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Creating RGB Images from Hyperspectral Images Using a Color Matching Function

Magnús S. Magnússon, Jakob Sigurðsson, Sveinn Eirikur Armansson, Magnús Ö. Úlfarsson, Hilda Deborah, Jóhannes R. Sveinsson

202060 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Standard illuminantRGB color modelArtificial intelligenceColor spaceComputer visionHyperspectral imagingComputer scienceSpectral colorRGB color spaceColor histogramColor modelColor balanceColor imageFalse colorFocus (optics)Image processingImage (mathematics)OpticsPhysicsRemote-Sensing Image ClassificationRemote Sensing and Land UseImage Retrieval and Classification Techniques
Creating RGB Images from Hyperspectral Images Using a Color Matching Function | Litcius