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.

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] .