Hyperspectral image super-resolution, which refers to reconstructing the high-resolution
hyperspectral image from the input low-resolution observation, aims to improve the spatial …

Remote sensing technology has undeniable importance in various industrial applications,
such as mineral exploration, plant detection, defect detection in aerospace and shipbuilding …

Hyperspectral image (HSI) restoration aims at recovering clean images from degraded
observations and plays a vital role in downstream tasks. Existing model-based methods …

Diffusion models have recently received a surge of interest due to their impressive
performance for image restoration, especially in terms of noise robustness. However …

Hyperspectral image (HSI) super-resolution (SR) is a classical computer vision task that
aims to accomplish the conversion of images from lower to higher resolutions. With the …

Remarkable achievements have been obtained with binary neural networks (BNN) in real-
time and energy-efficient single-image super-resolution (SISR) methods. However, existing …

In recent years, many single hyperspectral image super-resolution methods have emerged
to enhance the spatial resolution of hyperspectral images without hardware modification …

To address the limitations of hyperspectral imaging systems, super-resolution (SR)
techniques that fuse low-resolution hyperspectral image (HSI) with high-resolution …

Due to the generally low spatial resolution of hyperspectral images (HSIs), early
multispectral images lacked corresponding panchromatic bands, and as a result, fusion …

Recently, infrared thermal radiation effect correction methods are dominated by removing
bias field in spatial domain. Since they do not consider the low-frequency characteristics of …