DocumentCode
1902726
Title
Exploring limits in hyperspectral unresolved object detection
Author
Kerekes, John P.
Author_Institution
Chester F. Carlson Center for Imaging Sci., Rochester Inst. of Technol., Rochester, NY, USA
fYear
2011
fDate
24-29 July 2011
Firstpage
4415
Lastpage
4418
Abstract
Hyperspectral imaging systems have been shown to enable unresolved object detection through enhanced spectral characteristics of the data. Robust detection performance prediction tools are desirable for many reasons including optimal system design and operation. The research described in this paper explores the general understanding of system factors that limit detection performance. Examples are shown for detectability limits due to target subpixel fill fraction, sensor noise, and scene complexity.
Keywords
geophysical image processing; geophysical techniques; object detection; enhanced spectral characteristics; hyperspectral imaging system; hyperspectral unresolved object detection; optimal system design; robust detection performance prediction tools; scene complexity; sensor noise; subpixel fill fraction; Atmospheric modeling; Complexity theory; Hyperspectral imaging; Imaging; Noise; Object detection; hyperspectral; performance prediction; system modeling; target detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location
Vancouver, BC
ISSN
2153-6996
Print_ISBN
978-1-4577-1003-2
Type
conf
DOI
10.1109/IGARSS.2011.6050211
Filename
6050211
Link To Document