DRCS-SR: Deep Robust Compressed Sensing for Single Image Super-Resolution
Compressed sensing (CS) represents an efficient framework to simultaneously acquire and compress images/signals while reducing acquisition time and memory requirements to process or transmit them. Specifically, CS is able to recover an image from a random measurements. Recently, deep neural networks...
Main Authors: | Hossam M. Kasem, Mahmoud M. Selim, Ehab Mahmoud Mohamed, Amr H. Hussein |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9197598/ |
Similar Items
-
Spatial Transformer Generative Adversarial Network for Robust Image Super-Resolution
by: Hossam M. Kasem, et al.
Published: (2019-01-01) -
Burst-Enhanced Super-Resolution Network (BESR)
by: Jiaao Li, et al.
Published: (2024-03-01) -
Multi-Perspective Discriminators-Based Generative Adversarial Network for Image Super Resolution
by: Oh-Young Lee, et al.
Published: (2019-01-01) -
TnTViT-G: Transformer in Transformer Network for Guidance Super Resolution
by: Armin Mehri, et al.
Published: (2023-01-01) -
HyFormer: Hybrid Grouping-Aggregation Transformer and Wide-Spanning CNN for Hyperspectral Image Super-Resolution
by: Yantao Ji, et al.
Published: (2023-08-01)