Example-based color stylization based on categorical perception
Author(s): Youngha Chang, Keiji Uchikawa, Suguru Saito, Masayuki Nakajima.
Proceedings: 1st Symposium on Applied perception in graphics and visualization, pp. 91--98, ACM Press,
2004.
[BibTeX] 
Abstract:
We describe a new computational approach to stylize the colors of
an image by using a reference image. During processing, we take
characteristics of human color perception into account to generate
more appealing results. Our system starts by classifying each pixel
value into one of a set of the basic color categories, derived from
our psycho-physiological experiments. The basic color categories
are perceptual categories that are universal to everyone, regardless
of nationality or cultural background. These categories provide restrictions
on the color transformations to avoid generating unnatural
results. Our system then renders a new image by transferring
colors from a reference image to the input image, based on this categorizations.
To avoid artifacts due to the explicit clustering, our
system denes fuzzy categorization when pseudo-contours appear
in the resulting image. We present a variety of results and show that
our color transformation performs a large, yet natural color transformation
without any sense of incongruity, and that the resulting
images automatically capture the characteristics of the color use of
the reference image.