Abstract
The illumination chromaticity estimation based on the dichromatic reflection model has not been made practicable, since the method needs image segmentation beforehand. However, its two-dimensional model is sufficiently robust, when it is combined with the least square method. The proposed algorithm executes the color space division instead of the segmentation. The original image is divided into small color regions, each of which corresponds to one of color sub-spaces. Though this division is imperfect image segmentation, the illumination chromaticity estimation based on the chromaticity distribution in the color regions is possible. Experimental result shows that this method is also applicable to images of apparently matt surfaces.
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Tajima, J. (2009). Illumination Chromaticity Estimation Based on Dichromatic Reflection Model and Imperfect Segmentation. In: Trémeau, A., Schettini, R., Tominaga, S. (eds) Computational Color Imaging. CCIW 2009. Lecture Notes in Computer Science, vol 5646. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03265-3_6
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DOI: https://doi.org/10.1007/978-3-642-03265-3_6
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