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<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Annals</journal-id>
<journal-title-group>
<journal-title>ISPRS Annals of the 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-IV-2-W4-99-2017</article-id>
<title-group>
<article-title>POINT-CLOUD COMPRESSION FOR VEHICLE-BASED MOBILE MAPPING SYSTEMS USING PORTABLE NETWORK GRAPHICS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kohira</surname>
<given-names>K.</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>Masuda</surname>
<given-names>H.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Dept. of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, Japan</addr-line>
</aff>
<pub-date pub-type="epub">
<day>13</day>
<month>09</month>
<year>2017</year>
</pub-date>
<volume>IV-2/W4</volume>
<fpage>99</fpage>
<lpage>106</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2017 K. Kohira</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-annals.copernicus.org/articles/IV-2-W4/99/2017/isprs-annals-IV-2-W4-99-2017.html">This article is available from https://isprs-annals.copernicus.org/articles/IV-2-W4/99/2017/isprs-annals-IV-2-W4-99-2017.html</self-uri>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/IV-2-W4/99/2017/isprs-annals-IV-2-W4-99-2017.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/IV-2-W4/99/2017/isprs-annals-IV-2-W4-99-2017.pdf</self-uri>
<abstract>
<p>A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects．Point-clouds of urban areas,
residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the
data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds,
and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data
sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for
vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the
parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed
using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.</p>
</abstract>
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