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<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/isprsarchives-XL-7-W4-103-2015</article-id>
<title-group>
<article-title>A color balancing method for wide range Remote Sensing imagery based on Regionalization</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Liu</surname>
<given-names>J.</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>Li</surname>
<given-names>H. T.</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>Gu</surname>
<given-names>H. Y.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Key Laboratory of Geo-informatics of National Administration of Surveying, Mapping and Geoinformation, Chinese Academy of Surveying and Mapping, Beijing 100830, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>26</day>
<month>06</month>
<year>2015</year>
</pub-date>
<volume>XL-7/W4</volume>
<fpage>103</fpage>
<lpage>108</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2015 J. Liu et al.</copyright-statement>
<copyright-year>2015</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-7-W4/103/2015/isprs-archives-XL-7-W4-103-2015.html">This article is available from https://isprs-archives.copernicus.org/articles/XL-7-W4/103/2015/isprs-archives-XL-7-W4-103-2015.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-7-W4/103/2015/isprs-archives-XL-7-W4-103-2015.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-7-W4/103/2015/isprs-archives-XL-7-W4-103-2015.pdf</self-uri>
<abstract>
<p>Quick mosaicking of wide range remote sensing imagery is an important foundation for land resource survey and dynamic
monitoring of environment and nature disasters. It is also technically important for basis imagery of geographic information
acquiring and geographic information product updating. This paper mainly focuses on one key technique of mosaicking, color
balancing for wide range Remote Sensing imagery. Due to huge amount of data, large covering rage, great variety of climate and
geographical condition, color balancing for wide range remote sensing imagery is a difficult problem. In this paper we use Ecogeographic
regionalization to divide the large area into several regions based on terrains and climatic data, construct the algorithmic
framework of a color balancing method according to the regionalization result, which conduct from region edge to center to fit wide
range imagery mosaicking. The experimental results with wide range HJ-1 dataset show that our method can significantly improve
the wide range of remote sensing imagery color balancing effects: making images well-proportioned mosaicking and better in
keeping images&apos; original information. In summary, this color balancing method based on regionalization could be a good solution for
nationwide remote sensing image color balancing and mosaicking.</p>
</abstract>
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