Image fusion algorithm in Intelligent Transport System
Traffic congestion has been increasing world-wide as a result of increased motorization, urbanization, population growth and changes in population density. Interest in intelligent transport system (ITS) comes from the problems caused by traffic congestion and a synergy of new information technologie...
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creator | Zeng Min Wang Zhao Xuan Yang Yang Chen Jia Peng Wu Xue Wen Ding |
description | Traffic congestion has been increasing world-wide as a result of increased motorization, urbanization, population growth and changes in population density. Interest in intelligent transport system (ITS) comes from the problems caused by traffic congestion and a synergy of new information technologies for simulation, real-time control and communications networks. Successful implementation of ITS depends upon complete and accurate vehicle information. An image fusion algorithm based on lifting wavelet transform (LWT) is presented in this paper to combine an infrared image and a visible light image into a single composite image. A new image fusion method is proposed in this paper: after lifting wavelet transform, mean gradient are used to determine the coefficients in fusion formula for low frequency component. Local deviation rules are applied to merge the high frequency coefficients. Experimental results have shown that most of the final composite images have better quality than either of the source images. The results indicate that application of this algorithm improves performance of ITS. |
doi_str_mv | 10.1109/ICMLC.2008.4620381 |
format | Conference Proceeding |
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Interest in intelligent transport system (ITS) comes from the problems caused by traffic congestion and a synergy of new information technologies for simulation, real-time control and communications networks. Successful implementation of ITS depends upon complete and accurate vehicle information. An image fusion algorithm based on lifting wavelet transform (LWT) is presented in this paper to combine an infrared image and a visible light image into a single composite image. A new image fusion method is proposed in this paper: after lifting wavelet transform, mean gradient are used to determine the coefficients in fusion formula for low frequency component. Local deviation rules are applied to merge the high frequency coefficients. Experimental results have shown that most of the final composite images have better quality than either of the source images. 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The results indicate that application of this algorithm improves performance of ITS.</description><subject>Artificial neural networks</subject><subject>Image fusion</subject><subject>Intelligent Transport System (ITS)</subject><subject>lifting wavelet transform</subject><subject>Manganese</subject><subject>Real time systems</subject><subject>Transforms</subject><subject>Vehicles</subject><subject>Wavelet transforms</subject><issn>2160-133X</issn><isbn>1424420954</isbn><isbn>9781424420957</isbn><isbn>9781424420964</isbn><isbn>1424420962</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kLFOwzAYhI2gEm3JC8DiF0j4_dux4xFFUCIFMVAktspJ7GCUpFVshr49RZRbTjd8p9MRcssgYwz0fVW-1GWGAEUmJAIv2AVJtCqYQCEQtBSXZPUfcnFFlsgkpIzzjwVZ_XIaQCh2TZIQvuAkrnPJcUlkNZreUvcd_H6iZuj3s4-fI_UTraZoh8H3dop0O5spHPZzpG_HEO14QxbODMEmZ1-T96fHbfmc1q-bqnyoU89UHtPWGZerppCdVLxBrVznioZJ5A5Zg61p0IJprbYWMDcdOK4ECNEIdhotHF-Tu79eb63dHWY_mvm4O3_AfwBhREuJ</recordid><startdate>200807</startdate><enddate>200807</enddate><creator>Zeng Min Wang</creator><creator>Zhao Xuan Yang</creator><creator>Yang Chen</creator><creator>Jia Peng Wu</creator><creator>Xue Wen Ding</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200807</creationdate><title>Image fusion algorithm in Intelligent Transport System</title><author>Zeng Min Wang ; Zhao Xuan Yang ; Yang Chen ; Jia Peng Wu ; Xue Wen Ding</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-cfaf57b86d673b297fdf8b1623f21b2cab2e0ace9ee025ad0f374044b412004f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Artificial neural networks</topic><topic>Image fusion</topic><topic>Intelligent Transport System (ITS)</topic><topic>lifting wavelet transform</topic><topic>Manganese</topic><topic>Real time systems</topic><topic>Transforms</topic><topic>Vehicles</topic><topic>Wavelet transforms</topic><toplevel>online_resources</toplevel><creatorcontrib>Zeng Min Wang</creatorcontrib><creatorcontrib>Zhao Xuan Yang</creatorcontrib><creatorcontrib>Yang Chen</creatorcontrib><creatorcontrib>Jia Peng Wu</creatorcontrib><creatorcontrib>Xue Wen Ding</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>Zeng Min Wang</au><au>Zhao Xuan Yang</au><au>Yang Chen</au><au>Jia Peng Wu</au><au>Xue Wen Ding</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Image fusion algorithm in Intelligent Transport System</atitle><btitle>2008 International Conference on Machine Learning and Cybernetics</btitle><stitle>ICMLC</stitle><date>2008-07</date><risdate>2008</risdate><volume>1</volume><spage>74</spage><epage>77</epage><pages>74-77</pages><issn>2160-133X</issn><isbn>1424420954</isbn><isbn>9781424420957</isbn><eisbn>9781424420964</eisbn><eisbn>1424420962</eisbn><abstract>Traffic congestion has been increasing world-wide as a result of increased motorization, urbanization, population growth and changes in population density. Interest in intelligent transport system (ITS) comes from the problems caused by traffic congestion and a synergy of new information technologies for simulation, real-time control and communications networks. Successful implementation of ITS depends upon complete and accurate vehicle information. An image fusion algorithm based on lifting wavelet transform (LWT) is presented in this paper to combine an infrared image and a visible light image into a single composite image. A new image fusion method is proposed in this paper: after lifting wavelet transform, mean gradient are used to determine the coefficients in fusion formula for low frequency component. Local deviation rules are applied to merge the high frequency coefficients. Experimental results have shown that most of the final composite images have better quality than either of the source images. The results indicate that application of this algorithm improves performance of ITS.</abstract><pub>IEEE</pub><doi>10.1109/ICMLC.2008.4620381</doi><tpages>4</tpages></addata></record> |
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ispartof | 2008 International Conference on Machine Learning and Cybernetics, 2008, Vol.1, p.74-77 |
issn | 2160-133X |
language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Artificial neural networks Image fusion Intelligent Transport System (ITS) lifting wavelet transform Manganese Real time systems Transforms Vehicles Wavelet transforms |
title | Image fusion algorithm in Intelligent Transport System |
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