| Encoding Methods of Spectral Vector in Hyperspectral Romote Sensing Image |
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| 作者姓名： | 方涛 唐宏 施鹏飞 |
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| 作者单位： | InstituteofImageProcessingandPatternRecognition,ShanghaiJiaotongUniversity,Shanghai200030,P.R.China |
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| 基金项目： | theNationalHighTechnologyResearchandDevelopmentProgramofChina(GrantNo.2001AA135091),theNationalNaturalScienceFoundationofChina(GrantNo.60275021),andChinaPostdoctoralScienceFoundation(GrantNo.2002032152) |
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| 摘 要： | 1 Introduction Withtherapiddevelopmentofhyperspectralremotesensing(RS)informationacquisitiontechniques,manyhyperspectralRSinformationsources,forexample,AVIRIS,OMIS,PHI,etc.,havebecomeavailable.ThisstimulateswideapplicationsandrapidprogressofhyperspectralRSinvariousfieldssuchasresources,environments,urbandevelopment,ecologyandothers1,2].WiththeaccumulationofvasthyperspectralRSinformation,itissignificanttoretrieveinterestedimagesforgiventasksquicklyfromlargeinformationsystems(ordataba…
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| 关 键 词： | 高光谱遥感影像 光谱向量 编码方法 相似性测度 光谱角 |
| 收稿时间： | 25 August 2003 |
Encoding methods of spectral vector in hyperspectral romote sensing image |
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| Du?Pei-jun,Fang?Tao,Tang?Hong,Shi?Peng-fei.Encoding Methods of Spectral Vector in Hyperspectral Romote Sensing Image[J].Journal of Shanghai University(English Edition),2005,9(1):52-57. |
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| Authors: | Du Pei-jun Fang Tao Tang Hong Shi Peng-fei |
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| Institution: | (1) Department of Remote Sensing and Geographical Information Science, China University of Mining and Technology, 221008 Xuzhou, P.R. China;(2) Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai, P.R. China |
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| Abstract: | Taking into account the demands of hyperspectral remote sensing(RS) image retrieval and processing, some encoding methods of spectral vector including direct encoding, feature-based encoding and tree-based encoding methods are proposed and compared. In direct encoding, based on the analysis of binary encoding and quad-value encoding, decimal encoding is proposed. It is proved that quad-value encoding and decimal encoding are suitable to fast processing and retrieval. In absorption feature-based encoding method, five common metrics are compared. Because locations of reflection/absorption features are sensitive to noise, this method is not very effective in retrieval. In tree-based encoding methods, bitree, quadtree, octree and hextree are proposed and discussed. It is proved that 2-level octree and 2-level hextree are more effective than bitree and quadtree. Finally, quad-value encoding, decimal encoding, 2-level octree and 2-level hextree are proposed in spectral vectors encoding, similarity measure and hyperspectral RS image retrieval. |
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| Keywords: | hyperspectral remote sensing spectral vector encoding similarity measure spectral angle |
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