A new public Alsat-2B dataset for single-image super-resolution

03/21/2021
by   Achraf Djerida, et al.
0

Currently, when reliable training datasets are available, deep learning methods dominate the proposed solutions for image super-resolution. However, for remote sensing benchmarks, it is very expensive to obtain high spatial resolution images. Most of the super-resolution methods use down-sampling techniques to simulate low and high spatial resolution pairs and construct the training samples. To solve this issue, the paper introduces a novel public remote sensing dataset (Alsat2B) of low and high spatial resolution images (10m and 2.5m respectively) for the single-image super-resolution task. The high-resolution images are obtained through pan-sharpening. Besides, the performance of some super-resolution methods on the dataset is assessed based on common criteria. The obtained results reveal that the proposed scheme is promising and highlight the challenges in the dataset which shows the need for advanced methods to grasp the relationship between the low and high-resolution patches.

READ FULL TEXT

page 2

page 3

page 5

10/01/2020

High Quality Remote Sensing Image Super-Resolution Using Deep Memory Connected Network

Single image super-resolution is an effective way to enhance the spatial...
03/01/2019

Deep Learning for Multiple-Image Super-Resolution

Super-resolution reconstruction (SRR) is a process aimed at enhancing sp...
11/06/2020

Augmented Equivariant Attention Networks for Electron Microscopy Image Super-Resolution

Taking electron microscopy (EM) images in high-resolution is time-consum...
04/04/2022

Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution

Automated tracking of urban development in areas where construction info...
09/02/2021

Infrared Image Super-Resolution via Heterogeneous Convolutional WGAN

Image super-resolution is important in many fields, such as surveillance...

Please sign up or login with your details

Forgot password? Click here to reset