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TitleA semi-automatic segmentation procedure for feature extraction in remotely sensed imagery
AuthorZhang, Q; Pavlic, G; Chen, W; Fraser, R; Leblanc, S; Cihlar, J
SourceComputers and Geosciences vol. 31, no. 3, 2005 p. 289-296,
Alt SeriesNatural Resources Canada, Contribution Series 20181485
PublisherElsevier BV
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; remote sensing
ProgramClimate Change Geoscience
AbstractThis 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