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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/isprs-archives-XLII-3-W3-47-2017</article-id>
<title-group>
<article-title>SOFTWARE FRAMEWORK FOR HYPERSPECTRAL DATA EXPLORATION AND PROCESSING IN MATLAB</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Eskelinen</surname>
<given-names>M. A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>University of Jyväskylä, Faculty of Information Technology, Jyväskylä, Finland</addr-line>
</aff>
<pub-date pub-type="epub">
<day>19</day>
<month>10</month>
<year>2017</year>
</pub-date>
<volume>XLII-3/W3</volume>
<fpage>47</fpage>
<lpage>50</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2017 M. A. Eskelinen</copyright-statement>
<copyright-year>2017</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-W3/47/2017/isprs-archives-XLII-3-W3-47-2017.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-3-W3/47/2017/isprs-archives-XLII-3-W3-47-2017.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-3-W3/47/2017/isprs-archives-XLII-3-W3-47-2017.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-3-W3/47/2017/isprs-archives-XLII-3-W3-47-2017.pdf</self-uri>
<abstract>
<p>This paper presents a user introduction and a general overview of the MATLAB software package &lt;tt&gt;hsicube&lt;/tt&gt; developed by the author for
simplifying the data manipulation and visualization tasks often encountered in hyperspectral analysis work, and the design principles
and software development methods used by the author. The framework implements methods for slicing, masking, visualization and
application of existing functions to hyperspectral data cubes without the need to use explicit indexing or reshaping, as well as enabling
expressive syntax for combining these operations on the command line for highly efficient data analysis workflows. It also includes
utilities for interfacing with existing file reader scripts for easy access to files using the framework. The &lt;tt&gt;hsicube&lt;/tt&gt; framework is released
as open source to promote the free use and peer review of the code and enable collaborative development.</p>
</abstract>
<counts><page-count count="4"/></counts>
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