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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Annals</journal-id>
<journal-title-group>
<journal-title>ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Annals</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9050</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-annals-V-2-2020-871-2020</article-id>
<title-group>
<article-title>CORRECTION OF SYSTEMATIC RADIOMETRIC INHOMOGENEITY IN SCANNED AERIAL CAMPAIGNS USING PRINCIPAL COMPONENT ANALYSIS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Lelégard</surname>
<given-names>L.</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>Le Bris</surname>
<given-names>A.</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>Giordano</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>LASTIG, Université Gustave Eiffel, ENSG, IGN, F-94160 Saint-Mandé, France</addr-line>
</aff>
<pub-date pub-type="epub">
<day>03</day>
<month>08</month>
<year>2020</year>
</pub-date>
<volume>V-2-2020</volume>
<fpage>871</fpage>
<lpage>876</lpage>
<permissions>
<copyright-statement>Copyright: © 2020 L. Lelégard et al.</copyright-statement>
<copyright-year>2020</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-annals.copernicus.org/articles/isprs-annals-V-2-2020-871-2020.html">This article is available from https://isprs-annals.copernicus.org/articles/isprs-annals-V-2-2020-871-2020.html</self-uri>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/isprs-annals-V-2-2020-871-2020.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/isprs-annals-V-2-2020-871-2020.pdf</self-uri>
<abstract>
<p>Orthophotomosaic is defined as a single image that can be layered on a map. The term “mosaic” implies that it is produced from a set of images, usually aerial images. Even if these images are taken during cloudless period, they are impaired by radiometric inhomogeneity mostly due to atmospheric phenomena, like hotspot, haze or high altitude clouds shadows as well as imaging device systematisms, like lens vignetting. These create some unsightly radiometric inhomogeneity in the orthophotomosaic that could be corrected by using a Wallis filter. Yet this solution leads to a significant loss of contrast at small scales. This work introduces an alternative to Wallis filter by considering some systematic radiometric behaviours in the images through a principal component analysis process.</p>
</abstract>
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