提出了几种基于不同方法的可能组合。然后将伪彩色图像显示在经过校准的CRT监视器上。最后,使用几个参数评估样品之间的色差。在视觉辨别力方面提供最佳结果的方法基于PCA分析。

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