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The objective of colour mapping or colour transfer methods is to recolour a given image or video by deriving a mapping between that image and another image serving as a reference. These methods have received considerable attention in recent years, both in academic literature and industrial applications. Methods for recolouring images have often appeared under the labels of colour correction, colour transfer or colour balancing, to name a few, but their goal is always the same: mapping the colours of one image to another. In this paper, we present a comprehensive overview of these methods and offer a classification of current solutions depending not only on their algorithmic formulation but also their range of applications. We also provide a new dataset and a novel evaluation technique called 'evaluation by colour mapping roundtrip'. We discuss the relative merit of each class of techniques through examples and show how colour mapping solutions can have been applied to a diverse range of problems.

We propose a color mapping method that compensates color differences between images having a common semantic content such as multiple views of a scene taken from different viewpoints. A so-called color mapping model is usually estimated from color correspondences selected from those images. In this work, we introduce a color mapping that model color change in two steps: first, nonlinear, channel-wise mapping; second, linear, cross-channel mapping. Additionally, unlike many state of the art methods, we estimate the model from sparse matches and do not require dense geometric correspondences. We show that well known cross-channel color change can be estimated from sparse color correspondence. Quantitative and visual benchmark tests show good performance compared to recent methods in literature.

International audienceOne of the basic tenets of conventional applied colorimetry is that the whole population of color normal observers can be represented by a single "standard" observer with reasonable accuracy. The 1964 CIE standard colorimetric observer has indeed served us well in all industrial color imaging applications, until recently. With the proliferation of modern wide-gamut displays with narrow-band primaries, color scientists and engineers face a new challenge. Various recent studies, including those by the current authors, have shown that the color perception on such displays varies significantly among color normal observers. Conventional colorimetry has no means to predict this variation. In this paper, we explore this problem by summarizing the results from an ongoing study, and explain the practical significance of this issue in the context of display applications

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