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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLIX-B3-2026-449-2026</article-id>
<title-group>
<article-title>An Open-Source Application and a Benchmarking Framework for Sentinel-2 Image Sharpening</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Vaiopoulos</surname>
<given-names>Aristides D.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Tsironis</surname>
<given-names>Vasileios</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Karantzalos</surname>
<given-names>Konstantinos</given-names>
<ext-link>https://orcid.org/0000-0001-8730-6245</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Raymetrics S.A., Spartis 32, Metamorphosis, Athens, Greece</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>National Technical University of Athens (NTUA), Department of Topography, Remote Sensing Laboratory, Athens, Greece</addr-line>
</aff>
<pub-date pub-type="epub">
<day>30</day>
<month>07</month>
<year>2026</year>
</pub-date>
<volume>XLIX-B3-2026</volume>
<fpage>449</fpage>
<lpage>455</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Aristides D. Vaiopoulos et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/449/2026/isprs-archives-XLIX-B3-2026-449-2026.html">This article is available from https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/449/2026/isprs-archives-XLIX-B3-2026-449-2026.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/449/2026/isprs-archives-XLIX-B3-2026-449-2026.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/449/2026/isprs-archives-XLIX-B3-2026-449-2026.pdf</self-uri>
<abstract>
<p>Earth Observing (EO) satellites are an invaluable tool in remote sensing and have various applications. Spatial resolution is often crucial to those applications. The current work focuses on sharpening Sentinel-2 images. Moreover, a new application/program has been developed towards this goal. The application sharpens Sentinel-2 lower resolution bands (20m, 60m) and creates a 12-band image in 10m resolution. To run the program, one needs to load a Sentinel-2 L2A product, select one or more pansharpening methods and click the fuse button. This process will fuse the whole scene, but it is possible to crop areas of interest and process them instead. To validate the process, 14 pansharpening methods were employed and tested against well-known image quality metrics. On all areas of interest, the quality indices agree with each other. However, the indices tend to penalize methods who fail spectrally, which is correct, but they also tend to favor images with poor performance in the spatial domain. MS-SSIM seems to rank better the algorithm images and is closer to the visual comparison assessment. HPF is one of the best performing methods for sharpening a L2A product of Sentinel-2. ATWT, AWLP, HCS and LMM are good alternatives according to our results. The application, S-2 Sharpy (A Sentinel-2 Image Sharpening GUI) is made available on Github. Furthermore, its generic counterpart,PanFusion (Image pansharpening GUI for various sensors) is also made available on the mentioned platform, since it was the application that set the foundation for the current application and study.</p>
</abstract>
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