Aliasing Detection and Reduction in Plenoptic Imaging

Abstract

When using plenoptic camera for digital refocusing, angular undersampling can cause severe (angular) aliasing artifacts. Previous approaches have focused on avoiding aliasing by pre-processing the acquired light field via prefiltering, demosaicing, reparameterization, etc. In this paper, we present a different solution that first detects and then removes aliasing at the light field refocusing stage. Different from previous frequency domain aliasing analysis, we carry out a spatial domain analysis to reveal whether the aliasing would occur and uncover where in the image it would occur. The spatial analysis also facilitates easy separation of the aliasing vs. non-aliasing regions and aliasing removal. Experiments on both synthetic scene and real light field camera array data sets demonstrate that our approach has a number of advantages over the classical prefiltering and depth-dependent light field rendering techniques.

Cite

Text

Xiao et al. "Aliasing Detection and Reduction in Plenoptic Imaging." Conference on Computer Vision and Pattern Recognition, 2014. doi:10.1109/CVPR.2014.425

Markdown

[Xiao et al. "Aliasing Detection and Reduction in Plenoptic Imaging." Conference on Computer Vision and Pattern Recognition, 2014.](https://mlanthology.org/cvpr/2014/xiao2014cvpr-aliasing/) doi:10.1109/CVPR.2014.425

BibTeX

@inproceedings{xiao2014cvpr-aliasing,
  title     = {{Aliasing Detection and Reduction in Plenoptic Imaging}},
  author    = {Xiao, Zhaolin and Wang, Qing and Zhou, Guoqing and Yu, Jingyi},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2014},
  doi       = {10.1109/CVPR.2014.425},
  url       = {https://mlanthology.org/cvpr/2014/xiao2014cvpr-aliasing/}
}