ML Anthology

Extracting Smooth and Transparent Layers from a Single Image

Sai Kit Yeung, Tai-Pang Wu, Chi-Keung Tang
CVPR 2008
doi:10.1109/CVPR.2008.4587494 /cvpr/2008/yeung2008cvpr-extracting/

Abstract

Layer decomposition from a single image is an underconstrained problem, because there are more unknowns than equations. This paper studies a slightly easier but very useful alternative where only the background layer has substantial image gradients and structures. We propose to solve this useful alternative by an expectation-maximization (EM) algorithm that employs the hidden markov model (HMM), which maintains spatial coherency of smooth and overlapping layers, and helps to preserve image details of the textured background layer. We demonstrate that, using a small amount of user input, various seemingly unrelated problems in computational photography can be effectively addressed by solving this alternative using our EM-HMM algorithm.

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Cite

Text

Yeung et al. "Extracting Smooth and Transparent Layers from a Single Image." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587494

Markdown

[Yeung et al. "Extracting Smooth and Transparent Layers from a Single Image." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/yeung2008cvpr-extracting/) doi:10.1109/CVPR.2008.4587494

BibTeX

@inproceedings{yeung2008cvpr-extracting,
  title     = {{Extracting Smooth and Transparent Layers from a Single Image}},
  author    = {Yeung, Sai Kit and Wu, Tai-Pang and Tang, Chi-Keung},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2008},
  doi       = {10.1109/CVPR.2008.4587494},
  url       = {https://mlanthology.org/cvpr/2008/yeung2008cvpr-extracting/}
}