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A novel compression algorithm for LiDAR data
Light Detection and Ranging (LiDAR) data compression is a critical research field for data processing during past few years because of the large storage size. When LiDAR has small number of data points, the surface generation represented by interpolation methods may be inefficient. This paper presen...
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creator | Ruoyu Du Hyo Jong Lee |
description | Light Detection and Ranging (LiDAR) data compression is a critical research field for data processing during past few years because of the large storage size. When LiDAR has small number of data points, the surface generation represented by interpolation methods may be inefficient. This paper presents a compression algorithm to simplify the LiDAR data set, which is constructed based on the quad-tree structure, for fast preprocessing step. The related theory and the methods to make it reality are discussed in detail respectively. Some conclusions were induced from tests: the method presented in this paper can provide multiple compression ratios based on needs, and guarantee the accuracy of LiDAR data for each case. |
doi_str_mv | 10.1109/CISP.2012.6469993 |
format | conference_proceeding |
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When LiDAR has small number of data points, the surface generation represented by interpolation methods may be inefficient. This paper presents a compression algorithm to simplify the LiDAR data set, which is constructed based on the quad-tree structure, for fast preprocessing step. The related theory and the methods to make it reality are discussed in detail respectively. Some conclusions were induced from tests: the method presented in this paper can provide multiple compression ratios based on needs, and guarantee the accuracy of LiDAR data for each case.</description><identifier>ISBN: 9781467309653</identifier><identifier>ISBN: 1467309656</identifier><identifier>EISBN: 9781467309639</identifier><identifier>EISBN: 146730963X</identifier><identifier>EISBN: 1467309648</identifier><identifier>EISBN: 9781467309646</identifier><identifier>DOI: 10.1109/CISP.2012.6469993</identifier><language>eng</language><publisher>IEEE</publisher><subject>Accuracy ; Buildings ; Data compression ; Data structures ; Laser radar ; LiDAR data ; quad-tree ; Remote sensing ; Surface treatment</subject><ispartof>2012 5th International Congress on Image and Signal Processing, 2012, p.987-991</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6469993$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6469993$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ruoyu Du</creatorcontrib><creatorcontrib>Hyo Jong Lee</creatorcontrib><title>A novel compression algorithm for LiDAR data</title><title>2012 5th International Congress on Image and Signal Processing</title><addtitle>CISP</addtitle><description>Light Detection and Ranging (LiDAR) data compression is a critical research field for data processing during past few years because of the large storage size. When LiDAR has small number of data points, the surface generation represented by interpolation methods may be inefficient. This paper presents a compression algorithm to simplify the LiDAR data set, which is constructed based on the quad-tree structure, for fast preprocessing step. The related theory and the methods to make it reality are discussed in detail respectively. Some conclusions were induced from tests: the method presented in this paper can provide multiple compression ratios based on needs, and guarantee the accuracy of LiDAR data for each case.</description><subject>Accuracy</subject><subject>Buildings</subject><subject>Data compression</subject><subject>Data structures</subject><subject>Laser radar</subject><subject>LiDAR data</subject><subject>quad-tree</subject><subject>Remote sensing</subject><subject>Surface treatment</subject><isbn>9781467309653</isbn><isbn>1467309656</isbn><isbn>9781467309639</isbn><isbn>146730963X</isbn><isbn>1467309648</isbn><isbn>9781467309646</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpVj8tKxDAYhSMiKGMfQNzkAWzNpfmTf1mqjgMFxct6SHPRSDsZ2iL49g44G1eH88H54BByxVnFOcPbdvP6XAnGRQU1IKI8IQVqw2vQkiFIPP3XlTwnxTx_McYOcxBQX5Cbhu7ydxioy-N-CvOc8o7a4SNPafkcacwT7dJd80K9XewlOYt2mENxzBV5f7h_ax_L7mm9aZuuTFyrpYyoXTQSlRUawXNjem0gcBZZEOg8Qu2c9_aA0EsA3itZC6Vib3XPI8gVuf7zphDCdj-l0U4_2-NH-QuN2EMy</recordid><startdate>201210</startdate><enddate>201210</enddate><creator>Ruoyu Du</creator><creator>Hyo Jong Lee</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201210</creationdate><title>A novel compression algorithm for LiDAR data</title><author>Ruoyu Du ; Hyo Jong Lee</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-f97cf8395a2796d188b786e10f0e29cd964ccdda6e19d3661b534255fba7b1f63</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Accuracy</topic><topic>Buildings</topic><topic>Data compression</topic><topic>Data structures</topic><topic>Laser radar</topic><topic>LiDAR data</topic><topic>quad-tree</topic><topic>Remote sensing</topic><topic>Surface treatment</topic><toplevel>online_resources</toplevel><creatorcontrib>Ruoyu Du</creatorcontrib><creatorcontrib>Hyo Jong Lee</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library Online</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ruoyu Du</au><au>Hyo Jong Lee</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A novel compression algorithm for LiDAR data</atitle><btitle>2012 5th International Congress on Image and Signal Processing</btitle><stitle>CISP</stitle><date>2012-10</date><risdate>2012</risdate><spage>987</spage><epage>991</epage><pages>987-991</pages><isbn>9781467309653</isbn><isbn>1467309656</isbn><eisbn>9781467309639</eisbn><eisbn>146730963X</eisbn><eisbn>1467309648</eisbn><eisbn>9781467309646</eisbn><abstract>Light Detection and Ranging (LiDAR) data compression is a critical research field for data processing during past few years because of the large storage size. When LiDAR has small number of data points, the surface generation represented by interpolation methods may be inefficient. This paper presents a compression algorithm to simplify the LiDAR data set, which is constructed based on the quad-tree structure, for fast preprocessing step. The related theory and the methods to make it reality are discussed in detail respectively. Some conclusions were induced from tests: the method presented in this paper can provide multiple compression ratios based on needs, and guarantee the accuracy of LiDAR data for each case.</abstract><pub>IEEE</pub><doi>10.1109/CISP.2012.6469993</doi><tpages>5</tpages></addata></record> |
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subjects | Accuracy Buildings Data compression Data structures Laser radar LiDAR data quad-tree Remote sensing Surface treatment |
title | A novel compression algorithm for LiDAR data |
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