Single Image Reflection Suppression

Nikolaos Arvanitopoulos, Radhakrishna Achanta, Sabine Susstrunk

CVPR 2017

doi:10.1109/CVPR.2017.190 /cvpr/2017/arvanitopoulos2017cvpr-single/

Abstract

Reflections are a common artifact in images taken through glass windows. Automatically removing the reflection artifacts after the picture is taken is an ill-posed problem. Attempts to solve this problem using optimization schemes therefore rely on various prior assumptions from the physical world. Instead of removing reflections from a single image, which has met with limited success so far, we propose a novel approach to suppress reflections. It is based on a Laplacian data fidelity term and an l-zero gradient sparsity term imposed on the output. With experiments on artificial and real-world images we show that our reflection suppression method performs better than the state-of-the-art reflection removal techniques.

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Cite

Text

Arvanitopoulos et al. "Single Image Reflection Suppression." Conference on Computer Vision and Pattern Recognition, 2017. doi:10.1109/CVPR.2017.190

Markdown

[Arvanitopoulos et al. "Single Image Reflection Suppression." Conference on Computer Vision and Pattern Recognition, 2017.](https://mlanthology.org/cvpr/2017/arvanitopoulos2017cvpr-single/) doi:10.1109/CVPR.2017.190

BibTeX

@inproceedings{arvanitopoulos2017cvpr-single,
  title     = {{Single Image Reflection Suppression}},
  author    = {Arvanitopoulos, Nikolaos and Achanta, Radhakrishna and Susstrunk, Sabine},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2017},
  doi       = {10.1109/CVPR.2017.190},
  url       = {https://mlanthology.org/cvpr/2017/arvanitopoulos2017cvpr-single/}
}