yc-cui/Pansharpening-Zoo
A collection of deep learning based pansharpening models.
This resource helps remote sensing specialists improve the visual quality and detail of satellite or aerial images. By combining a low-resolution, color-rich multispectral image with a high-resolution, grayscale panchromatic image, it produces a single, high-resolution color image. This is useful for anyone who needs to extract fine details from satellite imagery, such as urban planners, environmental scientists, or cartographers.
No commits in the last 6 months.
Use this if you need to enhance the spatial resolution of your color satellite imagery while preserving its spectral information for detailed analysis or mapping.
Not ideal if you are working with non-satellite image data or if your primary need is for object detection rather than image enhancement.
Stars
25
Forks
1
Language
—
License
—
Category
Last pushed
Jan 13, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/yc-cui/Pansharpening-Zoo"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MLSTRUCT/MLStructFP
Multi-unit floor plan dataset for architectural analysis and recognition
yassouali/pytorch-segmentation
:art: Semantic segmentation models, datasets and losses implemented in PyTorch.
wkentaro/pytorch-fcn
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original...
meetps/pytorch-semseg
Semantic Segmentation Architectures Implemented in PyTorch
fregu856/deeplabv3
PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset.