• About
  • Policies
  • What is openaccess
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Kentsel yapıların biçimbilimsel bölütlenmesi

      Thumbnail
      View / Download
      2.0 Mb
      Author
      Akçay, H. Gökhan
      Aksoy, Selim
      Date
      2007-06
      Source Title
      IEEE 15th Signal Processing and Communications Applications, SIU 2007
      Publisher
      IEEE
      Language
      Turkish
      Type
      Conference Paper
      Item Usage Stats
      157
      views
      102
      downloads
      Abstract
      Yüksek çözünürlükteki uzaktan algılamalı uydu görüntülerinde bölütleme kent uygulamalarında önemli bir problemdir çünkü elde edilen bölütlemelerle sınıflandırma için piksel tabanlı spektral bilginin yanında uzamsal ve yapısal bilgiler elde edilebilir. Bu bildiride, biçimbilimsel işlemlerle çıkarılan yapısal bilgi ve ana bileşenler analizi ile özetlenen spektral bilgi kullanılarak gürültüden etkilenmeyen bölütler elde eden bir yöntem sunduk. Yapılan deneyler yöntemin görüntü üzerinde komşuluk bilgisini ve spektral bilgiyi beraber kullanmayan başka bir yönteme göre daha düzgün ve anlamlı yapılar bulduğunu göstermiştir. Automatic segmentation of high-resolution remote sensing imagery is an important problem in urban applications because the resulting segmentations can provide valuable spatial and structural information that are complementary to pixel-based spectral information in classification. We present a method that combines structural information extracted by morphological processing with spectral information summarized using principal components analysis to produce precise segmentations that are also robust to noise. The experiments show that the method is able to detect structures in the image which are more precise and more meaningful than the structures detected by another approach that does not make strong use of neighborhood and spectral information.
      Keywords
      Automatic segmentations
      High-resolution remote sensing
      Morphological processing
      Morphological segmentation
      Principal components analysis
      Spectral informations
      Structural informations
      Urban structures
      Principal component analysis
      Remote sensing
      Space optics
      Signal processing
      Permalink
      http://hdl.handle.net/11693/26969
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2007.4298713
      Collections
      • Department of Computer Engineering 1410
      Show full item record

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy