Color Consistency Correction Based on Remapping Optimization for Image Stitching

Menghan Xia, Jian Yao, Renping Xie, Mi Zhang

Abstract:

Color consistency correction is a challenging problem in
image stitching, because it matters several factors, including
tone, contrast and fidelity, to present a natural appearance.
In this paper, we propose an effective color correction
method which is feasible to optimize the color consistency
across images and guarantee the imaging quality of individual
image meanwhile. Our method first apply well-directed
alteration detection algorithms to find coherent-content regions
in inter-image overlaps where reliable color correspondences
are extracted. Then, we parameterize the color
remapping curve as transform model, and express the constraints
of color consistency, contrast and gradient in an
uniform energy function. It can be formulated as a convex
quadratic programming problem which provides the global
optimal solution efficiently. Our method has a good performance
in color consistency and suffers no pixel saturation
or tonal dimming. Experimental results of representative
datasets demonstrate the superiority of our method over
state-of-the-art algorithms.