By Topic

Application of a New Symmetry-Based Cluster Validity Index for Satellite Image Segmentation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Sriparna Saha ; Machine Intell. Unit, Indian Stat. Inst., Kolkata ; Sanghamitra Bandyopadhyay

An important approach for image segmentation is clustering pixels based on their spectral properties. In particular, satellite images contain land cover types, some of which cover significantly large areas, while some (e.g., bridges and roads) occupy relatively much smaller regions. Automatically detecting regions or clusters of such widely varying sizes presents a challenging task. In this letter, a symmetry-based cluster validity index, named Sym-index (Symmetry distance-based index), is proposed. It is able to correctly indicate the presence of clusters of different sizes as long as they are internally symmetrical. A genetic-algorithm-based clustering technique that optimizes the Sym-index is used for image segmentation where the number of clusters is determined automatically. The superiority of the proposed index, as compared to other indices, is established for automatically segmenting the land cover types from SPOT and Indian Remote Sensing satellite images of two different cities in India.

Published in:

IEEE Geoscience and Remote Sensing Letters  (Volume:5 ,  Issue: 2 )