Unmixing method for hyperspectral data based on sub-space method with learning process

Details Unmixing method for hyperspectral data based on sub-space method with learning process Unmixing method for hyperspectral data based on sub-space method with learning process

Aug 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009adspr..44..517a&link_type=abstract

Advances in Space Research, Volume 44, Issue 4, p. 517-523.

Computer Science

Learning

Scientific paper

An unmixing method for hyperspectral Earth observation satellite imagery data is proposed. It is based on a sub-space method with learning process. The proposed method utilizes a sub-space for feature space during unmixing. It is used to be done in a feature space which consists of spectral bands of observation vectors. As the results from the experiments with airborne based hyperspectral imagery data, AVIRIS, it is found that the proposed unmixing is superior to the other existing method in terms of decomposition accuracy and the process time required for the decompositions.

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