Gamut mapping with image Laplacian commutators

In this paper, we present a gamut mapping algorithm that is based on spectral properties of image Laplacians as image structure descriptors. Using the fact that structurally similar images have similar Laplacian eigenvectors and employing the relation between joint diagonalizability and commutativity of matrices, we minimize the Laplacians commutator w.r.t. the parameters of a color transformation to achieve optimal structure preservation while complying with the target gamut. Our method is computationally efficient, favorably compares to state-of-the-art approaches in terms of quality, allows mapping to devices with any number of primaries, and supports gamma correction, accounting for brightness response of computer displays.