Colour Transfer using the L2 Metric

17th May 2017
Colour Transfer using the L2 Metric


Colour transfer is an important pre-processing step in many applications, including stereo vision, surface reconstruction and image stitching. It can also be applied to images and videos as a post processing step to create interesting special effects and change their tone or feel. While many software tools are available to professionals for editing the colours and tone of an image, bringing this type of technology into the hands of everyday users, with an interface that is intuitive and easy to use, has generated a lot of interest in recent years.

One approach often used for colour transfer is to allow the user to provide a palette image which has the desired colour distribution, and use it to transfer the desired colour feel to the original target image. This approach allows the user to easily generate the desired colour transfer result without the need for user interaction.

Demo: Colour Transfer Using the L2 metric

It has recently been shown that the L2 metric can be used to create good colour transfer results when the user provides a palette image for recolouring [1]. This technique proposes to model the colour distribution of the target and palette images using Gaussian Mixture Models (GMMs) and registers these GMMs to compute the colour transfer function that maps the colours of the palette image to the target image. It has been shown to outperform other state of the art colour transfer techniques, and can be easily extended to video content. A demo of this colour transfer technique is available here:

In the V-Sense project we are investigating ways to extend this L2 based colour transfer approach to other applications, finding areas in which this robust metric could prove advantageous.



[1] Robust Registration of Gaussian Mixtures fro Colour Transfer , Mairéad Grogan and Rozenn Dahyot, ArXiv, May 2017.