High-resolution satellite imagery is a key element for many Earth monitoring applications.
Satellites such as Sentinel-2 feature characteristics that are favorable for super-resolution …

Wildlife surveys are key to assessing the health of global biodiversity. Traditional field and
aerial methods however have significant limitations, including high costs, substantial time …

Image resolution is an important criterion for many applications based on satellite imagery.
In this work, we adapt a state-of-the-art kernel regression technique for smartphone camera …

Accurately predicting the impact of hormonal therapy on Prostate Cancer (PC) lesions is
paramount for effective treatment planning and monitoring. This study proposes a …

Supervised training has led to state-of-the-art results in image and video denoising.
However, its application to real data is limited since it requires large datasets of noisy-clean …

Burst or multi-frame image super-resolution (MFSR) has emerged as a critical area in
computer vision, aimed at reconstructing high-resolution images from low-resolution bursts …

This paper introduces a camera-array-based super-resolution color polarization imaging
system designed to simultaneously capture color and polarization information of a scene in …

The use of NeRF to model 3D scenes from satellite images is becoming increasingly
common. However, the models proposed to date assume the availability of pre-processed …

Long-strip imaging is an important way of improving the coverage and acquisition efficiency
of remote sensing satellite data. During the agile maneuver imaging process of the satellite …

To date, the best-performing blind super-resolution (SR) techniques follow one of two
paradigms:(A) train standard SR networks on synthetic low-resolution–high-resolution (LR …