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TitreA semi-automatic segmentation procedure for feature extraction in remotely sensed imagery
AuteurZhang, Q; Pavlic, G; Chen, W; Fraser, R; Leblanc, S; Cihlar, J
SourceComputers and Geosciences vol. 31, no. 3, 2005 p. 289-296, https://doi.org/10.1016/j.cageo.2004.10.003
Année2005
Séries alt.Ressources naturelles Canada, Contribution externe 20181485
ÉditeurElsevier BV
Documentpublication en série
Lang.anglais
DOIhttps://doi.org/10.1016/j.cageo.2004.10.003
Mediapapier; en ligne; numérique
Formatspdf
Sujetstélédétection; géophysique
ProgrammeGéosciences de changements climatiques
Résumé(disponible en anglais seulement)
This paper presents a semi-automatic procedure that integrates thresholding, region growing, and edge detection techniques for feature extraction in remotely sensed imagery. An interface has been developed to provide an interactive platform of the procedure. Thresholding technique is employed to sample object of interest. Estimated properties (i.e., mean and variance) of the sample are applied for feature extraction using region growing. Since the derived object is subject to the sample and initial conditions, edge detection is incorporated to calibrate initial parameters by examining how the derived object matches the local edges inherent in the imagery. The program is loosely linked to PCI (PCI Geomatics, Richmond Hill, Ontario, Canada), a widely distributed image processing software. We demonstrate applications of this procedure by deriving burned scars using SPOT VGT and NOAA AVHRR imagery
GEOSCAN ID311840