Cluster-space hyperspectral data representation for mixed pixel analysis

Author

Jia, Xiuping

Author_Institution

Sch. of Electr. Eng., New South Wales Univ., Campbell, ACT, Australia

Volume

5

fYear

2000

fDate

2000

Firstpage

2167

Abstract

The probabilistic mixture model for sub-pixel analysis is investigated and further developed. The probability distribution for each endmember is estimated by using a cluster-space data representation which is adaptable to individual class data distribution shapes. The proposed method is easy to implement and suitable for hyperspectral image data processing. Experiments using HyMap data are presented, showing the detailed sub-pixel estimation

Keywords

geophysical signal processing; geophysical techniques; multidimensional signal processing; remote sensing; terrain mapping; cluster space data representation; cluster-space hyperspectral data representation; endmember; geophysical measurement technique; hyperspectral remote sensing; image processing; land surface; mixed pixel analysis; multidimensional signal processing; multispectral remote sensing; probabilistic mixture model; probability distribution; sub-pixel analysis; subpixel estimation; terrain mapping; Australia; Educational institutions; Electronic mail; Equations; Gaussian distribution; Hyperspectral imaging; Hyperspectral sensors; Probability distribution; Shape; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-6359-0

Type

conf

DOI

10.1109/IGARSS.2000.858344

Filename

858344