In a multiple-view image acquisition process, color consistency is not ensured. This is an important problem for image fusion tasks: object texturing or mosaics blending for example. In automatic mode, the camera adapts its settings –shutter-speed and aperture– to the captured image content. Therefore the color of objects changes over an image sequence.
In order to restore the color consistency, a transformation model between reference and observed colors have to be estimated. It introduces two main problems:
- the data selection (common pixels between images),
- the estimation of a reliable color transformation between those pixels.
This module propose an interface to solve this problem:
[Moulon13] propose a global multi-view color consistency solution that in a first step selects robustly the common color information between images and in a second step estimates the color transformations that set all pictures in a common color reference, which involves a global minimization. It uses a compact histogram representation of the shared color information per image pairs and solve the color consistency by using a linear program with a gain and offset model for each image.
A reference have to be choosen in order to set the color reference.
Here the obtained results on the image sequence after having choosen a “white” or “blue” image as reference: