Encoding Methods of Spectral Vector in Hyperspectral Romote Sensing Image

作     者：杜培军 方涛 唐宏 施鹏飞 

作者机构：Department of Remote Sensing and Geographical Information Science China University of Mining and Technology Xuzhou 221008 P.R. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P.R. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P.R. China 

出 版 物：《Journal of Shanghai University(English Edition)》 (上海大学学报（英文版）)

年 卷 期：2005年第9卷第1期

页      面：52-57页

学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 09[农学] 0804[工学-仪器科学与技术] 0903[农学-农业资源与环境] 0816[工学-测绘科学与技术] 081602[工学-摄影测量与遥感] 081102[工学-检测技术与自动化装置] 0811[工学-控制科学与工程] 

基　　金：theNationalHighTechnologyResearchandDevelopmentProgramofChina(GrantNo.2001AA135091) theNationalNaturalScienceFoundationofChina(GrantNo.60275021) andChinaPostdoctoralScienceFoundation(GrantNo.2002032152) 

主　　题：hyperspectral remote sensing spectral vector encoding similarity measure spectral angle. 

摘      要：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.