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Section: New Results

Color transfer guided by summary statistics

Participants : Benoit Arbelot, Thomas Hurtut, Romain Vergne [contact] , Joëlle Thollot.

Figure 5. Our framework allows for automatic local color transfer (left) and colorization (right) based on textural properties.
IMG/ColorTransfer.png IMG/Colorization.png
Color transfer Colorization

We have targeted two related color manipulation problems: Color transfer for modifying an image colors and colorization for adding colors to a greyscale image. Automatic methods for these two applications propose to modify the input image using a reference that contains the desired colors. Previous approaches usually do not target both applications and suffer from two main limitations: possible misleading associations between input and reference regions and poor spatial coherence around image structures. In this paper, we propose a unified framework that uses the textural content of the images to guide the color transfer and colorization. Our method introduces an edge-aware texture descriptor based on region covariance, allowing for local color transformations. We show that our approach is able to produce results comparable or better than state-of-the-art methods in both applications. This work was presented at the AFIG conference [7] . An extended version is available as a research report [9] .