Gamut mapping transforms the colors of an input/nimage to the colors of a target device so as to exploit the full/npotential of the rendering device in terms of color rendition. In/nthis paper we present spatial gamut mapping algorithms that rely/non a perceptually-based variational framework. Our algorithms/nadapt a well-known image energy functional whose minimization/nleads to image enhancement and contrast modification. We show/nhow by varying the importance of the contrast term in the/nimage ...
Gamut mapping transforms the colors of an input/nimage to the colors of a target device so as to exploit the full/npotential of the rendering device in terms of color rendition. In/nthis paper we present spatial gamut mapping algorithms that rely/non a perceptually-based variational framework. Our algorithms/nadapt a well-known image energy functional whose minimization/nleads to image enhancement and contrast modification. We show/nhow by varying the importance of the contrast term in the/nimage functional we are able to perform gamut reduction and/ngamut extension. We propose an iterative scheme that allows our/nalgorithms to successfully map the colors from the gamut of the/noriginal image to a given destination gamut while keeping the/nperceived colors close to the original image. Both subjective and/nobjective evaluations validate the promising results achieved via/nour proposed algorithms.
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