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FN ISI Export Format
VR 1.0
PT  C
AU  Xu, YJ
Hu, GD
Chen, ZJ
AF  Xu, Yuanjin
Hu, Guangdao
Chen, Zhijun
ED  Lei, J; Yu, J; Zhou, SG
TI  Application of spectral exhaustive method for object identification and mapping using EO-1 hyperion data
SO  FOURTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 2, PROCEEDINGS
LA  English
DT  Proceedings Paper
CT  4th International Conference on Fuzzy Systems and Knowledge Discovery
CY  AUG 24-27, 2007
CL  Haikou, PEOPLES R CHINA
SP  Hainan Univ, IEEE Reliabil Soc, Asia Pacific Neural Network Assembly
DE  hyperspectral image; the spectral exhaustive method (SEM); object identification
ID  HYPERSPECTRAL DATA; MINERALS
AB  Due to the uncertainty of thresholds, different results are often obtained in object identification and classification of the same hyperspectral image. This paper presents a new approach to object identification based on the spectral exhaustive method (SEM). Each pixel spectrum in hyperspectral imagery has an optimal matching spectrum (OMS) among all possible spectra that are correlated with the study area by an algorithm for computing the maximal angle cosine or correlation coefficient. Hyperspectral image is mapped using OMS with different colors so that all pixels can be identified. Thus, the image becomes a color map in which those pixels corresponding to the same OMS have the same color. A gray map is created by calculating the correlation coefficient between each pixel spectrum and its OMS to determine the degree of match. This approach requires all possible reference spectra, mostly from the spectral library (built by us), and various pretreatments of the hyperspectral data. This approach was applied to an EO-1 Hyperion hyperspectral image of the Pulang area, Zhongdian county, Yunnan province, China, to obtain identification maps of the study area. Examination of the outlined objects in the map indicated that the SEM-based approach is effective.
C1  [Xu, Yuanjin; Hu, Guangdao; Chen, Zhijun] China Univ Geosci, Inst Math Geol & Remote Sensing Geol, Wuhan 430074, Peoples R China.
RP  Xu, YJ, China Univ Geosci, Inst Math Geol & Remote Sensing Geol, Wuhan 430074, Peoples R China.
NR  8
TC  0
PU  IEEE COMPUTER SOC
PI  LOS ALAMITOS
PA  10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
PY  2007
BP  124
EP  128
PG  5
SC  Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; Engineering, Electrical & Electronic
GA  BHE43
UT  ISI:000252460300025
ER  

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