Color misalignment correction is an important, yet unsolved problem, especially for multiview video captured by large disparity camera setups. In this paper, we introduce a robust large-baseline color correction method that preserves the original manifold structure of the input video. The manifold structure is extracted by locally linear embedding (LLE), aimed at linearly representing each pixel based on its neighbors, assuming that they are all clustered in a high-dimensional feature space. Besides the proposed manifold structure preservation constraint, the proposed method enforces spatio-temporal color consistencies and gradient preservation. The multiview color correction solution is obtained by solving a global optimization problem. Thorough objective and subjective experimental results demonstrate that our proposed approach significantly and systematically outperforms the state-of-the-art color correction methods on large-baseline multiview video data.
Ye, S, Lu, S-P & Munteanu, A 2017, 'Color correction for large-baseline multiview video', Signal Processing: Image Communication, vol. 53, pp. 40-50. https://doi.org/10.1016/j.image.2017.01.004
Ye, S., Lu, S.-P., & Munteanu, A. (2017). Color correction for large-baseline multiview video. Signal Processing: Image Communication, 53, 40-50. https://doi.org/10.1016/j.image.2017.01.004
@article{3567583849a04d1d9565d865706ea047,
title = "Color correction for large-baseline multiview video",
abstract = "Color misalignment correction is an important, yet unsolved problem, especially for multiview video captured by large disparity camera setups. In this paper, we introduce a robust large-baseline color correction method that preserves the original manifold structure of the input video. The manifold structure is extracted by locally linear embedding (LLE), aimed at linearly representing each pixel based on its neighbors, assuming that they are all clustered in a high-dimensional feature space. Besides the proposed manifold structure preservation constraint, the proposed method enforces spatio-temporal color consistencies and gradient preservation. The multiview color correction solution is obtained by solving a global optimization problem. Thorough objective and subjective experimental results demonstrate that our proposed approach significantly and systematically outperforms the state-of-the-art color correction methods on large-baseline multiview video data.",
keywords = "Color correction, Large-baseline cameras, Local structure preservation, Multiview video",
author = "Siqi Ye and Shao-Ping Lu and Adrian Munteanu",
year = "2017",
month = apr,
doi = "10.1016/j.image.2017.01.004",
language = "English",
volume = "53",
pages = "40--50",
journal = "Signal Processing: Image Communication",
issn = "0923-5965",
publisher = "Elsevier",
}