Learning Shared and Cluster-Specific Dictionaries for Single Image Super-Resolution
Recently, many multi-dictionary-based sparse representation methods have been proposed for single-image super-resolution (SISR) by learning a sub-dictionary for each specific type of visual content (i.e., a cluster). Although promising reconstruction results have been achieved for certain scenarios,...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8766085/ |