satellite image super-resolution
4 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in satellite image super-resolution
Most implemented papers
Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network
Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we apply a new edge-enhanced super-resolution GAN (EESRGAN) to improve the image quality of remote sensing images and use different detector networks in an end-to-end manner where detector loss is backpropagated into the EESRGAN to improve the detection performance.
The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery
We also quantify the performance of object detection as a function of native resolution and object pixel size.
Pansharpening by convolutional neural networks in the full resolution framework
A further problem is the scarcity of training data, which causes a limited generalization ability and a poor performance on off-training test images.
Fast Full-Resolution Target-Adaptive CNN-Based Pansharpening Framework
In this work, we propose a variant of this method with an effective target-adaptation scheme that allows for the reduction in inference time by a factor of ten, on average, without accuracy loss.