Upsampling

Source	Pléiades Neo tasking or catalog collections
Compatibility	- The STAC item should be a Pléiades Neo image of the display radiometric processing level - The STAC item should have been added to storage in 2023 or later
Required parameters	- Console: If your chosen input data meets the above specifications you will be able to run your job - API: You will need to input an Output title and the Input data
Bands to unsample	You need to specify if you want to upsample the red, green, and blue bands or the NIR, red edge, and deep blue bands
Output data format	GeoTIFF file with an upsampled spatial resolution
Output	The result will be added to your account as a STAC item in a new STAC collection. You can retrieve the resulting data in one of the following ways: - Open the console, go to Data management → Jobs - Retrieve the results via the API

Algorithm performance and training data

Tensorflow is used to build a convolutional neural network (CNN) for super-resolution. Unlike other conventional super-resolution networks, high-resolution and low-resolution images are from different satellites. In the case of Pléiades Neo super-resolution, 10 cm GSD images are used for high resolution.

It helps users to have a clearer view of their areas of interest at a much lower cost compared to commercial imagery.

Remark: The algorithm also works with Pléiades Neo (Analytic), but it is not trained on 16-bit images. There might be color differences after applying super-resolution to the Pléiades Neo (Analytic) 16-bit product.

Processing time: Without considering preprocessing, it takes ~16 minutes to enhance a 3.92 sqkm (6600 x 6600 pixels) Pléiades Neo image using GPU (Nvidia Tesla K80) provided by UP42.

Limitation: Super-resolution cannot express features that are not shown in the original image.

Further information

For more information, please visit the technical documentation.