Decision surfaces of binary tests in hyperspectral detection / François Bouffard, DRDC Valcartier.: D68-4/098-2013E-PDF
"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.
Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.878037&sl=0
Department/Agency | Canada. Defence R&D Canada. Defence R&D Canada - Valcartier. |
---|---|
Title | Decision surfaces of binary tests in hyperspectral detection / François Bouffard, DRDC Valcartier. |
Series title | Technical report ; DRDC Valcartier TR 2013-098 |
Publication type | Series - View Master Record |
Language | [English] |
Format | Electronic |
Electronic document | |
Note(s) | "April 2013." Includes bibliographical references (pages 29-30). Includes abstracts and summaries in English and French. |
Publishing information | Québec QC : Defence Research and Development Canada - Valcartier, 2013. ©2013 |
Author / Contributor | Bouffard, François, author. |
Description | 1 online resource (x, 30 pages, 2 unnumbered pages) : illustrations. |
Catalogue number |
|
Subject terms | Remote sensing |
Request alternate formats
To request an alternate format of a publication, complete the Government of Canada Publications email form. Use the form’s “question or comment” field to specify the requested publication.- Date modified: