SAR image segmentation by mathematical morphology and texture analysis

Author

Ogor, Benoit ; Haese-coat, Véronique ; Ronsin, Joseph

Author_Institution

Lab. ARTIST, Inst. Nat. des Sci. Appliques, Rennes, France

Volume

1

fYear

1996

fDate

27-31 May 1996

Firstpage

717

Abstract

Presents a promising segmentation method for synthetic aperture radar (SAR) imagery designed in the context of agricultural remote sensing using a morphological region based image analysis. The region based approach is really appropriate for land use applications given that land cover is naturally built-up from regions. The method is divided into two principal steps: a morphological image partitioning resulting in a severe oversegmentation and a further region growing process exploiting information from a textural edge detector

Keywords

agriculture; edge detection; geophysical signal processing; geophysical techniques; image segmentation; image texture; mathematical morphology; radar imaging; radar signal processing; remote sensing by radar; spaceborne radar; synthetic aperture radar; SAR imaging; agriculture; geophysical measurement technique; image region analysis; image segmentation; image texture analysis; land cover; land surface; land use; mathematical morphology; morphological image partitioning; radar imaging; radar remote sensing; region growing process; severe oversegmentation; synthetic aperture radar; terrain mapping; textural edge detector; vegetation mapping; Detectors; Filters; Image analysis; Image edge detection; Image reconstruction; Image segmentation; Image texture analysis; Morphology; Optical sensors; Speckle;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International

Conference_Location

Lincoln, NE

Print_ISBN

0-7803-3068-4

Type

conf

DOI

10.1109/IGARSS.1996.516452

Filename

516452