Sparse bayesian learning of filters for efficient image expansion.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 20215080.
- Also identified by DOI 10.1109/TIP.2010.2043010.
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Abstract
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.
Medical subject headings
- Algorithms
- Artificial Intelligence
- Image Enhancement
- Image Interpretation, Computer-Assisted
- Pattern Recognition, Automated