A closed-form solution for multi-view color correction with gradient preservation.

Color correction across multiple images for consistency is a challenging problem in image mosaicking. To facilitate the global color optimization, existing methods mainly use less flexible correction models, e.g., linear or gamma function, which often struggle to cover the practically existing color discrepancy. In this paper, we present a novel color consistency correction method that models the color remapping function with a parameterized spline curve for each image. Thanks to the flexible model representation, on the one hand, our method has the capability to handle very challenging cases, i.e. hundreds of images with drastic color discrepancy; On the other, some important image properties, e.g., image gradient, contrast, and dynamic range, can be effective formulated with model parameters. Thus, the visual quality of individual images, along with the global color consistency, are comprehensively considered in our specifically designed cost function, which is solved in a closed form via convex quadratic programming. In addition, considering the possibly existing alteration objects within inter-image overlaps, we also propose an functional change detection algorithm with gradient and color features utilized, which guarantees the accuracy of the extracted color correspondences. We have tested the proposed approach on several challenging dataset of diverse genres, which shows that our method substantially outperforms state-of-the-art methods in both visual quality and quantitative metrics. [ABSTRACT FROM AUTHOR]