Published August 24, 2021 | Version v1
Dataset Open

PAirMax-Airbus

  • 1. Institute of Methodologies for Environmen- tal Analysis, National Research Council, Italy
  • 2. GIPSA-Lab, Grenoble Institute of Technology, France
  • 3. Department of Information Engineer- ing and Mathematics, University of Siena, Italy
  • 4. Maxar Technologies Inc., USA

Description

This archive contains 5 panchromatic and multispectral bundles (at both both full and reduced resolution).
These images are part of the PAirMax dataset (*).

This dataset is provided as a password protected folder as data can be accessed only after accepting the Airbus license.

Description:
The images were derived from original acquisitions by the Pléiades and Spot7 satellites and are provided courtesy of Airbus.
The original images full scenes can be accessed at:
https://sandbox.intelligence-airbusds.com -> Pansharpening dataset.

The 5 images in this archive are listed below.
Please refer to [1] for more details on the images and the preprocessing done.
- Pl_Hous_Urb
- Pl_Sacr_Mix
- Pl_Stoc_Urb
- S7_Napl_Urb
- S7_NewY_Mix

Instruction for retrieving the password:
- Go to https://sandbox.intelligence-airbusds.com
- Fill the form for requesting the Pansharpening dataset (need to accept the Airbus license)
- The password will be provided in the confirmation email.

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(*) The PAirMax dataset is a collection of data with the aim of assessing
the performance of pansharpening algorithms. The data collection
includes 5 test cases selected at full resolution (FR), acquired by two
sensors belonging to the Airbus' constellation of high-resolution
imaging satellites. Moreover, 5 related test cases at reduced resolution
(RR), simulated according to the Wald’s protocol, are included, thus
resulting in 10 challenging test cases for pansharpening performance
assessment. For further details, please, refer to the paper:

[1] G. Vivone, M. Dalla Mura, A. Garzelli, and F. Pacifici, "A Benchmarking
Protocol for Pansharpening: Dataset, Pre-processing, and Quality
Assessment," IEEE Journal of Selected Topics in Applied Earth
Observations and Remote Sensing, 2021.

Files

PAirMax-Airbus.zip

Files (153.9 MB)

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Additional details

Related works

Is cited by
Journal article: 10.1109/JSTARS.2021.3086877 (DOI)