Single Image Super-Resolution Based on Deep Learning Features and Dictionary Model

Single Image Super-Resolution Based on Deep Learning Features and Dictionary Model

In traditional single image super-resolution (SR) methods based on dictionary model, a large number of image features are needed to train the SR dictionary. In general, these features are extracted by artificial rules, such as pixel gray, gradient, and texture structure. But, the dictionary model tr...

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Bibliographic Details
Main Authors: Liling Zhao, Quansen Sun, Zelin Zhang
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Kernel function
deep learning features
dictionary model
single image super-resolution
PCA
Online Access:https://ieeexplore.ieee.org/document/8002557/

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