Kui Fu1, Jiansheng Peng1, 2, *, Hanxiao Zhang2, Xiaoliang Wang3, Frank Jiang4
CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1977-1997, 2020, DOI:10.32604/cmc.2020.09882
- 30 June 2020
Abstract Single image super resolution (SISR) is an important research content in the
field of computer vision and image processing. With the rapid development of deep
neural networks, different image super-resolution models have emerged. Compared to
some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods
using traditional convolutional neural networks, SISR based on generative adversarial
networks (GAN) has achieved the most advanced visual performance. In this review, we
first explore the challenges faced by SISR and introduce some common datasets and
evaluation More >
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