Color Tweak in Image Mosaicking Application

Abstract

Image Mosaicking have found a vast field of applications ranging from satellite or aerial imagery to medical imaging street view maps, city 3D modelling, texture synthesis or stereo reconstruction and so on. 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. The color correction is performed by applying those functions to all the regions of the image. A new color correction algorithm with the usage of truncated Gaussians is used to perform accurate color distribution. Results show that the proposed approach obtains the best average scores in both data sets and evaluation metrics and is also the most robust to failures.