Abstract
We propose a new method for the visualization of spectral images. It involves a perception-based spectrum segmentation using an adaptable thresholding of the stretched CIE standard observer color-matching functions. This allows for an underlying removal of irrelevant channels, and, consequently, an alleviation of the computational burden of further processings. Principal Components Analysis is then used in each of the three segments to extract the Red, Green and Blue primaries for final visualization. A comparison framework using two different datasets shows the efficiency of the proposed method.
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Le Moan, S., Mansouri, A., Voisin, Y., Hardeberg, J.Y. (2010). An Efficient Method for the Visualization of Spectral Images Based on a Perception-Oriented Spectrum Segmentation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17289-2_35
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DOI: https://doi.org/10.1007/978-3-642-17289-2_35
Publisher Name: Springer, Berlin, Heidelberg
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