ML Anthology

Fast Single Image Reflection Suppression via Convex Optimization

Yang Yang, Wenye Ma, Yin Zheng, Jian-Feng Cai, Weiyu Xu
CVPR 2019
doi:10.1109/CVPR.2019.00833 /cvpr/2019/yang2019cvpr-fast/

Abstract

Removing undesired reflections from images taken through the glass is of great importance in computer vision. It serves as a means to enhance the image quality for aesthetic purposes as well as to preprocess images in machine learning and pattern recognition applications. We propose a convex model to suppress the reflection from a single input image. Our model implies a partial differential equation with gradient thresholding, which is solved efficiently using Discrete Cosine Transform. Extensive experiments on synthetic and real-world images demonstrate that our approach achieves desirable reflection suppression results and dramatically reduces the execution time compared to the state of the art.

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Cite

Text

Yang et al. "Fast Single Image Reflection Suppression via Convex Optimization." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019. doi:10.1109/CVPR.2019.00833

Markdown

[Yang et al. "Fast Single Image Reflection Suppression via Convex Optimization." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019.](https://mlanthology.org/cvpr/2019/yang2019cvpr-fast/) doi:10.1109/CVPR.2019.00833

BibTeX

@inproceedings{yang2019cvpr-fast,
  title     = {{Fast Single Image Reflection Suppression via Convex Optimization}},
  author    = {Yang, Yang and Ma, Wenye and Zheng, Yin and Cai, Jian-Feng and Xu, Weiyu},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2019},
  doi       = {10.1109/CVPR.2019.00833},
  url       = {https://mlanthology.org/cvpr/2019/yang2019cvpr-fast/}
}