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A semi-automated gamut expansion method is proposed for transforming the colors of video and images to take ad- vantage of extended-gamut displays. In particular, a cus- tom color transformation is learned from an expert's en- hancement of a single image on an extended gamut display. This methodology allows for the gamut-expansion to be de- fined in a contextually appropriate way. From the user- enhanced image, we compare defining the gamut expansion by one linear transformation, or by a multi-dimensional LUT which we learn via local linear regression. We show that using the estimated multi-dimensional LUT with tri- linear interpolation (a standard workflow for ICC profiles and color management modules) leads to significantly more pleasant reproduction of skin tones and bright saturated colors.