Adaptive color transfer with relaxed optimal transport
Julien Rabin, Sira Ferradans, Nicolas Papadakis · 2014
This paper studies the problem of color transfer between images using optimal transport techniques. While being a generic framework to handle statistics properly, it is also known to be sensitive to noise and outliers, and is not suitable for direct application to images without additional postprocessing regularization to remove artifacts. To tackle these issues, we propose to directly deal with the regularity of the transport map and the spatial consistency of the reconstruction. Our approach is based on the relaxed and regularized discrete optimal transport method of [1]. We extend this work by (i) modeling the spatial distribution of colors within the image domain and (ii) tuning automatically the relaxation parameters. Experiments on real images demonstrate the capacity of our model to adapt itself to the considered data.