DocumentCode
692811
Title
Improvement of background characterization for hyperspectral target detection
Author
Ben Ma ; Qian Du
Author_Institution
Dept. of Electr. & Comput. Eng., Mississippi State Univ., Starkville, MS, USA
fYear
2012
fDate
4-7 June 2012
Firstpage
1
Lastpage
4
Abstract
In this paper, several background characterization methods are reviewed and evaluated together with widely used unstructured matched filters. Two modified methods of background characterization based on spectral clustering are proposed and implemented. Experiments with in-field hyperspectral dataset are conducted to show the stability and performance improvement of the proposed methods.
Keywords
filtering theory; hyperspectral imaging; object detection; pattern clustering; background characterization method; hyperspectral target detection; in-field hyperspectral dataset; spectral clustering; unstructured matched filters; Abstracts; Detectors; Hyperspectral imaging; Matched filters; Object detection; Radio frequency; background characterization; hyperspectral target detection; matched filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2012 4th Workshop on
Conference_Location
Shanghai
Print_ISBN
978-1-4799-3405-8
Type
conf
DOI
10.1109/WHISPERS.2012.6874264
Filename
6874264
Link To Document