Underwater Image Super-Resolution via Dual-aware Integrated Network
Underwater scenes are often affected by issues such as blurred details, color distortion, and low contrast, which are primarily caused by wavelength-dependent light scattering; these factors significantly impact human visual perception. Convolutional neural networks (CNNs) have recently displayed ve...
Main Authors: | Aiye Shi, Haimin Ding |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/24/12985 |
Similar Items
-
Underwater Image Super-Resolution Using Frequency-Domain Enhanced Attention Network
by: Xin Liu, et al.
Published: (2024-01-01) -
Collaborative Framework for Underwater Object Detection via Joint Image Enhancement and Super-Resolution
by: Xun Ji, et al.
Published: (2023-09-01) -
Burst-Enhanced Super-Resolution Network (BESR)
by: Jiaao Li, et al.
Published: (2024-03-01) -
Super-resolution reconstruction based on Gaussian transform and attention mechanism
by: Shuilong Zou, et al.
Published: (2023-01-01) -
Multi-Attention Multi-Image Super-Resolution Transformer (MAST) for Remote Sensing
by: Jiaao Li, et al.
Published: (2023-08-01)