Image super-resolution with an enhanced group convolutional neural network

Image super-resolution with an enhanced group convolutional neural network

CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to improve performance of image super-resolution, which may increase computational cost in general. In this paper, we present an enhanced super-resolution g...

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Bibliographic Details
Main Authors: Lin, C.-W (Author), Tian, C. (Author), Yuan, Y. (Author), Zhang, D. (Author), Zhang, S. (Author), Zuo, W. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2022
Subjects:
article
Arts computing
CNN
Computational costs
Convolution
convolutional neural network
Convolutional neural network
Convolutional neural networks
Group convolution
Image enhancement
image quality
Image super resolutions
Image super-resolution
Improve performance
Learning abilities
Lower frequencies
Network architecture
Optical resolving power
signal processing
Signal processing
Signal-processing
Single images
Superresolution
velocity
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