Comparing different thresholding algorithms for segmenting auroras
Extracting aurora oval boundary from spacecraft UV imagery is not a trivial problem. The distinction between aurora and background varies depending on the factors such as the date, time of the day, and satellite position. Thresholding technique is a well-known technique for detecting aurora boundary...
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| creator | Li, X. Ramachandran, R. He, M. Sunil Movva Rushing, J. Graves, S. Lyatsky, W. Arjun Tan Germany, G. |
| description | Extracting aurora oval boundary from spacecraft UV imagery is not a trivial problem. The distinction between aurora and background varies depending on the factors such as the date, time of the day, and satellite position. Thresholding technique is a well-known technique for detecting aurora boundary from satellite imagery. In this study, three distinct thresholding algorithms, mixture modeling, fuzzy sets and entropy thresholding were applied to a selected set of UV images measured on board Polar satellite to examine their effectiveness in aurora boundary detection. Two thresholding approaches were taken: global thresholding and adaptive thresholding. As expected, adaptive thresholding approach showed better results. In addition to these algorithms, another new algorithm (edge-based) was examined using adaptive approach. This thresholding algorithm detects aurora oval by identifying the boundary transition between aurora and background. The results from these different algorithms are presented. |
| doi_str_mv | 10.1109/ITCC.2004.1286718 |
| format | Conference Proceeding |
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The distinction between aurora and background varies depending on the factors such as the date, time of the day, and satellite position. Thresholding technique is a well-known technique for detecting aurora boundary from satellite imagery. In this study, three distinct thresholding algorithms, mixture modeling, fuzzy sets and entropy thresholding were applied to a selected set of UV images measured on board Polar satellite to examine their effectiveness in aurora boundary detection. Two thresholding approaches were taken: global thresholding and adaptive thresholding. As expected, adaptive thresholding approach showed better results. In addition to these algorithms, another new algorithm (edge-based) was examined using adaptive approach. This thresholding algorithm detects aurora oval by identifying the boundary transition between aurora and background. 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This thresholding algorithm detects aurora oval by identifying the boundary transition between aurora and background. The results from these different algorithms are presented.</description><subject>Entropy</subject><subject>Fuzzy sets</subject><subject>Helium</subject><subject>Image edge detection</subject><subject>Lead</subject><subject>Magnetic field measurement</subject><subject>Particle measurements</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>Space vehicles</subject><isbn>0769521088</isbn><isbn>9780769521084</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj01LxDAYhAMiqOv-APHSP9D6pvk-avBjYcHLel6S9k0baTdLUg_-e1fduQzMMwwMIXcUGkrBPGx21jYtAG9oq6Wi-oLcgJJGtBS0viLrUj7hJGa4EeaaPNk0H12Oh6HqYwiY8bBUy5ixjGnqf2M3DSnHZZxLFVKuCg7zqfNHvnLKrtySy-Cmguuzr8jHy_POvtXb99eNfdzWkSq21EoHJmgLptdBy4BgOBXMozdO6q73wghpoNMdhMCFdEqyDn2HnHt0vudsRe7_dyMi7o85zi5_78832Q9L1EoT</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Li, X.</creator><creator>Ramachandran, R.</creator><creator>He, M.</creator><creator>Sunil Movva</creator><creator>Rushing, J.</creator><creator>Graves, S.</creator><creator>Lyatsky, W.</creator><creator>Arjun Tan</creator><creator>Germany, G.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2004</creationdate><title>Comparing different thresholding algorithms for segmenting auroras</title><author>Li, X. ; Ramachandran, R. ; He, M. ; Sunil Movva ; Rushing, J. ; Graves, S. ; Lyatsky, W. ; Arjun Tan ; Germany, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i173t-78f351209d8f86fe094153beb9a68cdb595690c8c0ff456a763cebce44beabd43</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Entropy</topic><topic>Fuzzy sets</topic><topic>Helium</topic><topic>Image edge detection</topic><topic>Lead</topic><topic>Magnetic field measurement</topic><topic>Particle measurements</topic><topic>Remote sensing</topic><topic>Satellites</topic><topic>Space vehicles</topic><toplevel>online_resources</toplevel><creatorcontrib>Li, X.</creatorcontrib><creatorcontrib>Ramachandran, R.</creatorcontrib><creatorcontrib>He, M.</creatorcontrib><creatorcontrib>Sunil Movva</creatorcontrib><creatorcontrib>Rushing, J.</creatorcontrib><creatorcontrib>Graves, S.</creatorcontrib><creatorcontrib>Lyatsky, W.</creatorcontrib><creatorcontrib>Arjun Tan</creatorcontrib><creatorcontrib>Germany, G.</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 (IEL)</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>Li, X.</au><au>Ramachandran, R.</au><au>He, M.</au><au>Sunil Movva</au><au>Rushing, J.</au><au>Graves, S.</au><au>Lyatsky, W.</au><au>Arjun Tan</au><au>Germany, G.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Comparing different thresholding algorithms for segmenting auroras</atitle><btitle>International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004</btitle><stitle>ITCC</stitle><date>2004</date><risdate>2004</risdate><volume>2</volume><spage>594</spage><epage>601 Vol.2</epage><pages>594-601 Vol.2</pages><isbn>0769521088</isbn><isbn>9780769521084</isbn><abstract>Extracting aurora oval boundary from spacecraft UV imagery is not a trivial problem. The distinction between aurora and background varies depending on the factors such as the date, time of the day, and satellite position. Thresholding technique is a well-known technique for detecting aurora boundary from satellite imagery. In this study, three distinct thresholding algorithms, mixture modeling, fuzzy sets and entropy thresholding were applied to a selected set of UV images measured on board Polar satellite to examine their effectiveness in aurora boundary detection. Two thresholding approaches were taken: global thresholding and adaptive thresholding. As expected, adaptive thresholding approach showed better results. 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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Entropy Fuzzy sets Helium Image edge detection Lead Magnetic field measurement Particle measurements Remote sensing Satellites Space vehicles |
| title | Comparing different thresholding algorithms for segmenting auroras |
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