Deep Learning for Image Super-Resolution: A Survey

South China University of Technology

PubMed
Indexed incrossrefpubmed

Abstract

Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques. This article aims to provide a comprehensive survey on recent advances of image super-resolution using deep learning approaches. In general, we can roughly group the existing studies of SR techniques into three major categories: supervised SR, unsupervised SR, and domain-specific SR. In addition, we also cover some other important issues, such as publicly available benchmark datasets and performance evaluation metrics. Finally, we conclude this survey by…

Citation impact

1,872
total citations
FWCI
103.67
Percentile
100%
References
273
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Artificial intelligence
  • Deep learning
  • Benchmark (surveying)
  • Image (mathematics)
  • Image resolution
  • Contextual image classification
  • Image processing
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