Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Multi-resolution Segmentation and Shape Analysis for Remote Sensing Image Classification
 

Summary: Multi-resolution Segmentation and Shape Analysis
for Remote Sensing Image Classification
Selim Aksoy and H. G¨okhan Akc¸ay
Bilkent University
Department of Computer Engineering
Bilkent, 06800, Ankara, Turkey
{saksoy,akcay}@cs.bilkent.edu.tr
Abstract-- We present an approach for classification of re-
motely sensed imagery using spatial information extracted from
multi-resolution approximations. The wavelet transform is used
to obtain multiple representations of an image at different reso-
lutions to capture different details inherently found in different
structures. Then, pixels at each resolution are grouped into con-
tiguous regions using clustering and mathematical morphology-
based segmentation algorithms. The resulting regions are mod-
eled using the statistical summaries of their spectral, textural and
shape properties. These models are used to cluster the regions,
and the cluster memberships assigned to each region in multiple
resolution levels are used to classify the corresponding pixels
into land cover/land use categories. Final classification is done

  

Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University

 

Collections: Computer Technologies and Information Sciences