DocumentCode :
3271768
Title :
Correspondence analysis on Landsat TM remote sensing image
Author :
He, Fenqin ; Yin, Jianzhong
Author_Institution :
Sch. of Environ. Sci. & Safety Eng., Tianjin Univ. of Technol., Tianjin, China
Volume :
5
fYear :
2010
fDate :
16-18 Oct. 2010
Firstpage :
2154
Lastpage :
2157
Abstract :
Taking Mentougou district in the west of Beijing for example, the authors discussed Correspondence Analysis (CA) on TM remote sensing image. The experimental results showed that, CA developed on the basis of Principal Component Analysis (PCA) involved more than 98% information from the original TM image. Thereinto, the first component covered upwards of 88% information. The first component almost concentrated entirely useful information, while the rest components were mainly noise information. The intensity component of CA better represented the brightness values throughout the whole data compared to PCA. In addition, CA not only considered the relationship among bands, also the correlation between each band and surface features, which definitely expressed the physical meaning of each component and made up the limitation of PCA.
Keywords :
geophysical image processing; principal component analysis; remote sensing; Landsat TM remote sensing image; PCA; correspondence analysis; principal component analysis; Brightness; Correlation; Earth; Eigenvalues and eigenfunctions; Loading; Principal component analysis; Remote sensing; Correspondence Analysis(CA); Principal Component Analysis(PCA); TM; remote sensing image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
Type :
conf
DOI :
10.1109/CISP.2010.5647592
Filename :
5647592
Link To Document :
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