NDLI: Sub-pixel target spectra estimation and detection using functions of multiple instances

Content Provider	IEEE Xplore Digital Library
Author	Zare, A. Gader, P. Bolton, J. Yuksel, S. Dubroca, T. Close, R. Hummel, R.
Copyright Year	2011
Description	Author affiliation: Computer and Information Science and Engineering, University of Florida (Gader, P.; Bolton, J.; Yuksel, S.; Close, R.) \|\| Material Science and Engineering, University of Florida (Dubroca, T.; Hummel, R.) \|\| Electrical and Computer Engineering, University of Missouri (Zare, A.)
Abstract	The Functions of Multiple Instances (FUMI) method for learning target pattern and non-target patterns is introduced and extended. The FUMI method differs significantly from traditional supervised learning algorithms because only functions of target patterns are available. Moreover, these functions are likely to involve other non-target patterns. In this paper, data points which are convex combinations of a target prototype and several non-target prototypes are considered. The Convex-FUMI (C-FUMI) method learns the target and non-target patterns, the number of non-target patterns, and the weights (or proportions) of all the prototypes for each data point. For hyperspectral image analysis, the target and non-target prototypes estimated using C-FUMI are the end-members for the target material and non-target (background) materials. For this method, training data need only binary labels indicating whether a data point contains or does not contain some proportion of the target endmember; the specific target proportions for the training data are not needed. In this paper, the C-FUMI algorithm is extended to incorporate weights for training data such that target and non-target training data sets are balanced (resulting in the Weighted C-FUMI algorithm). After learning the target prototype using the binary-labeled training data, target detection is performed on test data. Results showing sub-pixel explosives detection and sub-pixel target detection on simulated data are presented.
Starting Page	1
Ending Page	4
File Size	311682
Page Count	4
File Format	PDF
ISBN	9781457722028
ISSN	21586268
e-ISBN	9781457722011
DOI	10.1109/WHISPERS.2011.6080874
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-06
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Prototypes Training data Materials Explosives Equations Hyperspectral imaging
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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