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Segmentation of high-resolution multispectral image based on extended morphological profiles
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
2007 (English)In: IGARSS 2007: 2007 IEEE International Geoscience and Remote Sensing Symposium, IEEE , 2007, p. 1481-1484Conference paper, Published paper (Refereed)
Abstract [en]

High-resolution multispectral remote sensing image provides both spectral and structural information about land cover/land use types. In segmentation of such complex image scenes with obvious texture, the efficient image segmentation is required. In this study, a method for high resolution image segmentation based on the extended morphological profiles is proposed. First, fundamental morphological vector operations (erosion and dilation) are defined by the extension, taking into account the spatial and spectral information in simultaneous fashion. Theoretical definitions of extended morphological operations are used in the formal definition of the concept of extended morphological profiles, which is constructed based on the repeated use of openings and closings by reconstruction with a structuring element (SE) of increasing size. Then, the morphological multiscale characteristic (MMC) of each pixel is gained through the derivative of the extended morphological profiles (DEMP). A modified method was proposed to obtain the right morphological characteristics of the pixel, which will be used for the final segmentation results. Finally, a simple region merging method based on the distance between two centroids of the neighboring regions was adopted to further improve the segmentation result. The proposed approach is applied to high-resolution QuickBird multispectral images from urban, agricultural and forest areas for evaluation and comparison with existing methods, in terms of qualitative visual inspection and quantitative criteria. The proposed method demonstrated better performance than the classical morphological segmentation approaches.

Place, publisher, year, edition, pages
IEEE , 2007. p. 1481-1484
Keywords [en]
Extended morphological profile, Quantitative evaluation, Region merging, Segmentation
National Category
Geology Remote Sensing
Identifiers
URN: urn:nbn:se:kth:diva-154944DOI: 10.1109/IGARSS.2007.4423088ISI: 000256657301153Scopus ID: 2-s2.0-82355164201ISBN: 1424412129 (print)ISBN: 978-142441212-9 OAI: oai:DiVA.org:kth-154944DiVA, id: diva2:761553
Conference
2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007, 23 June 2007 through 28 June 2007, Barcelona, Spain
Note

QC 20141107

Available from: 2014-11-07 Created: 2014-10-29 Last updated: 2014-11-07Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf