000	02247cam  2200361zi 4500
001	9.878037
003	CaOODSP
005	20221107165130
006	m     o  d f
007	cr cn|||||||||
008	190815t20132013quca    ob   f000 0 eng d
040	|aCaOODSP|beng|erda|cCaOODSP
041	0 |aeng|beng|bfre
043	|an-cn---
086	1 |aD68-4/098-2013E-PDF
100	1 |aBouffard, François, |eauthor.
245	10|aDecision surfaces of binary tests in hyperspectral detection / |cFrançois Bouffard, DRDC Valcartier.
264	1|aQuébec QC : |bDefence Research and Development Canada - Valcartier, |c2013.
264	4|c©2013
300	|a1 online resource (x, 30 pages, 2 unnumbered pages) : |billustrations.
336	|atext|btxt|2rdacontent
337	|acomputer|bc|2rdamedia
338	|aonline resource|bcr|2rdacarrier
490	1 |aTechnical report ; |vDRDC Valcartier TR 2013-098
500	|a"April 2013."
504	|aIncludes bibliographical references (pages 29-30).
520	3 |a"This report is first and foremost an analysis of the decision surfaces associated with common detection statistics used for hyperspectral target detection. The intention is to clarify the process leading to detection using those statistics and show where their differences and similarities lie. The large number of available detection statistics, along with their numerous parameters, makes formal comparisons complicated and sometimes produce ambiguous or uncertain conclusions. This document tries to establish a solid framework on which to base this analysis and then demonstrates how detection statistics can be grouped in distinct classes based on their decision surface's geometry. In doing so, possibly new detection statistics (or methods that can be used to build them) are exposed"--Abstract, page i.
546	|aIncludes abstracts and summaries in English and French.
692	07|2gccst|aRemote sensing
710	1 |aCanada. |bDefence R&D Canada.
710	2 |aDefence R&D Canada - Valcartier.
830	#0|aTechnical report (Defence R&D Canada)|vDRDC Valcartier TR 2013-098.|w(CaOODSP)9.820558
856	40|qPDF|s25.59 MB|uhttps://publications.gc.ca/collections/collection_2019/rddc-drdc/D68-4-098-2013-eng.pdf