Sparse Bayesian Learning of Filters for Efficient Image Expansion

@article{Kanemura2010SparseBL,
  title={Sparse Bayesian Learning of Filters for Efficient Image Expansion},
  author={Atsunori Kanemura and Shin-ichi Maeda and Shin Ishii},
  journal={IEEE Transactions on Image Processing},
  year={2010},
  volume={19},
  pages={1480-1490}
}
We propose a framework for expanding a given image using an interpolator that is trained in advance with training data, based on sparse Bayesian estimation for determining the optimal and compact support for efficient image expansion. Experiments on test data show that learned interpolators are compact yet superior to classical ones.