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Creating RGB Images from Hyperspectral Images Using a Color Matching Function

机译:使用颜色匹配函数从高光谱图像创建RGB图像

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Hyperspectral images (HSI) are composed of hundreds of spectral bands, covering a broad range of the electromagnetic spectrum. However, images can only be visualized using three spectral channels for red, green, and blue (RGB) colors. Generating realistic RGB images using HSI is seldom the main focus of remote sensing researchers, and is therefore sometimes lacking. In this paper, we present an algorithm which creates realistic color images of HSI, using standardized methods. Research, conducted on the human perception of color in the 1920s culminated in the CIE 1931 XYZ color space. The algorithm maps every spectral band in the visible spectrum to the XYZ color space, using D65 as the reference illuminant, and then maps the XYZ to the sRGB (standard Red Green Blue) color space. The image is gamma-corrected and finally thresholded to improve contrast. The method was validated using two HSIs, creating realistic color images.
机译:高光谱图像(HSI)由数百个光谱带组成,覆盖宽范围的电磁谱。但是,只能使用用于红色,绿色和蓝色(RGB)颜色的三个光谱通道可视化图像。使用HSI生成现实RGB图像很少是遥感研究人员的主要焦点,因此有时缺乏。在本文中,我们介绍了一种算法,它使用标准化方法创建HSI的现实彩色图像。研究,对​​20世纪20年代的人类对CIE 1931 XYZ颜色空间中的冠状色素的感知进行了研究。该算法将可见频谱中的每个光谱带映射到XYZ颜色空间,使用D65作为参考光源,然后将XYZ映射到SRGB(标准红色绿色蓝色)颜色空间。图像是伽马校正的并且最终阈值以改善对比度。使用两个HSIS验证该方法,创建现实彩色图像。

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