5 papers
A Dual-Domain Convolutional Network for Hyperspectral Single-Image Super-Resolution
Murat Karayaka, Usman Muhammad, Jorma Laaksonen +2
This study presents a lightweight dual-domain super-resolution network (DDSRNet) that combines Spatial-Net with the discrete wavelet transform (DWT). Specifically, our proposed mod…
Hybrid Deep Learning for Hyperspectral Single Image Super-Resolution
Usman Muhammad, Jorma Laaksonen
Hyperspectral single image super-resolution (SISR) is a challenging task due to the difficulty of restoring fine spatial details while preserving spectral fidelity across a wide ra…
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-Resolution
Usman Muhammad, Jorma Laaksonen
2D convolutional neural networks (CNNs) have attracted significant attention for hyperspectral image super-resolution tasks. However, a key limitation is their reliance on local ne…
A Fusion-Guided Inception Network for Hyperspectral Image Super-Resolution
Usman Muhammad, Jorma Laaksonen
The fusion of low-spatial-resolution hyperspectral images (HSIs) with high-spatial-resolution conventional images (e.g., panchromatic or RGB) has played a significant role in recen…
Towards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional Network
Usman Muhammad, Jorma Laaksonen, Lyudmila Mihaylova
Deep neural networks have demonstrated highly competitive performance in super-resolution (SR) for natural images by learning mappings from low-resolution (LR) to high-resolution (…