SK-SVR: Sigmoid kernel support vector regression based in-scale single image super-resolution.
Jebaveerasingh JebaduraiJ. Dinesh PeterPublished in: Pattern Recognit. Lett. (2017)
Keyphrases
- support vector
- single image super resolution
- kernel function
- support vector regression
- rbf kernel
- support vector machine
- sparse coding
- image patches
- radial basis function
- super resolution
- cross validation
- dictionary learning
- feature space
- feature selection
- sparse representation
- low resolution
- hyperparameters
- machine learning
- scale space
- high dimensional
- maximum likelihood
- edge detection
- high resolution images
- high resolution