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
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;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4577-1003-2
DOI :
10.1109/IGARSS.2011.6050211
