Skip to main content
padlock icon - secure page this page is secure

Texture information-based hybrid methodology for the segmentation of SAR images

Buy Article:

$61.00 + tax (Refund Policy)

Image segmentation is one of the crucial tasks in the postprocessing of synthetic aperture radar (SAR) images. However, SAR images are textural in nature, marked by the textural patterns of widely disparate mean intensity values. This renders conventional multi-resolution techniques inefficient for the segmentation of these images. This article proposes a novel technique of combining both intensity and textural information for effective region classification. To achieve this, two new approaches, called Neighbourhood‐based Membership Ambiguity Correction (NMAC) and Dynamic Sliding Window Size Estimation (DSWSE), have been proposed. The results obtained from the two schemes are combined, segregating the image into well-defined regions of distinct textures as well as intensities. Promising results have been obtained over the SAR images of Nordlinger Ries in the Swabian Jura and flood regions near the river Kosi in Bihar, India.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: Department of Electronics and Communication Engineering,Indian Institute of Technology Guwahati, India

Publication date: August 10, 2011

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more