A Probabilistic Approach for Color Correction in Image Mosaicking Applications,Image mosaicking applications require both geometrical and photometrical registrations between the images that compose the mosaic. This paper proposes a probabilistic color correction algorithm for correcting the photometrical disparities. First, the image to be color corrected is segmented into several regions using mean shift. Then, connected regions are extracted using a region fusion algorithm. Local joint image histograms of each region are modeled as collections of truncated Gaussians using a maximum likelihood estimation procedure. Then, local color palette mapping functions are computed using these sets of Gaussians.

This A Probabilistic Approach for Color Correction in Image Mosaicking Applications paper proposes a novel color correction algorithm. Images are color segmented using mean-shift and a region fusion algorithm. Each segmented region is then used to compute a local color palette mapping function by fitting a set of univariate truncated Gaussians to the observed color mappings. Finally, by using an extension of the color palette mapping functions to the whole image, it is possible to produce mosaics where no color transitions are noticeable.