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Example-Based Image Manipulation

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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.
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Document Type: Research Article

Publication date: January 1, 2012

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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