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Abstract:
Many color-related image adjustments can be conveniently executed by exposing
at most a small number of parameters to the user. Examples are tone
reproduction, contrast enhancements, gamma correction and white balancing.
Others require manual touch-ups, applied by means of brush strokes. More
recently, a new class of algorithms has emerged, which transfers specific image
attributes from one or more example images to a target. These attributes do not
have to be well-defined and concepts that are difficult to quantify with a
small set of parameters,
such as the �mood� of an image, can be instilled upon a target image simply
through the mechanism of selecting appropriate examples. This makes
example-based image manipulation a particularly suitable paradigm in creative
applications, but also finds uses in more technical tasks such as stereo pair
correction,video compression, image colorization, panorama stitching and
creating night-time images out of day-light shots.
