vkristoll
commented
12 months ago Dear Ana,
I have included the file “Preparing_input_files.txt” in the github repository (https://github.com/vkristoll/Pansharpening-PRISMA-CNNs). This file includes a link to access a Prisma L1 level image and a detailed description about preparing the input files of the CNN.
In the above repository you can also find the file “PRISMA_L2D_georeference.py” which contains information on georeferencing Prisma L2D level images.
Concerning the distortions, it is noted that in our implementation we used L1 instead of L2D images because of better visual quality. In addition, as stated in our paper (https://ieeexplore.ieee.org/abstract/document/9406795), the CNN method after histogram clipping produced satisfactory spectra but showed higher image distortions than conventional methods (e.g. PCA).
In order to reduce the noise in the output you could experiment with different patch and kernel sizes during training. Another simple solution (especially in bigger patch sizes) is producing different inference outputs by moving the inference image by a few pixels and then creating an average. The logic behind this is the fact that the noise is mostly present in the edges of the patches. You could also consider creating a more complex architecture (e.g adding residual blocks) as proposed in in our follow-up study.
( https://www.sciencedirect.com/science/article/pii/S0025326X22006567 , https://github.com/vkristoll/Fusion-Sentinel2-Worldview )
Best regards, Viktoria Kristollari
On Wed, Nov 22, 2023 at 10:35 PM Ana Kilgore @.***> wrote:
I am using your code to pansharpen a PRISMA dataset and am encountering some issues with the output. First of all, there is visible distortion remaining in the 9x9 pixel groups (image included below), second the projection is lost, and third the pixels are 1x1 m instead of 5x5 m. I have two questions, first what are the dimensions of your input data? Second, would it be possible to provide a sample image to test along with the script?
Thank you!
[image: pansharpen_test] https://user-images.githubusercontent.com/51758386/285034878-365c8b2e-dd51-4fce-8ac4-1193b07dcc8c.png
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-- Viktoria Kristollari Remote Sensing and Machine Learning Expert Ph.D. Candidate in the Lab of Remote Sensing School of Rural, Surveying and Geoinformatics Eng. National Technical University of Athens website:http://users.ntua.gr/vkristoll/
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I am using your code to pansharpen a PRISMA dataset and am encountering some issues with the output. First of all, there is visible distortion remaining in the 9x9 pixel groups (image included below), second the projection is lost, and third the pixels are 1x1 m instead of 5x5 m. I have two questions, first what are the dimensions of your input data? Second, would it be possible to provide a sample image to test along with the script?
Thank you!