Morphological segmentation of multispectral images for land cover mapping

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents an unsupervised segmentation method applied to multispectral satellite images especially SPOT images. The main objective of this work is to combine spectral and contextual information in order to extract the most important cartographic regions. We choose a mathematical morphology context. Previous morphological works are usually interested in one type of land covering area. The proposed technique globalizes the problem by considering all the important regions to perform complete and automatic multispectral satellite images cartography.

Original languageEnglish
Title of host publication2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
PagesIII326-III329
Edition1
DOIs
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings - Boston, MA, United States
Duration: 6 Jul 200811 Jul 2008

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Number1
Volume3

Conference

Conference2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Country/TerritoryUnited States
CityBoston, MA
Period6/07/0811/07/08

Keywords

  • Mathematical morphology
  • SPOT
  • Satellite images
  • Segmentation

Fingerprint

Dive into the research topics of 'Morphological segmentation of multispectral images for land cover mapping'. Together they form a unique fingerprint.

Cite this