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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-XLII-3-2083-2018</article-id>
<title-group>
<article-title>OIL SPILL AISA+ HYPERSPECTRAL DATA DETECTION BASED ON DIFFERENT SEA SURFACE GLINT SUPPRESSION METHODS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yang</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ren</surname>
<given-names>G.</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>Ma</surname>
<given-names>Y.</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>Dong</surname>
<given-names>L.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wan</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Geosciences, China University of Petroleum, Qingdao 266061, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>The First Institute of Oceanography, SOA, Qingdao 266061, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>North China Sea Branch, SOA, Qingdao 266061, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>30</day>
<month>04</month>
<year>2018</year>
</pub-date>
<volume>XLII-3</volume>
<fpage>2083</fpage>
<lpage>2087</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2018 J. Yang et al.</copyright-statement>
<copyright-year>2018</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/XLII-3/2083/2018/isprs-archives-XLII-3-2083-2018.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-3/2083/2018/isprs-archives-XLII-3-2083-2018.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-3/2083/2018/isprs-archives-XLII-3-2083-2018.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-3/2083/2018/isprs-archives-XLII-3-2083-2018.pdf</self-uri>
<abstract>
<p>The marine oil spill is a sudden event, and the airborne hyperspectral means to detect the oil spill is an important part of the rapid response. Sun glint, the specular reflection of sun light from water surface to sensor, is inevitable due to the limitation of observation geometry, which makes so much bright glint in image that it is difficult to extract oil spill feature information from the remote sensing data. This paper takes AISA+ airborne hyperspectral oil spill image as data source, using multi-scale wavelet transform, enhanced Lee filter, enhanced Frost filter and mean filter method for sea surface glint suppression of images. And then the classical SVM method is used for the oil spill information detection, and oil spill information distribution map obtained by human-computer interactive interpretation is used to verify the accuracy of oil spill detection. The results show that the above methods can effectively suppress the sea surface glints and improve the accuracy of oil spill detection. The enhanced Lee filter method has the highest detection accuracy of 88.28&amp;thinsp;%, which is 12.2&amp;thinsp;% higher than that of the original image.</p>
</abstract>
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