期刊文献+

多角度高光谱CHRIS数据特点及预处理研究 被引量:3

Characteristics and Preprocessing of Multi-angle Hyperspectral CHIRS Data
在线阅读 下载PDF
导出
摘要 详细地介绍了CHRIS多角度高光谱数据的特点,在图像质量检查的基础上,对CHRIS图像的预处理进行了探讨。通过试验,完成了CHRIS图像的噪声去除、大气校正和正射校正等预处理,取得较好质量的图像,为进一步的应用研究提供了数据保障。 The characteristics of the multi-angle hyperspectral CHRIS data were introduced,and the preprocessing of the CHRIS images based on the quality inspection was discussed.The preprocessing includes noise removal,atmospheric correction and ortho-rectification.The results showed that the manipulation data are favorable for further analysis and application.
作者 曹斌 谭炳香
出处 《安徽农业科学》 CAS 北大核心 2010年第22期12289-12294,共6页 Journal of Anhui Agricultural Sciences
基金 北京市科技计划项目(Z0006321000991) 国家自然科学基金项目(40601070)
关键词 CHRIS 多角度 高光谱 大气校正 正射校正 CHIRS Multi-angle Hyperspectal Atmospheric correction Ortho-rectification
  • 相关文献

参考文献12

  • 1姚延娟,阎广建,王锦地.多光谱多角度遥感数据综合反演叶面积指数方法研究[J].遥感学报,2005,9(2):117-122. 被引量:21
  • 2朱娟娟.多角度遥感现状与发展[J].中国高新技术企业,2008(12):72-72. 被引量:2
  • 3高峰,朱启疆.植被冠层多角度遥感研究进展[J].地理科学,1997,17(4):346-355. 被引量:14
  • 4GARCIA J C,MORENO J.Removol of noises in CHRIS/PROBA images:application to the SPARC campaign data[C].Frascati,Italy:Proc.of the 2nd CHRIS/Proba Workshop,ESA/ESRIN,2004:72-84.
  • 5DAVID G G,DYK A,HAN T,et al.Multi-temporal evaluation with CHRIS of coastal forests[J].IEEE International,2005,5(7):3557-3560.
  • 6KAYITAKIRE F,DEFOURNY P.Forest type discrimination using multi-angle hyperspectral data[C].Frascati,Italy:Proc.of the 2nd CHRIS/Proba Workshop,ESA/ESRIN,2004:72-48.
  • 7盖利亚,刘正军,张继贤.CHRIS/PROBA高光谱数据的预处理[J].测绘工程,2008,17(1):40-43. 被引量:11
  • 8ROBERT A SCBOWENGERDT.Remote sensing modals and methods for image processing[M].ACADEMIC Press,1997.
  • 9MANNHEIM S,HEIM B,SEGL K,et al.Monitoring of lake water quality using hyperspectral CHRIS-PROBA[C].Frascati,Italy:Farscati,Italy:Proc.of the 2nd CHRIS/Proba workshop,ESA/ESRIN,2004.
  • 10BARDUCCI A,GUZZI D,MARCOIONNI P,et al.CHRIS-PROBA performance evaluation,signal-to-noise ratio,instrument efficiency and data quality from acquisitions over san rossore test site[C].Frascati,Italy:Proc of 3rd.ESA CHRIS/PROBA Workshop,2006:21-23.

二级参考文献32

共引文献52

同被引文献53

  • 1李艳华,丁建丽,闫人华.基于国产GF-1遥感影像的山区细小水体提取方法研究[J].资源科学,2015,37(2):408-416. 被引量:62
  • 2徐涵秋.基于压缩数据维的城市建筑用地遥感信息提取[J].中国图象图形学报(A辑),2005,10(2):223-229. 被引量:106
  • 3李小曼,王刚,田杰.TM影像中水体提取方法研究[J].西南农业大学学报(自然科学版),2006,28(4):580-582. 被引量:40
  • 4张兵.高连如.高光谱图像分类与目标探测[M].北京:科学出版社,2011.
  • 5张良培,张立福.高光谱遥感[M].北京:测绘出版社,2011:1-3.
  • 6Anna M S, Annamaria C, Mariangela D, et al. Combined approach based on principal component analysis and canonical discriminant analysis for investigation hyperspectral plant response[J]. Italian Journal of Agronomy, 2012, 7(3): 247-253.
  • 7Chen G Y, Qian S E. Denoising of hyperspectral imagery using principal component analysis and wavelet shrinkage[J]. IEEE Transactions on Geoscience & Remote Sensing, 2011, 49(3): 973-980.
  • 8Koksal E S. Hyperspectral reflectance data processing through cluster and principal component analysis for estimating irrigation and yield related indicators[J]. Agricultural Water Management, 2011, 98(8): 1317-1328.
  • 9Qian D, Fowler J E. Low-complexity principal component analysis for hyperspectral image compression[J]. International Journal of High Performance Computing Applications, 2008, 22(4): 438-448.
  • 10Jaime Z, Ren J C, Ren J, et al. Structured covariance principal component analysis for real-time onsite featureextraction and dimensionality reduction in hyperspectral imaging[J]. Applied Optics, 2014, 53(20): 4440-4449.

引证文献3

二级引证文献8

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部